eBook

This eBook explores the use cases for AI in treasury management and corporate finance, as well as the barriers preventing mass adoption of the technology. These technologies are applicable in cash and liquidity management,...

This eBook explores the use cases for AI in treasury management and corporate finance, as well as the barriers preventing mass adoption of the technology. These technologies are applicable in cash and liquidity management, payments fraud detection, documentation of treasury processes, and more. AI/ML Today While artificial intelligence (AI) and machine learning (ML) have gradually worked their way into everyday life in treasury and finance, but we’ve only scratched the surface of their potential. It’s important to understand that AI and ML are not technically the same thing. While the terms are often used interchangeably, they are two distinct technologies. AI is a broader term denoting intelligent machines that can simulate human thinking capability and behavior. ML, in contrast, is an application or subset of AI that enables machines to learn from data without additional programming.1 What makes AI so powerful now, as opposed to just a few years ago? The simple answer is data. We have so much more now than ever before. Both companies and consumers are using a host of applications that generate mass amounts of data, and with the right systems in place, that data can be transformed for better decision-making. Data scientists train AI models on historical data. Next, they run new data through the trained AI model to make much more informed predictions. Such models are incredibly useful for treasury and finance, which have had to make rapid adjustments in recent years to keep organizations running. Applying AI in Treasury Management and Finance With applications proliferating across so many areas, as well as the connectivity that banks and technology providers are building through APIs, treasury and finance departments have more data at their fingertips than ever before. But processing all of that data manually is nearly impossible. That’s where AI comes in. Technology providers train AI models on data that is extracted from operational applications and placed in a central repository. These can vary and have different advantages. Data warehouses store data in hierarchal dimensions and tables. Data lakes, in contrast, store massive amounts of raw data, storing it in flat architectures to allow users more freedom for data management.2 Unlike robotic process automation, which can only replicate processes, AI models can analyze data and identify trends and patterns in a fraction of the time that humans can.3 This allows for much faster and complete conversion of raw data into meaningful information that treasury and finance departments can use. AI models can be used for various treasury functions such as cash forecasting, payments fraud detection, and working capital optimization. For example, AI can drastically improve receivables management. As noted in a recent AFP Treasury in Practice Guide, a technology company’s accounts receivable (AR) team was struggling to manually process over 2,500 monthly checks, leading to major delays. Realizing that it needed to make a change, the AR team worked with its banking partners to implement an machine learning-enabled receivables solution. The solution automated the manual gathering, consolidation and formatting process that the AR team had been doing every morning, allowing most payments to process within two days. Furthermore, over time, the machine continues to learn from exceptions, improving accuracy. It has also provided the AR team with more opportunities to increase electronic payments adoption. How Machine Learning Works for Treasury Payments Fraud Detection Modern payments fraud detection software uses AI to screen payments against historical payment data pulled from a data source. All the characteristics of payments—the payment amounts, payment types, the number of payments, where they’re going, etc.—reside within that data source. A machine then analyzes that data, which enables it to identify anomalies in future activity. A number of different models can be used to pinpoint those anomalies. One of the most effective is an isolation forest methodology. This model compares all the different variables in the data source against new payments to determine the normality of those payments. Any payment that has an unusually high abnormality rank is flagged and set aside for further review. Machine learning solutions can even show users that variable comparison, providing them with insights into how that normality/abnormality rank is calculated. Users can even set their own levels for abnormality tolerance. Companies that work in industries that are high targets for fraudulent activity might want a very low abnormality tolerance, whereas organizations that are less at risk might want to set it much higher so that minor anomalies won’t disrupt payment activity. Additionally, workflows can be embedded to swiftly resolve anomalies. Real-Time Screening, Alerts and Notifications The rise of same-day and real-time payment systems has increased the need for real-time responses to fraud attempts. Modern fraud detection software uses AI/ML to screen payments against historical payment data, pinpointing any anomalies. By providing more complete data, these solutions enable data-driven decision-making. Solutions can flag any abnormal payments, providing insights into the variables that determine payment normality. Generative Adversarial Networks The lack of data around fraud can be a problem for AI models. Training AI models can thus be challenging because the algorithms often can only learn from good payments and, at best, a handful of bad ones. Generative adversarial networks (GANs) can solve this problem. GANs are deep learning models that pit two separate neural networks against each other. One network mixes real data and synthetic data together and attempts to outwit the opposing network. By training fraud detection models on these competing networks, fraudulent transactions can be more easily identified in real data. Cash Forecasting Manual processes persist in treasury, even with the advent and evolution of technologies like AI. Many treasury departments continue to rely on Excel, even though it can produce highly inaccurate cash flow forecasts that can negatively impact the business. Organizations can increase the accuracy of their short-term cash forecasting with AI-based tools that learn from the history of cash flows and continuously improve inflow projections over time. With deeper analysis of this data, organizations can better predict cash flows by season or region, which in turn reduces efforts for key functions like accounts payable by, anticipating free cash flow closing, and adjusting the payment campaign budget. AI/ML users also can select what companies, currencies and cash flow types to include, as well as adjust the forecasting period to align on short-term payment/funding/investment decisions. With interest rates increasing, treasury teams can optimize liquidity by reducing their maximum idle cash while also minimizing the risk and cost of overdraft. Treasury will be able to determine how much of its budget it can allocate towards certain expenditures over a period of time, or whether it will need to borrow funds to make certain payments. AI tools can factor in multiple variables and errors found in historical data to better estimate cash inflows and outflows over the next seven days. This allows treasury to determine how much of its budget it can allocate towards certain expenditures over that time period, or whether it will need to borrow funds to make certain payments. Soon, as these tools accumulate more data, they will be able to make predictions on mid- and long-term horizons. Check out Kyriba's latest AI-powered cash forecasting module: Cash Management AI to see how AI in treasury management can already be used fluently for short-term cash forecasting. ChatGPT and Generative AI in Treasury Management ChatGPT has become a popular generative AI app, in part because of a $10 billion partnership with Microsoft. ChatGPT is well known for its natural language processing chatbot abilities that answer any question. Yet the real opportunity for ChatGPT and generative AI is to change the way we interact with online software applications, including online search and business applications like ERP and treasury management systems (TMS). ChatGPT can also be used within a TMS where the user gives instructions to the system using keywords or questions. With a user experience (UX) that has been optimized for natural language processing, the TMS can respond to basic queries such as “What is my exposure to the Yen?” or more complex requests, including “What caused the variance in my forecast last week?”. Treasury may also find this technology to be useful in documenting treasury processes and procedures. Documentation and how-to manuals take time and effort to compile. Fortunately, ChatGPT and similar generative AI models can do all the writing for you after being fed a minimum amount of information. Take Action The demands of today, and tomorrow, dictate that CFOs and treasurers must act. While pervasive economic hardships and rising global inflation may make it difficult for companies to justify spending on new technology, they are facing massive challenges if they don’t adjust to the pace of the modern business world. Rest assured; if your peers aren’t investing in this technology yet, they will be soon. Many companies have also stockpiled their cash reserves throughout the pandemic — now is the time to begin spending some of that cash on tech enablers, one good area to look into being AI in treasury management. Treasury teams would be wise to look for a trusted partner as they explore possible use cases of AI in treasury management. There are technology providers with teams of data experts and portfolios of treasury apps available. Many tools are already in production and require minimal effort on the part of the company. As we emerge from the pandemic—a time when companies were focused primarily on survival—the focus now needs to be on growth. As more data becomes available, growth will come from those organizations that are able to harness that data and turn it into useful applications. Others will drown in it and fall behind. With AI in treasury management to assist the human, treasury teams can ensure that they are positioning their organizations for success. Related Resources Javapoint: Difference Between Artificial Intelligence and Machine Learning TechTarget: Data Lake AFP: Identifying Value for Treasury: Automation, Machine Learning & Artificial Intelligence PYMNTS Intelligence: How Payments Automation and Digitization Can Reduce Errors and Streamline Transactions Gartner: Success With AP Invoice Automation Requires More Than Paper to Digital ERP News: Automation for Business Intelligence Kyriba: 15-Minute Guide to Payment Hubs Want to see how AI in treasury management improves cash forecasting? Join Kyriba's upcoming monthly live demo sessions. An on-demand demo session is available here.

Cash is still king — but the value of cash and forecasted liquidity held or planned by the company can only be realized via cash visibility, when the treasurer knows what cash is available,...

Cash is still king — but the value of cash and forecasted liquidity held or planned by the company can only be realized via cash visibility, when the treasurer knows what cash is available, where it is held and what flows are expected in the future. However, all too often, treasurers do not have access to their organization’s full cash picture. There are many good reasons for working with multiple banks across different markets, but complex banking structures and sprawling geographical footprints can make it difficult to achieve complete cash visibility into current balances, never mind impacting the accuracy of cash and liquidity forecasting. Luckily, achieving full cash visibility over cash is not an insurmountable goal. This eBook outlines the action plan treasurers can take to gain full visibility over their cash, from gaining a clear view of current bank accounts to increasing the accuracy of the cash forecast. "More than a quarter of global cash is not visible to corporate treasury on a daily basis.” Source: PWC’s Global Treasury Benchmarking Survey   What is Cash Visibility? Cash visibility is critical to making effective decisions. Armed with clear visibility over the company’s current cash position and future liquidity flows, treasurers can: Invest cash strategically Support the CEO, CFO in strategic initiatives with the right levels of cash and liquidity Use cash management structures effectively Minimize debt and interest expense Make better informed hedging decisions Reduce bank fees Bolster treasury’s reputation within the organization Key Vocabulary Cash Visibility means knowing what cash the company currently has and where it is held. It also means being able to predict what cash the company will have in the future. Cash Budgeting generally performed by FP&A, is more focused beyond one year and has an increased emphasis on free, cash-flow guidance. The reconciliation of indirect budget-based forecasts with direct cash flow forecasts are increasingly managed quarterly. Cash Positioning is concerned with today and often the next five business days. The purpose is to manage daily liquidity to ensure shortfalls are covered and surpluses are concentrated to earn some yield on excess cash. Cash and Liquidity Forecasting typically extends cash positioning with horizons anywhere from one week to one year. Forecasting leverages multiple data sources to increase confidence in the projected liquidity balances so that better cash decisions can be made. Why is Cash Visibility Important? Cash visibility is the lifeblood of any organization. A company that has clear visibility can invest or deploy cash strategically while minimizing debt and interest expenses. Accurate visibility also increases the effectiveness of hedging decisions and enables the treasurer to mitigate their organization’s risk to exposures while supplying the CFO with funding in support of strategic initiatives. Conversely, a lack of clear visibility can result in numerous issues, including: Insufficient buffer of surplus cash to absorb unforeseen expenses Idle cash, lower returns on investments Insufficient return on cash Higher than necessary borrowing costs Unnecessary bank fees and costs Inadequate support for CFO strategic decision-making Less competitive results and less effective treasury organization as a partner for finance Related Resource Unreliable cash visibility and forecasting is the treasury issue that causes CFOs the most concern. "The top benefits of using Kyriba are the visibility that it provides, the timeliness with which it provides that visibility, and the ease of use, in that it provides it all in one simple one-stop shop.” TRISH FISHER Director, Treasury Operations, WeWork The Path to Cash Visibility Whether the treasurer is seeking to pay down external borrowing or maximize return on investments, the first step is to know what cash is currently available. But that’s not all, treasurers also need to be able to predict future liquidity flows and keep the right people informed. Achieving cash visibility is possible by using 5 definitive steps to move towards greater cash visibility and flexibility: Identify and Record Without an inventory of your banks and accounts, a complete cash visibility picture is unattainable. Prioritize and Rationalize Identify where to begin, difficult regions or banks, and determine accounts for closure. Automate Bank Connectivity and Reporting Harness the most costeffective and leading connectivity methods to access data from banks in an automated way. Generate and Streamline Cash Positioning with Liquidity Forecasting Accurately predict cash flows over the coming hours and days, and match actuals to forecasts to speed up daily reconciliation and cash application. Enhance and Optimize Future Cash Flow with Liquidity Planning The ability to see a holistic, aggregated view of cash and liquidity sources creates more accurate views and predictable free cash flow. Knowing your predictable liquidity creates a better understanding of any future liquidity shortfalls. Step One: Identify and Record Regardless of the scale and breadth of your organization’s banking and accounts structure, it is important to understand the banking landscape of all business units and subsidiaries. Whether operating in a domestic or international capacity, banking relationships. the accounts, the purpose of those accounts, and the core attributes of the bank, the accounts and their purpose all are necessary to begin a cash visibility project. This has many implications for the success of global cash visibility projects, such as: Establishing a full inventory of managed accounts, ensuring all balances are identified Ensuring the proper scope and prioritization of your project Optimization and rationalization across banks and accounts Effective comparisons and evaluations across banks for technical capabilities for connectivity, tech, regional coverage and other important services An effective bank relationship and bank account management database is the starting point for successful projects, but particularly when it comes to cash reporting. Where cash is rolling up in concentration or pooling structures, how funds are being transferred, purpose of the accounts, and even regulatory limitations all have a say in how you engage with your banking partners and the extent of cash flexibility. Step Two: Prioritize and Rationalize Bank reporting rationalization ensures accounts are identified and open for the right reasons. Often, particularly in international or more complex organizations, accounts are opened in haste to support business development and decisions. This is often necessary for statutory purposes, or to deal with an unforeseen acquisition or reorganization. However, if this situation exists, it’s possible cash and liquidity is not well defined or identified, as well. Organizations must understand and rationalize accounts, prior to moving into the next ‘step’, but this can continue throughout the project in parallel, too. The focus here is on creating a streamlined, but effective banking and account structure that fulfills treasury’s mission of safeguarding and optimizing cash, while still meeting specific business unit or subsidiary’s requirements. Bank improvements in reporting quality as well as the leading application of configuration within leading treasury management systems, creates the scenarios where previously opened, special-purpose accounts are no longer required to serve special purposes such as revenue, collections, treasury, or payables accounts. With banks being able to provide significantly improved quality of liquidity information within bank statements and other special purpose reports, and the speed of that data increasing through APIs, some companies can conduct business with one or two bank accounts per legal entity, business unit or country office. The focus here is on creating a streamlined, but effective banking and account structure that fulfills treasury’s mission of safeguarding and optimizing cash, while still meeting specific business unit or subsidiary’s requirements. Step Three: Automate Bank Connectivity and Reporting Visibility over multiple accounts requires automated bank connectivity. Companies of all sizes are often challenged in finding and implementing the right bank connectivity solution and is a critical driver of lack of visibility into cash. On the surface, bank connectivity is easy, so long as treasury teams prioritize the following: Security Automation Speed and Cost There are a variety of connectivity options to deliver security, automation and cost objectives. Yet, not all connectivity options are alike. Bank connectivity comes in a number of different forms, including: Host-to-host solutions, such as FTP, or leading practice connections using application programming interfaces (APIs) Country or region-specific protocols such as EBICS, Editran, Zengin Global cooperatives like SWIFT , which offer flexibility to manage your own connectivity or use a service provider and fully managed service bureaus The ideal connectivity solution for an organization will actually depend on factors such as bank and payment transaction volumes, bank account structures, and the location of company banks. These characteristics — in combination with what technologies the banks can (and prefer) to support — will drive the ideal connectivity choices. In practice, a combination of connectivity methods is likely the best solution to optimize costs while maintaining automation and security. Without utilizing varying connectivity methods, the company may spend more than necessary and potentially sacrifice information transparency. While managing multiple connectivity methods on your own may seem complex, connectivity-as-aservice models gives organizations faster global access to banks with pre-configured and existing connections. This coverage of the connective landscape for banks saves effort and time spelling big cost savings for the project phase as well as ongoing productive operations. When you select the right vendor to simplify bank connectivity by taking care of everything — from building connections, monitoring availability, and delivering automation all while providing new technology like APIs, organizations win and save money. Step Four: Generate and Streamline Cash Positions and Liquidity Forecasts The goal of cash positioning is to establish a realtime view of cash at any point in time and to be able to reconcile prior-day forecasts to enable the deployment of cash throughout the organization more quickly and accurately. Effective cash positioning reduces idle cash, creating opportunities to earn immediate yield while providing certainty over risk exposures that cash is exposed to. As a process, cash positioning involves gaining a real-time view of the company’s cash position at any moment in the current day(s) by consolidating a number of different sources and replacing old data with more up-to-date information. With today’s APIs gaining the real-time, near-instantaneous view of cash and liquidity is easier than ever. Within treasury technology, building the cash position typically involves combining a number of data sources: Prior-day balance — automatically downloaded from banks at the start of the day Current-day bank reporting — automatically downloaded from banks throughout the day, either at specific times (e.g., 1st or 2nd presentment) or as a constant stream of data via an API Expected payables and receivables — from the organization’s ERP and reported/cleared from bank statement details Treasury financial transactions and settlements — which are integrated within the treasury system Building a cash position is just the start. After building a cash position, it is then necessary to maintain and reconcile it. Maintaining the cash position involves updating and replacing cash flow data with more accurate information via intra-day updates from internal systems and banks. Reconciliation of the cash position is the matching of actuals to forecast flows, which is often done first thing in the morning as a part of typical treasury processes. The goal is to identify and understand surprises — for example, if a transaction did not happen yesterday then it may happen today, meaning the unreconciled variance needs to be rolled into today’s position. For many organizations, this process can be time consuming, so rules-based automation or artificial intelligence can be introduced to simplify the process. Key requirements for cash positioning include interactive dashboards and clear communication within — and outside of the treasury organizations: Interactive dashboards enable cash managers to drill down through multiple levels into any component of the cash position. Positions should be viewable by multiple dimensions in real-time by line item, bank, entity, currency, etc. Communication within and outside of treasury is critical. The treasurer, CFO and finance personnel managing subsidiaries all require cash visibility, so delivering visual and detailed reconciled cash positions is a critical outcome of daily cash positioning. Effective cash positioning and liquidity planning leads to numerous benefits for the finance organization: Keeping the CFO and the Board up to date with reliable and accurate cash position information Mobilizing cash across the organization for funding and investment purposes Enabling cash management processes such as pooling, sweeping and intercompany borrowing Optimizing interest income and expense via better informed borrowing and lending operations Reducing external borrowing by using internal cash resources effectively Step Five: Enhance, Optimize and Predict Cash and Liquidity While cash positioning can be used to predict cash flows in the coming hours and days, cash forecasting with liquidity planning information creates more accurate, longer horizons beyond weeks, extending into months, years. Cash forecasting must not only be accurate, but predictive using more historical and current data to be truly effective. Without complete confidence in projected forecasts, the cash forecast cannot support treasury in improving cash utilization. Cash forecasting is needed to help treasury invest cash over longer maturities, secure borrowing to fund operations and make more effective hedging decisions. And confidence in the cash forecast is the difference between achieving these outcomes and hoping to do so. So why do so many companies struggle to achieve an accurate forecast? Common challenges include a lack of accurate data sources, lost results from past forecasts, ineffective methodologies and a lack of alignment with performance metrics. If a forecast isn’t reliable, treasury is unable to trust it and therefore cannot use the cash forecast to make critical decisions. It is crucial to incorporate data sources from treasury, like financial transactions along with all the normal P2P and O2C cycle flows from the ERP Cash forecasting and Liquidity Planning creates future views of anticipated free cash flow and helps all of finance from FP&A to the CFO better strategic accuracy in decision-making. Identify, Find the Data Consolidate the Information Measuring Forecast Accuracy Predictive Analytics: Optimize Your Forecast Find the Data: Collaborating with Other Teams Forecasting incorporates key data points from elsewhere in the business so that effective collaboration can be administered between AP, FP&A, IT and regional controllers who own valuable forecasts data and/or administer systems to enhance forecast visibility. This collaboration is essential in making sure everyone involved knows what they are expected to provide with executive oversight to ensure that collaboration is prioritized. Consolidating Forecast Data Automating the integration of forecast data into a single system of record is the next critical factor in achieving effective forecasting. In many cases, source data may come from various ERP modules or in some cases other special purpose systems like procurement or revenue recognition/accounts receivable. In the past and in some situations, spreadsheet data to augment or provide coverage for areas or business units without systems could be a source, too. While consolidating data into a single system could be an IT-intensive exercise, best practice is to eliminate the need for internal IT resources, reducing the cost and time required to integrate systems. This can be done by having pre-built connectivity and integration through APIs provided by your treasury system. Measuring Forecast Accuracy The final piece of cash forecasting is to measure the accuracy of the cash forecast at a detailed level. Measuring forecast performance is critical to understanding how effective each line item and source of information was, offering valuable insight into where the forecast can be improved. This analysis must be done at a detailed level. For example, measuring accuracy before and after a 90-day/13- week period can hide many anomalies and offers no meaningful conclusions. Many organizations will measure week over week, while some will drill down at a daily level. Once accuracy is measured, the treasury team must implement a feedback loop to effect meaningful change. Regional controllers, for example, can only improve if presented with detailed facts. Further, standardized KPIs — that ideally would form a component of performance reviews and compensation calculations — go a long way in reinforcing desired forecast behavior. This is where commitment from the CFO will drive effective forecast performance. Optimize: Predictions for your Cash and Liquidity Once the foundation is established for forecasting your liquidity with the prior steps, the next level naturally leads to identifying the technology solution that will offer your organization and team the support and improvements for your liquidity forecasting. Technology can do more to provide value through expanding the horizon of your forecast, depth of insight, accuracy, and enhanced user experience with information already within your organization’s grasp. Through tools that leverage artificial intelligence companies today should be more advanced and be capable of: Create predictive dashboards and enhanced reporting Cash forecasts with risk models built-in Identify optimum cash cushion, draw-down levels, and investment levels Characteristics to look for when evolving and upleveling your forecasting efforts should include looking to solutions using AI-based predictive analytics for forecasting including calculations based on risk models that give treasury and FP&A teams the optimal cash cushion. Additionally, look for solutions giving you: Cash flow by level of confidence Recommendations for optimal investment strategy Predict liquidity requirements To successfully deploy an AI-driven predictive forecasting model, organizations must prepare structured and normalized historical data. Machine learning algorithms will identify patterns within the data to make predictions about when, for example, customers will actually remit payment. This AI-predicted data stream will align with other forecast data sources to deliver a more intelligent cash forecast to predict future liquidity needs. Human interaction remains important to ensure liquidity forecasting and planning aligns with internal risk policies of the team and organization. AI is a tool to complement, rather than replace, treasury teams as they execute more complex tasks and processes. In this role, AI is a critical piece in the drive to towards real-time treasury decision making and the progressions towards 24/7 liquidity management. Optimizing Cash Visibility Benefits Achieving full cash visibility takes time and effort, but the rewards are significant. Armed with a complete, accurate and up-to-date picture of the current cash position and liquidity planning flows, treasurers can: Make timely and confident decisions about activities, including investments, borrowing, cash concentration and hedging Pay down external borrowing with a clearer view of the cash available Invest strategically with a clear picture of current and future flows Reduce bank fees by closing or combining redundant bank accounts or negotiating with banks from a position of knowledge Minimize debt and interest expense by making the best use of internal cash and reducing external borrowing Gain a clearer picture of risk exposures and manage those risks more effectively Optimize planning of borrowing and lending operations Increase effectiveness of hedging by ensuring decisions are based on complete pictures of current balances and planned future transactions Cash Visibility – Final Thoughts The future of treasury technology is here and advancing rapidly; some banks have deployed their own APIs to integrate with their customers’ systems. New platforms are opening new products and services for corporate customers. One of these innovations is the movement towards real-time bank reporting. In many parts of the world, intra-day reporting happens less than twice per day, and in some cases not at all, meaning that daily cash positioning is largely driven by prior-day reporting and expectations of clearings throughout the day. Real-time bank reporting, delivered only by APIs, is the future and will be a game-changer for cash managers looking to achieve instant cash visibility into accounts. Additionally, Liquidity Planning extends the value of real-time treasury with the inclusion of cash, treasury instruments, planning information and liability information to deliver longer range strategic decisions by the CFO. Combined with real-time payments, treasury teams will be in an enviable position of not only having real-time views into bank accounts but also being able to mobilize cash domestically — and eventually cross border — within seconds. The transformation to real-time reporting will further pressure treasury teams to employ the right processes and analysis to effectively manage cash information in real time. It will be a change for those organizations that lack modern treasury technology, but an opportunity for enabled organizations to earn a competitive advantage in the utilization and deployment of cash. How Kyriba Can Help Kyriba can support you in achieving full visibility over cash. Kyriba helps organizations reduce the cost and complexity of bank connectivity — whether a company is connecting via SWIFT, using APIs, leveraging country protocol or using a combination of channels prioritizing security, automation and cost minimization. Organizations can easily keep track of signatories, manage workflows and store documents thanks to the control over all global bank accounts given by Kyriba’s bank relationship management solution. Additionally, companies can maximize the accuracy of their cash and liquidity reporting with Kyriba’s detailed and flexible variance analysis and feedback loop to forecast sources. With a full picture of current balances and future flows, you’ll be better positioned to make confident decisions about cash.   Want to learn more about how to achieve cash visibility for better cash forecasting? Check out this webinar to hear Kelkoo Group, a leading e-commerce company, shares their best practices and the payoffs of superior cash forecasting.

APIs offer a lifeline for CFOs and treasurers who are looking for both innovation and cost improvements. Although many CFOs think of APIs for finance as an expedited pathway for bank connectivity, bank connections...

APIs offer a lifeline for CFOs and treasurers who are looking for both innovation and cost improvements. Although many CFOs think of APIs for finance as an expedited pathway for bank connectivity, bank connections are just the tip of the iceberg. APIs open integration to a variety of systems, including capabilities that vastly improve cash forecasting, liquidity management and payments. APIs offer an information and processing gateway to realizing digital transformation. Unlike FTP, APIs do not require files to be sent or downloaded. Data is exchanged point to point between systems immediately, allowing for instant data transmission and eliminating substantial risk. They enable the development and use of faster, pre-built connectors to reduce implementation times and facilitate real-time payments and security. In this whitepaper, we'll explore: What APIs are and how they work for finance The different types of APIs that are available How APIs can revolutionize ERP connectivity, cash management, liquidity management, payments and more. CFOs Are Investing Billions CFOs are investing more than ever on enterprise platforms, with organizations spending an estimated $675 billion in 2022, according to Statista. Much of this investment is for organizations to move their enterprise resource planning (ERP) systems to cloud platforms, such as SAP S/4 Hana Oracle Cloud, and Microsoft Dynamics 365 leading the large corporate market. For CIOs looking to effectively support their CFO business partners, connectivity from ERP to internal and external systems and data sets remains a costly challenge, often delaying go-live dates and driving significant cost overruns. APIs open integration to a variety of systems, introducing capabilities and process automation that had not previously been possible. APIs offer an information and processing gateway to realizing digital transformation. What Is an API? An API is a program that allows mulitple pieces of software to “talk” to each other. Applications on your phone and embedded widgets on a website all use APIs to request or deliver information. Why APIs for Finance Matter Gartner research revealed that nearly 50 percent of financial leaders will incorporate a “composable financial management system” by 2024 “to deliver capabilities and outcomes that keep up with the rapid pace of business change.” APIs are enabling that change. They are transforming the way finance leaders consume data and are allowing a coupling of multiple applications that was previously impractical to support, creating a gateway to real-time business intelligence and digital solutions. Unlike file transfer protocol (FTP), APIs do not require files to be sent or downloaded. Data is exchanged point to point between the systems immediately, allowing for instant data transmission and eliminating substantial risk. They enable the development and use of faster, pre-built connectors to reduce implementation times and facilitate real-time payments and security. "With APIs for finance, your platforms evolve from being systems of record to systems of engagement,” said Bob Stark, Global Head of Market Strategy at Kyriba. “Your platform is connected with any number of internal and external systems to be continuously up to date.” Open API Platforms APIs facilitate open networks. Using developer portals, technology providers can build applications on top of the API provider’s platform. Open banking is a perfect example. The Revised Payments Services Directive (PSD2) in 2018 helped to make APIs even more relevant for corporate treasury and finance. The EU Directive requires banks to open their platforms to payment technology providers – with APIs being a leading solution to manage this compliance. Although PSD2 only applies to the European Union, similar initiatives in other regions also quickly emerged as banks in the United States and throughout APAC have recognized the opportunity to offer real-time, data-driven services to corporate clients. "The PSD2 movement has really encouraged banks to start to open APIs for corporates.” —Felix Grevy, VP of Product, Open API and Connectivity for Kyriba A common frustration among treasury and finance leaders is a lack of centralized visibility across multiple departments, liquidity and payments. Open API platforms act as a conduit between disparate teams and systems, allowing for real-time connections to apps, data, and new products and services. Open API platforms reduce manual processes, and deliver composable technology solutions, enabling corporate and bank users to inject data-driven decision-making into every financial operation. APIs for Bank Connectivity It’s important to note that banks and technology solutions providers that are managing open platforms are not replacing legacy formats like FTP and SWIFT with APIs. Instead, they are offering APIs as a complement to these formats. Following the advent of PSD2, European banks have begun using “premium” APIs, which are APIs with greater functionality. "The difference between the PSD2 APIs and premium APIs is that premium APIs are more powerful,” Grevy said. “You can retrieve balances and do instant payments. And they are much more secure, and much more appropriate for integration with an ERP or treasury management system (TMS).” Banking services optimized via API vary, some examples include: Bank Groups Branch Reporting Bank Account Groups Cash and Cash Flow Reporting However, the rollout has been slow. Most banks are not using APIs in live production yet, and many of the ones that do use APIs only offer them for certain real-time services—meaning that multiple connectivity options are needed to fully support a treasury and finance team. Furthermore, most technology vendors only offer no functionality beyond bank connectivity and can only connect one ERP to a bank. Nevertheless, API connectivity brings key advantages over a file-based approach, such as immediate response from banks, and the ability to receive new data and notifications in real-time. So while adoption may be slow and gradual, the advantages to the end user are clear. ERP Connectors ERP platforms like SAP, Oracle and MS Dynamics have major efforts to develop and embed APIs into a wide array of functions and workflows. Luckily, for IT and Finance functions arent’ required to do the heavy lift; these APIs are plug-and-play and enabling more and more core integrations and reporting capabilities. Cash Management APIs offer organizations the ability to manage cash continuously and in real-time. Rather than relying on batch reporting that is constrained to pre-determined times throughout the day, treasury teams can now access reports as needed. Receiving un-batched, real-time liquidity information greatly improves cash reconciliations, cash application, and accuracy of liquidity overall. This will, in turn, change the mechanics for best-practice cash forecasting and lead to the production of intraday liquidity products, such as hourly investing. Allowing treasury professionals to access their cash outside of previously “normal” hours not only expands the scope in which organizations can leverage their liquidity, but also allows treasury to make greater strategic contributions. APIs also allow treasury and finance to track sufficient movements in and out of the accounts throughout the day. That visibility can help organizations to make significant intraday decisions instead of end of day or overnight. Payments APIs for finance can also streamline the entire payment journey. Instead of relying on batch processes that transmit at several pre-determined times each day, APIs allow payments to be initiated from treasury management systems and ERP systems as needed—even in real time. In fact, real-time payments sometimes require APIs. Simply put, if you want payments to settle instantly, file transfers may not be the best connectivity option to choose. Using File Transfer, bank files are extracted, reformatted, encrypted, and downloaded by the treasury platform—a process that takes five to ten minutes at least. Once balances are known, the process to send and confirm a payment is another five to ten minutes at minimum. APIs, in contrast, can query a bank balance and then send a real-time payment instantly without the transfer of any files. With the rapid increase of both domestic real-time payment systems (The Clearing House’s RTP and FedNow in the U.S.) and cross-border platforms (SEPA Instant, SWIFT Go, and Nexus) APIs are a necessity for businesses who want to deliver instant payments. Leveraging APIs to utilize real-time payments not only revolutionizes the initiation and acknowledgement process, but also the ability to mitigate fraud. While the 2022 AFP Payments Fraud & Control Survey found that business email compromise scams have decreased recently, they are nevertheless still a persistent threat. Since real-time payments don’t afford users the opportunity to identify fraudulent transactions after transmission, fraud mitigation strategies must now be included in the approval process. Building APIs into the payment platform allows users to fully automate bank account validation and payment policy screening, identifying exceptions. Outliers can be flagged and set aside for review, while all other payments travel seamlessly as intended. Creating Flexible Reporting and Information Systems APIs are far more than just connectors to banks and ERPs. APIs can revolutionize the ways in which treasury and finance operate both internally and holistically. APIs offer the ability to create a flexible, custom, data warehouse that could exist within your TMS, as some treasury systems can act as a single source of record. When other systems have limited functionality, your data warehouse can fill the gaps through provision of market data, financial transaction specifics such as portfolio, project or risk-related information to deliver a quick, flexible source of weekly treasury reporting. Regardless of where your data is stored, APIs establish the means to integrate various data sources within a single repository or warehouse. Second, APIs allow treasury and finance to automate beyond task automation, which streamlines the organization’s own capabilities. APIs enable process automation, which simplifies and entire workflow like the entire payment journey. Entire systems and processes can be brought together more easily via APIs. Both automation and the extent of the functional coverage facilitate composable financial management systems. When networks of personalized systems, reports, dashboards, and efficient workstreams are enabled and integrated by APIs, treasury and finance teams can then focus on accelerating innovation and cost-reduction projects. ERPs, while critical, are not the only system requiring strong integration and the exchange of information for stronger decision-making. APIs are the glue that holds all of these components together and APIs change the efficiency and real-time capabilities for treasury and finance leaders. "CFOs and CIOs, hand in hand, are recognizing that we need APIs to bring everything together to accelerate the innovation,” Stark said. “Before APIs, the way that you’re making a composable financial system is by using custom interfaces, manual clicking and logging into systems and, if you’re lucky, a little bit of RPA. APIs are perfectly suited to improve process automation, linking multiple systems and workflows together, because they allow finance teams to build a system of multiple components.” Figure 1. Progression of Hyberautomation Initiatives Source: Gartner 2021 References Information technology (IT) spending on enterprise software worldwide, from 2009 to 2023 2022 AFP Payments Fraud and Control Survey Gartner Identifies the Top Technology Trends That CFOs Should Address Today   Interested to learn more about how APIs for finance will change the way leaders consume and act on information? Check out this webinar where Alex Yang from Bank of America, David Miller from Hunt Companies and Bob Stark from Kyriba demystify APIs' value for payments, intra-day liquidity, ERP integration, fraud detection, cryptocurrencies and more.

Le moderne minacce di frode sono innovative e in continua evoluzione. Per affrontare queste minacce, le organizzazioni che vogliono sopravvivere devono implementare le soluzioni di rilevamento e prevenzione più aggiornate.

Le moderne minacce di frode sono innovative e in continua evoluzione. Per far fronte a queste minacce, le organizzazioni che vogliono sopravvivere devono implementare le più aggiornate soluzioni di rilevamento e prevenzione delle frodi nei pagamenti. In questo eBook esploreremo le minacce di frode più comuni per le aziende di oggi e descriveremo nel dettaglio gli strumenti leader basati sull'intelligenza artificiale che i CFO e i CIO possono utilizzare per bloccare gli attacchi prima che si verifichino. Esploreremo i modi in cui le soluzioni Kyriba proteggono i nostri clienti e vi trasmetteremo queste conoscenze. Analizzeremo anche strumenti come l'intelligenza artificiale e l'apprendimento automatico (AI/ML) e le interfacce di programmazione delle applicazioni (API) che cambiano le carte in tavola nella lotta contro le frodi. Noi comprendiamo e utilizziamo queste tecnologie ed è ora che lo facciate anche voi. Il volto mutevole della frode Le minacce di frode sono cresciute in modo esponenziale durante la pandemia COVID-19, poiché l'ambiente di lavoro remoto ha lasciato le aziende in difficoltà nel garantire che i dipendenti seguissero rigorosi protocolli di sicurezza. Secondo un'indagine KPMG del 2022 condotta su oltre 600 dirigenti, il passaggio al lavoro a distanza ha aumentato il rischio di frode e l'anno scorso la maggior parte delle aziende ha subito incidenti di frode. FRAUD OUTLOOK Fonte: 2022 KPMG Fraud Outlook Le perdite derivanti dalle frodi sono significative. Gli intervistati hanno riferito una perdita media di profitto dell'1% dovuta a frodi e violazioni della conformità nel 2021. E più l'azienda è grande, più i criminali la prenderanno di mira. Necessità di investimenti e attenzione da parte delle aziende Con la pandemia che continuerà nel prossimo futuro e che metterà a dura prova la capacità delle organizzazioni di operare e di impiegare il personale in modo efficace per contrastare la crescente minaccia di frode, è sorprendente che oltre la metà delle aziende intervistate dichiari che non ci saranno cambiamenti nei loro budget per investire in misure antifrode. Con meno della metà delle organizzazioni che oggi hanno un programma in atto per prevenire, rilevare e rispondere alle frodi, è evidente che è necessario concentrarsi su maggiori investimenti nelle loro protezioni. I CFO, i tesorieri e i CIO hanno chiaramente bisogno di una serie di difese più complete sotto forma di un nuovo sistema di rilevamento delle frodi automatizzato basato sull'intelligenza artificiale. Minacce di frode pervasive ed emergenti Le truffe via e-mail continuano ad affliggere i dipartimenti di tesoreria e finanza. Le truffe BEC iniziano tipicamente con un'e-mail urgente inviata a un dipendente che sembra provenire da un funzionario di alto livello, con la richiesta di un trasferimento di denaro. In realtà, un truffatore ha copiato un indirizzo e-mail legittimo, di solito dopo essersi infiltrato nel sistema di posta elettronica di un'azienda tramite phishing. Una variante di questa truffa consiste nell'invio di fatture via e-mail che sembrano provenire da un fornitore abituale e che contengono nuove istruzioni su dove inviare il pagamento. Secondo la Cyber Division dell'FBI, dal 2019 al 2020 si è registrato un aumento del 5% delle perdite di BEC, con oltre 1,7 miliardi di dollari di perdite registrate nel 2019 e oltre 1,8 miliardi di dollari nel 2020. Frode con assegni e bonifici rimane un problema significativo per i dipartimenti di tesoreria e finanza, in quanto questi sono i metodi di pagamento più suscettibili di frode. La ricerca AFP ha rilevato che il 66% e il 39% dei professionisti della finanza hanno segnalato attività di frode attraverso questi due tipi di pagamento nel 2020. Tuttavia, negli ultimi anni le frodi legate agli assegni sono diminuite, poiché un numero minore di organizzazioni utilizza gli assegni per i pagamenti B2B. Frode vocale deepfake è un metodo di attacco relativamente nuovo, ma che si è dimostrato molto efficace. Questo tipo di frode consiste nell'effettuare chiamate utilizzando la tecnologia deepfake voice, un software in grado di copiare con successo la voce di una persona attraverso un piccolo campione audio. VULNERABILITÀ COMUNI PER LE ORGANIZZAZIONI La frode vocale Deepfake ha attirato l'attenzione internazionale l'anno scorso, quando è stato rivelato che i truffatori l'hanno utilizzata per portare a termine una rapina in banca da 35 milioni di dollari. Attacchi ransomware, anche se non sono tecnicamente frodi, sono comunque minacce importanti per i sistemi e i conti bancari delle aziende e sono aumentate negli ultimi anni. In un attacco ransomware, il sistema interno di un'azienda viene compromesso (di solito tramite phishing) e preso in consegna. Agli utenti viene chiesto di pagare un riscatto o di perdere definitivamente l'accesso ai propri sistemi. Il ransomware come servizio (RaaS) è l'ultima innovazione di questa minaccia; consiste nella vendita o nell'affitto di exploit ransomware da parte degli sviluppatori ai clienti, che poi li scatenano contro le sfortunate vittime. Strumenti di protezione contro le frodi Per combattere le minacce di oggi, le vostre soluzioni di prevenzione e rilevamento delle frodi nei pagamenti dovrebbero includere queste funzionalità: Processi di pagamento automatizzati per standardizzare i controlli Screening in tempo reale di tutti i dati relativi ai pagamenti per identificare le transazioni sospette Regole di screening dei pagamenti definite dall'utente Flusso di lavoro di risoluzione per indagare sui pagamenti sospetti Un'opzione per evitare di avvisare gli utenti che hanno violato una regola sui pagamenti Monitoraggio dello stato e della priorità degli avvisi in un cruscotto KPI I moderni software di rilevamento delle frodi nei pagamenti, come il modulo Payments Fraud Detection di Kyriba, offrono queste e altre soluzioni. Screening, avvisi e notifiche in tempo reale L'aumento dei sistemi di pagamento in giornata e in tempo reale ha aumentato la necessità di risposte in tempo reale ai tentativi di frode. I moderni software di rilevamento delle frodi utilizzano l'intelligenza artificiale (AI) e l'apprendimento automatico per analizzare i pagamenti rispetto ai dati storici, individuando eventuali anomalie. Fornendo dati più completi, queste soluzioni consentono di prendere decisioni basate sui dati. Ad esempio, la soluzione Payment Fraud Detection di Kyriba determina la normalità di ogni pagamento, sia esso automatico o manuale, segnalando quelli con un basso grado di normalità. La soluzione fornisce informazioni sulle variabili che determinano la normalità dei pagamenti, consentendo agli utenti di capire perché uno o più pagamenti sono stati considerati anomali. L'aspetto forse più vantaggioso per l'utente è che i processi non vengono in alcun modo rallentati, anche con una maggiore visibilità sui dati dei pagamenti. I pagamenti possono essere segnalati come anomali per una serie di motivi, tra cui: Un numero elevato di pagamenti per la stessa terza parte Pagamenti con importi insolitamente elevati Pagamenti a paesi inseriti nella lista nera secondo la politica aziendale Modifiche sospette ai pagamenti importati da un ERP Pagamenti su un conto bancario utilizzato da più parti terze Pagamenti duplicati Dopo aver testato diversi modelli di apprendimento automatico, i data scientist di Kyriba hanno selezionato due soluzioni per identificare le irregolarità nei pagamenti. Isolation Forest Un modello di Isolation Forest è un algoritmo non supervisionato che funziona secondo il principio dell'isolamento delle anomalie; le istanze anomale in un set di dati tendono a essere più facili da separare dal resto del campione. Nell'esempio seguente, si può notare che le anomalie richiedono meno partizioni casuali per essere isolate, rispetto ai punti normali: Rete avversaria generativa Un problema in cui molti modelli di apprendimento automatico si imbattono quando cercano di identificare le frodi è la mancanza di dati sulle frodi. La maggior parte delle organizzazioni non ha sperimentato frodi significative nei pagamenti e quindi non ha una quantità di esempi da condividere. Altri che sono stati vittime di frodi possono essere riluttanti o incapaci di condividere i dettagli. L'addestramento di modelli di intelligenza artificiale può quindi essere impegnativo, perché gli algoritmi possono imparare solo dai pagamenti buoni e, al massimo, da una manciata di quelli cattivi. Le reti generative avversarie (GAN) possono risolvere questo problema. Una GAN è un modello di apprendimento profondo che mette due reti neurali separate l'una contro l'altra. Una rete (il generatore) mescola dati reali e dati sintetici e cerca di superare la rete avversaria (il discriminatore). Kyriba crea una rete "truffaldina" (il generatore), che nasconde frodi sintetiche tra le transazioni legittime basate sulla cronologia dei pagamenti di un cliente. Poi, una rete di "polizia" (il discriminatore) passa al setaccio i dati, separando le transazioni illecite da quelle buone. Addestrando il modello di rilevamento delle frodi su queste reti concorrenti, Kyriba può identificare meglio le transazioni fraudolente quando visualizza i dati reali. Modello di rete avversaria generativa (GAN) Dashboard I dashboard possono essere impostati per visualizzare tutti i pagamenti sospetti e dare priorità alla loro risoluzione, in base a fattori quali le regole di rilevamento, l'esposizione al rischio, il conteggio degli incidenti e una scorecard di rilevamento delle frodi. I dashboard forniscono agli utenti autorizzati una trasparenza completa su tutti gli screening dei pagamenti e possono risolvere le azioni in sospeso in modo efficiente. Flussi di lavoro per la prevenzione delle frodi nei pagamenti I moderni moduli di rilevamento delle frodi nei pagamenti supportano anche flussi di lavoro end-to-end completamente automatizzati per la risoluzione dei pagamenti sospetti in sospeso. Gli utenti possono anche stabilire come deve essere gestito ogni pagamento rilevato, applicando la separazione dei compiti tra chi inizia, chi approva e chi rivede un pagamento rilevato. I revisori possono anche essere determinati in base alle regole di pagamento e a uno scenario specifico (ad esempio, il responsabile della tesoreria esamina i pagamenti inferiori a 1 milione di dollari, mentre i pagamenti superiori a 1 milione di dollari vengono assegnati al tesoriere) e il personale non addetto alla tesoreria può essere incaricato di esaminare determinati pagamenti rilevati. Reporting e tracce di controllo Le soluzioni tecnologiche più avanzate possono garantire che i pagamenti sospetti rilevati siano permanentemente tracciati nel sistema per la rendicontazione giornaliera, mensile o annuale. La cronologia viene mantenuta a tempo indeterminato e tutti i dettagli della transazione sospetta, compreso l'audit trail delle azioni individuate e risolte, vengono conservati per i rapporti di audit interni ed esterni. Hub di pagamento Con un hub di pagamento, le organizzazioni hanno tutte le loro capacità di protezione dalle frodi in un unico luogo. Gli hub di pagamento consolidano i flussi di pagamento provenienti da ERP, finanza, tesoreria, ufficio legale, mercati dei capitali e team decentralizzati, trasformando processi disaggregati in un'unica fonte di registrazione per tutti i pagamenti in uscita. Un hub di pagamento trasforma inoltre i dati di pagamento in formati di file specifici per le banche e si connette direttamente con le banche globali tramite diversi protocolli, tra cui host-to-host, SWIFT e reti regionali. I pagamenti provenienti da ERP o da altri sistemi possono far rientrare l'intero panorama dei pagamenti aziendali in un quadro di rilevamento delle frodi sui pagamenti coerente e incentrato sul rischio. Grazie alle connessioni e all'integrazione basata su API e collegata a un flusso di lavoro per l'approvazione e il rilevamento e la prevenzione delle frodi nei pagamenti, i controlli e le frodi sono migliorati e facilmente governati. Hub di pagamento per il rilevamento delle frodi nei pagamenti Matrice di mitigazione delle frodi I professionisti della tesoreria e della finanza hanno a disposizione molti strumenti per il rilevamento delle frodi nei pagamenti. Il seguente elenco di soluzioni fornisce una panoramica di alcune delle funzionalità che gli strumenti odierni offrono per mitigare il rischio di frode. Matrice di mitigazione delle frodi Soluzione Protezioni chiave Capabilities Scenari di rilevamento delle frodi nei pagamenti Regole di rilevamento predefinite Segnala i pagamenti non convenzionali per un'ulteriore verifica Facile da personalizzare e da inventare con le proprie regole Screening in tempo reale Dashboard AI Esamina i pagamenti rispetto ai dati storici dei pagamenti Visualizza tutti i pagamenti sospetti e dà priorità alla loro risoluzione Flusso di lavoro per la prevenzione delle frodi nei pagamenti Flusso di lavoro completamente automatizzato Consente agli utenti di risolvere i pagamenti sospetti in sospeso Consente agli utenti di stabilire come gestire i pagamenti rilevati Impone la separazione dei compiti in relazione a un pagamento rilevato Designa i revisori in base alla regola di pagamento e allo scenario specifico Fornisce la possibilità di assegnare la revisione dei pagamenti a personale non appartenente alla Tesoreria. Offre la possibilità di nascondere gli avvisi ai promotori/approdatori di un pagamento Consente di bloccare i pagamenti in base allo scenario finché non vengono risolti Consente di bypassare i pagamenti di basso valore Impostazione di approvazioni a livelli Reporting e tracce di controllo Reportistica KPI completa I pagamenti rilevati sono tracciati in modo permanente nel sistema Lo storico viene mantenuto a tempo indeterminato API: Il futuro del rilevamento delle frodi nei pagamenti I pagamenti in tempo reale, che si stanno gradualmente diffondendo, offrono una visibilità e una trasparenza senza precedenti sia all'ordinante che al beneficiario. Tuttavia, una volta eseguita una transazione in tempo reale, non è possibile fermare il trasferimento di fondi. Pertanto, è necessario prevenire le frodi nel processo di approvazione prima che una richiesta di pagamento raggiunga la banca. La creazione di API nella piattaforma di pagamento consente agli utenti di automatizzare completamente la convalida del conto bancario e lo screening dei criteri di pagamento, identificando le eccezioni in tempo reale. Le API possono confrontare istantaneamente i pagamenti con i dati di terze parti; ad esempio, possono essere utilizzate per lo screening degli elenchi di sanzioni o per verificare la proprietà del conto bancario a cui l'azienda sta pagando. Utilizzando le API per l'integrazione di sistemi di terze parti con la vostra piattaforma di pagamento, la vostra organizzazione può garantire l'accesso in tempo reale a qualsiasi database necessario per la convalida del conto o della conformità. I pagamenti eccezionali possono essere immediatamente messi in quarantena per un'ulteriore verifica, mentre quelli non eccezionali vengono processati normalmente. Apprendimenti e risultati I CFO e i tesorieri hanno bisogno di una serie più completa di controlli sui pagamenti per mitigare le moderne minacce di frode, tra cui l'intelligenza artificiale/l'apprendimento automatico e le API. Le organizzazioni hanno tre aree comuni che le rendono vulnerabili alle frodi: sistemi tecnici, processi ed errori umani. Le minacce moderne includono le truffe con compromissione delle e-mail aziendali, le frodi con assegni, le frodi telematiche, le frodi vocali deepfake e i ransomware. Le tecnologie che possono essere utilizzate per combattere le frodi includono regole predefinite di rilevamento delle frodi; screening, avvisi e notifiche in tempo reale; flussi di lavoro per la prevenzione delle frodi nei pagamenti; reporting e audit trail; e hub di pagamento. Poiché le minacce continuano ad evolversi, i team di tesoreria e finanza devono aumentare la loro consapevolezza. Siete interessati a scoprire come costruire programmi di rilevamento delle frodi nei pagamenti e di risposta agli incidenti per massimizzare la protezione end-to-end? Date un'occhiata a questo webinar on-demand. Gli esperti di cybersecurity e frodi di Corelight e Kyriba illustrano le strategie di difesa dalle frodi.

Applying Principles of Quality and Efficiency from the Manufacturing World to Treasury and Finance to Achieve More Efficient FX Risk Management. One of the principal tenets of Lean is a focus on customer value. Activities that do not have a direct bearing on the value of the product or end result are targeted for elimination. Our customers, using our platform and Lean principles work to transition their foreign currency related systems and processes to create greater automation and efficiency.

The quantified negative currency impact for North American and European companies has continued to impact MNCs negatively to the tune of $27.87 billion for Q3, 2021 and is increasing adversely when comparing the quarterly results of the past few years. The need for a process that mitigates foreign exchange risk becomes even more apparent when organizations experience impact spikes from volatility due to the global COVID-19 pandemic. Manufacturers first adopted Lean principles and processes where they needed them most: on the manufacturing floor. Revisiting Henry Ford’s flow production assembly line model, Kiichiro Toyota created the Toyota Production System (TPS) model, which propelled Toyota and the Japanese industry into a new age of productivity and global competitiveness. Toyota’s ideas have since been widely embraced and translated into concepts like Lean production and Six Sigma, who are common in global manufacturing. Companies and consultants who have demonstrated success using these approaches to eliminate wasteful processes and improve quality have extended them to other industries and other disciplines. While Six Sigma is a very scientific rigor around quality control, Lean looks to produce more with fewer resources and to help processes flow more smoothly. Lean, which tends to be less dogmatic than Six Sigma, describes a process for improvement and a set of workplace best practices. The management techniques include taking a long-term view of the business, as well as active mentorship of staff at all levels. There is great potential for companies who apply Lean and TPS principles to improving financial processes, as the guiding principle of Lean directly applies to the challenges faced by organizations trying to manage their FX risk. With little standardization and tedious, manual processes, there is a great opportunity for companies to focus more on value and eliminating waste. However, Lean is more about fixing a specific process. Lean practitioners outside Japan tend to focus heavily on specific analysis tools and omit critical elements of the best practices and management techniques. For Lean implementations to be successful, companies need to go beyond a specific project approach and integrate Lean as a guiding principle so that it can lead to continuous improvement. Applying Lean to Foreign Exchange Risk A growing number of companies in the U.S. are beginning to take a closer look at the principles of Lean and how they can help improve the costly, inefficient and often ineffective FX exposure management processes typical of most organizations today. By taking a methodical and disciplined approach, they are able to significantly reduce the time and effort spent aggregating, validating, and analyzing foreign currency data to make better risk mitigation decisions. Equally important, they create visibility to the entire process and support an environment that makes continuous improvement possible. Companies of all sizes with FX exposures can benefit from extracting and compiling their exposures from various systems whether they be ERPs, procurement or billing systems and applying Lean methodologies and processes to ensure hedging activities and other related processes like trading, confirmations, and settlements are all done as efficiently and effectively as possible with appropriate policies and procedures applied. Focus on Value and Eliminate Waste One of the principal tenets of Lean is a focus on customer value. Activities that do not have a direct bearing on the value of the product or end result are targeted for elimination. Our customers, using our platform and Lean principles work to transition their foreign currency related systems and processes to create greater automation and efficiency. Finance and IT must be partnered and work to assemble project teams with representatives from finance, treasury, and IT along with strong project sponsors to set sights on creating greater value and eliminating waste across the overall foreign exchange exposure management process. Finance and treasury, supported by IT, must methodically go through and aggregate transaction data from their ERP or other related systems to identify exposures and, in turn, deliver the capacity to make appropriate hedging decisions to mitigate risk. Pulling together regional experts and business unit representatives or various department leaders is a significant investment of resources, but it gives companies undergoing the exercise of streamlining FX and other processes exactly what was needed to gain visibility of the entire process, end to end. These cross-functional reviews often result in identifying manual processes required to pull together the data and validate results through the use of spreadsheets to calculate exposures. Once identified wasteful, manual processes are mapped out, it’s important to take the appropriate steps and have commitment from your executive leadership team and stakeholders to make the changes. For instance, the use of automation can cut the number of steps required to go from data aggregation to risk mitigation decision in half, while delivering greater transparency to the process as a whole. Assessing the Whole Value Stream Another tenet of Lean involves taking a holistic view of any process, considering the impacts and dependencies of other processes, both up and downstream. Manufacturing plants designed along Lean/TPS principles allow leadership to witness the entire process, end-to-end, from any place on the factory floor. To be effective, that same sense of transparency can be applied to the foreign exchange exposure management process. For many companies, finance is responsible for aggregating foreign currency transaction data from their ERP systems, which is then typically passed to treasury for appropriate risk management; whether it’s simply allowing the risk to reside on the balance sheet, as part of a natural hedge, actively managing the risk through a derivative and identifying how the impact to the income statement should be accounted for. Automation creates the bridge between data aggregation, validation, and analysis, so that both finance and treasury have visibility to detail and summarize views of the company’s currency exposures. As a result, discrepancies and potential errors become easier to spot, with instant visibility by every stakeholder in the process. That visibility extended beyond Treasury, Finance, and IT to executive management, who could gain a better understanding about how business practices impacted the company’s exposure to foreign currency risk. Automating FX processes illuminates underlying business practices driving overall financial practices and put a new lens by looking at the big picture. Strive for Continuous Improvement: Momentum Building The concept of continuous improvement is a key component of Lean; one that prods companies to go from one-time process improvement initiatives to making customer value and waste elimination a way of doing business. Companies benefit most from implementing software tools to support their new process workflow and provide greater transparency, achieving ongoing improvements requires continuous communication, teamwork, and leadership. As part of the analysis of waste elimination from FX exposure management processes, it is important to quantify the time saved on non-value-added activities and defined how that time/effort would be reapplied to creating additional value. In this way, Lean practices have the potential to build and “snowball” from one process to the next, where the more time saved and value added, the greater the opportunity to save more time and create even more value.   Want to learn more about how to improve your foreign exchange risk management process? Check out Kyriba's latest demo session and see how Kyriba helps its clients mitigate the effects of currency volatility and reduce hedging costs.

Kyriba è lieta e fiera di continuare a sostenere la serie "Tesoreria nella pratica" di AFP, e ciò vale anche per quest'ultima pubblicazione, "Identificare il valore per la Tesoreria: Automazione, Machine Learning e Intelligenza...

Kyriba è lieta e fiera di continuare a sostenere la serie "Tesoreria nella pratica" di AFP, e ciò vale anche per quest'ultima pubblicazione, "Identificare il valore per la Tesoreria: Automazione, Machine Learning e Intelligenza Artificiale”

Digital treasury tools, such as robotic process automation (RPA), machine learning and artificial intelligence (AI) are already being used to facilitate treasury automation. The use of treasury technology leads to better decision-making and also...

Digital treasury tools, such as robotic process automation (RPA), machine learning and artificial intelligence (AI) are already being used to facilitate treasury automation. The use of treasury technology leads to better decision-making and also frees time for skilled treasury practitioners to focus on strategic development. This guide outlines how RPA, ML and AI can–and are–being used to improve treasury management processes for receivables finance, payments, fraud detection and more. The guide also explores how to build a business case for a new automation project. The Need for Technology to Maintain Effective Operations Corporate treasury departments rely on technology to maintain effective operations. The technology varies and is constantly improving, offering ever more sophisticated solutions and functionality. Treasury uses a wide range of different technologies, from spreadsheets developed in-house to manage a specific process to highly sophisticated treasury management systems. Technology is also an enabler as treasury evolves from an operational department to a strategic partner to the whole of the business, with automation playing an increasingly important role. While technology is critical to improving operational efficiency, that efficiency is only achievable if the technology is deployed to perform suitable tasks, which requires accurate expectations of what each type of technology can and, just as importantly, cannot deliver. Treasurers must be able to do two things: Identify key inefficiencies, or “pain” points, within their operations. Match each activity to an appropriate technology with the potential to solve them. Pain points manifest themselves in different ways, whether as errors, such as missed investment opportunities or unhedged exposures, or as timeconsuming manual processes, such as the preparation of the cash position. While the root causes and associated operational weakness are relatively simple to identify, the challenge lies in selecting appropriate solutions to solve those problems. All companies have these pain points and, if left unchecked, they are only going to get worse. With the increased use of real-time payments, we are moving ever nearer to a world of real-time finance, an environment of constantly changing data. Without more automation, treasury practitioners simply will not be able to make decisions quickly enough. On a positive note, digital treasury tools, notably Robotic Process Automation (RPA) and machine learning, are already being used to facilitate treasury automation. The use of these tools can be shown to lead to better decision-making; it also frees time for skilled treasury practitioners to focus on strategic development. This guide outlines how RPA and machine learning can, and is, being used, and shows how to build a business case for a new automation project. Robotic Process Automation, Machine Learning and Artificial Intelligence In this section, RPA and machine learning/artificial intelligence (AI) are defined and explained along with the potential benefits of their use. The next section includes three use cases to highlight how different companies have already deployed digital technologies to streamline operations. Robotic Process Automation Robotic Process Automation is a rules-based technology enabling users to automate repetitive tasks. It effectively uses a software “bot” to replicate a series of manual processes performed by a person. Unlike a standard workflow process that operates within a single system, an RPA bot can be set up to capture data from multiple systems, as it mirrors a human treasury team member by sitting above existing systems. Because of this, RPA processes can often be implemented quickly and without major disruption to existing operations. RPA is typically used to replicate a manual, repetitive task, or series of tasks, that can be tightly defined. Machine Learning and Artificial Intelligence Artificial intelligence (AI) is the use of a computer or machine to mimic certain elements of human intelligence. Machine learning (ML) is a branch of AI, in which a machine learns how to identify patterns in data. Unlike RPA, which simply replicates a series of repetitive processes, machine learning can be used to analyze data to identify trends or patterns, via the use of algorithms. This goes to the heart of many companies’ problems with data analysis: companies generally hold, or amass vast stores of data, but they do not convert it into meaningful information. As with RPA, data analysis via machine learning is faster than human computation; once set up, machine learning can operate any time (constantly, overnight or according to a customized schedule), enabling decisions to be made with the optimal, latest available data. However, implementation is more complex than typical RPA scenarios. Machines can learn, or be taught via amendments to the underlying algorithms, patterns over time, but they are reliant on access to multiple data to perform meaningful calculations. Companies need to be prepared to make the investment in technology and data cleansing or preparation before any machine learning would be effective, both from a results and a cost perspective. The Potential Benefits of RPA and Machine Learning Although the use cases vary, the use of RPA and machine learning offer similar potential advantages, including: Improved accuracy. With RPA, as long as the process is set up correctly, the bot will perform the same tasks in the same way every time. The risk of human processing errors is eliminated and, if any variance between RPA outcome and actual outcome is identified, the RPA process can be adjusted. In the case of machine learning, accuracy will improve over time, as the machine learns and the algorithms are adjusted. Significantly reduced processing time. Bots and machines can perform typical tasks in a fraction of the time it takes a person to complete. This means that activities can be performed faster, so decisions can be made on the most recent available data. Results available, globally, when needed. Machine learning and RPA technology can operate at any time, so calculations can be performed overnight or on desired schedules to meet operational requirements. So, for example, in the case of cash positioning in a multinational organization, results can be available when teams in each location start their respective days, rather than two or more hours into them. Time management. Eliminating mundane processing from a treasury professional’s day frees that time to devote to more value-added activities, whether that is engaging with additional timesaving activities, supporting the wider business or focusing on strategic decisions. Improved morale. Although some treasury staff will be concerned about the impact of RPA and machine learning on their own jobs, for most organizations the technology will be an additional process that will improve team members’ experiences by eliminating the stress of calculating positions under time pressure or reducing the risk of error. Team members will also have time to spend on more interesting and personally rewarding activities. How Emerging Technologies Are Being Used This section outlines three ways RPA and machine learning are being used to solve particular problems faced by individual treasury departments. Case Study: Automating Time-Consuming Tasks via RPA One insurance company’s treasury department used to spend hundreds of hours a year processing internal customer requests for check images. While critical for the business as a whole, these requests were timeconsuming to complete and added no value within finance. The treasury team developed an internal RPA process via bot to automate the process. While the team had to spend some time training their internal customers on the new process so that requests were made in a standardized format to enable bot processing, the system is now operational and running three times a day. Using the bot has improved the response time for treasury’s internal customers, while releasing time back to treasury to devote to more value-added activities. It is now a task that treasury no longer has to perform. In addition, the customer experience and SLA have improved, as treasury can now typically respond to a customer’s request in a matter of hours, rather than weeks. Case Study: Improving Cash Flow Forecasts One of the key benefits of RPA is that it can be used to process data from a number of different company systems. This makes RPA a useful tool to improve cash flow forecasts, as they are built on data sourced from banks, treasury management and ERP systems and from other company departments, including payment teams. Séverine Le Blevennec, senior director of EMEA Treasury at Honeywell has led the development of an RPA process to improve the accuracy and timeliness of the in-house bank’s cash flow forecasts. She identified RPA as a technology that might have the capability to enhance the existing forecast, and then took time to fully understand whether RPA could work by examining the technology in some detail. Convinced that RPA was the potential solution, Le Blevennec then engaged with internal and external stakeholders to communicate her vision. She worked with Honeywell’s technology providers and banking partners to see whether data could be supplied in a more accessible way, wanting her colleagues to view the bot as a useful colleague, not as a threat to their jobs. Critically, Le Blevennec knew the bot needed to have a significant positive impact from the start, as she wanted the project to energize her colleagues toward future digitization projects. In other words, the new process had to deliver the expected returns. Ensuring this required a review of the current process and a strict testing program. Le Blevennec learned that “rule-based programming [like RPA] requires detailed documentation.” She revisited all existing processes and created seven workflows for seven different activities, from maturing time deposits to intraday payments and collections. She emphasized the importance of testing. Tests were performed in a mindset in which it was expected that “things could go wrong.” Then, before going live, the team used the new spreadsheet alongside the old process to make sure everything worked as expected. Since going live, Honeywell has seen some significant benefits. The new system is more efficient: Two hours a day have been saved. It is more accurate: The old manual system could only include data from about 40 Honeywell bank accounts. Today, data from over 160 accounts are included in the forecast, and any new accounts can be included easily. Enhanced visibility has resulted in improved counterparty risk management, reduced levels of un-invested cash and, as a result, increased investment returns. Most importantly, Honeywell’s treasury team has seen the benefits. They are less stressed, and more engaged for the next stage in Honeywell’s digitization journey. Case Study: Receivables Management A steady growth in sales, resulting in increased receivables, is usually good news. But it might not be for an AR team, over-reliant on expensive lockbox processing. With over 2,500 monthly checks all needing some form of human intervention coupled with increased sales, a technology company’s AR team suffered from low morale, leading to delays in receivables processing and reduced confidence in the accuracy of AR data in the ERP. As a result, the treasury team was so busy processing payments, they didn’t have time to convince customers to transition to more efficient, less costly electronic payment formats. The team recognized they needed a solution that could be scaled and that would allow them to react in the ever-changing B2B payment environment. It is one thing to recognize the need for change; it is another to understand how to bring it about. The team did their research and spoke to their banking partners. One discussion started with an enquiry on how to implement a more modern lockbox, utilizing the OCR codes; it ended with the team realizing that machine learning could be used to automate some of the processes. They were able to design a solution that would get machines to do much of the previously manual work. However, there were hurdles to overcome. For example, in one division, clients tended to pay by claim, rather than by invoice, and the ERP system didn’t hold the claim line item information. The team realized bridging the gap between the system holding the claim information and the ERP was well-suited to machine learning. Once the solution was operational, it freed time for the team to manage exceptions and also to improve the quality of the data on which the AI system relied. The time savings enabled the team to work with customers to send and enhance information coming into the system, so the machine learning tool could better consolidate and match the data, and constantly learn to improve. The result was dramatic. By replacing the manual gathering, consolidation and formatting that was required every morning, the AI-enabled receivables solution allows the company to quickly improve the time taken to process a payment. Most payments are processed within two days. This was achieved because of the consolidation of information. The payments are now standardized. Reconciliation is simpler, with the team confident all the information is there. Three months later, with even more time available as the machine continues to learn from manual exception management actions, the team can spend more time with collections and customers to help them provide better remittance information, further improving matching. The team can now build electronic adoption, with the AI bringing together remittance and payment automatically. Now, every time a match is confirmed, the system can see it and learn from it. The team can respond quickly to queries. Information is tracked immediately, so there is no need for time-consuming searches for data. The team has confidence in the data, and morale is high as they can focus on more value-added activities. Making the Business Case to Implement As with any technology project, it is critical to build a strong business case when seeking to adopt RPA or machine learning. This means getting buy-in from a project sponsor, and approval from all required stakeholders. Setting and achieving key success metrics will give credibility to the project, which in turn will help treasury practitioners introduce more digital finance initiatives. To help make a compelling business case and ensure the objectives are well defined, there are a number of key considerations. Understand the technology to maximize the potential benefits. As outlined above, different technologies are better suited to solving particular problems. The project owner needs to understand the nature of the problem and how the proposed technology will solve it. Some proposals may appear to be a standalone solution to a particular problem with limited impact across the wider business, yet when examined further, are either extendible into other functions and/or require change to operations within those functions. Optimize processes before automating. If there is an existing process, map it and review whether it can be made more efficient. Many manual processes incorporate separate checks and approvals to protect against error and fraud. While some may need to be migrated into an automated process, for example if a transaction exceeds a certain pre-set limit, it may not be necessary to migrate all of them, as long as the rules are tightly written. A machine learning project may require improvements to data management to enable automated data analysis. Communicate and educate stakeholders on the proposed solution. Communication is central to the success of any project. Senior management will have to approve the project. If IT input is required, they will need to be engaged early in the planning process to secure resources. Banks, technology providers and other data suppliers should also be approached early to plan how they can support the project. Treasury team members will want to understand the implications for them. Identify potential returns. One of the key benefits of automating a process, whether by RPA or ML, is to remove layers of human involvement in either mundane, standardized processing or time-consuming data collation and analysis. So, although there will be some clearly measurable costs and benefits, many will be “softer” benefits in the form of released time and reduced risk of error and fraud. Establish and monitor success metrics. It can be helpful to identify some clear targets to serve as measurements of the success of the project, such as how much time an RPA project has saved. It may be possible to illustrate consequential benefits too, such as improved investment returns due to more accurate cash forecasts. If possible, use these measurements to refine the bot or machine to achieve further efficiencies. Scale the solution; look for the next step. Measuring the outcome of one project will help build support and momentum for others. As technology develops, there will always be further ways it can be adopted to improve treasury operations. Greater Automation Is the Future As this guide has indicated, technology is enabling corporate treasury departments to operate more efficiently by automating processes and taking advantage of more advanced data analytics. In turn, these changes further enable transformation and evolution of treasury departments from laborintensive operational, tactical departments into strategic partners to the wider business. The adoption of new treasury technologies continues to accelerate, driven by multiple factors. Two stand out: the evolution of the “internet of things,” and the move toward “real-time” finance. While the catalysts for the development of these two trends is different, the implications for treasury and finance are closely linked. The Internet of Things The value of the internet of things comes from the way data can be shared between billions of different devices being connected via the internet. It allows individuals to control their personal environment (e.g., smart lighting and heating) and companies to manage a whole range of processes from stock ordering to logistics management. For treasury and finance, the value will come from being able to link the physical and financial supply chains and gain better insight into cash. To do so effectively, data sent out by these connected devices needs to be analyzed by artificial intelligence; the devices simply produce too much data to be analyzed in any other way. The Implications of Real-Time Finance There is a clear trend toward more real-time activity in treasury and finance, with real-time payments being just one, albeit significant, step. Notably, the move toward real-time processing is also a shift to 24/7/365, always on operations. Treasury will need to consider how to manage this change and, particularly, how to manage risks that will emerge overnight, including between the Friday close and the Monday restart. The growth of e-commerce has already provided a sense of changes to come. Consumers who pay online expect to see their order status updated in real time and, in some sectors, the service or product available in real time too. With the adoption of real-time payments, actions not limited to fraud prevention have to take place in real time as part of the payment initiation process, as real-time payments are generally irrevocable, with no opportunity to stop or amend payments. But managing payment processes is just one part of a much wider change that the adoption of realtime payments will bring to finance and treasury. If payments are being made in real time, treasury departments will need to manage their liquidity in real time too and they will rely on a level of automation and artificial intelligence to do so. And before long, the foreign exchange and money markets will move toward real time, profoundly affecting the treasury departmental day, which is currently structured by cut-off times. For these reasons, it seems inevitable that both RPA and artificial intelligence, including machine learning, will play a more prominent role in the management of corporate treasury departments in the coming years. Conclusion Although RPA and AI are seen as cutting edge, in reality many companies are benefiting from these technologies through solutions provided by their banks and technology partners. For organizations yet to implement the technology, doing so successfully requires three key steps: Identify a pain point to be solved. RPA and AI/machine learning both work best when implemented to solve particular problems. Don’t start using RPA; start using RPA to automate a process. Match the technology to the task. Different types of technology solve different problems. If you want to automate a process, RPA is likely to be the more suitable solution. If you want to analyze data, investigate AI, including machine learning. Build a business case. RPA and AI/ ML are likely to become even more important in the future, so a successful first project is important. Make sure your chosen technology can do what you want it to do, then build support for your solution among stakeholders including, critically, the treasury team. You can then use your successful first project as the springboard for future development.

A major shift is underway in the world of enterprise resource planning (ERP) software. With both customers and ERP software vendors driving a mass migration to the cloud, many companies have already completed their...

A major shift is underway in the world of enterprise resource planning (ERP) software. With both customers and ERP software vendors driving a mass migration to the cloud, many companies have already completed their ERP cloud migration projects—and thousands more are set to follow suit by the end of this decade. But ERP cloud migration is a costly and time-consuming undertaking, particularly where IT is concerned. For companies seeking to digitize their enterprise applications, it’s clear that corporate IT will be heavily taxed for the foreseeable future. Meanwhile, cloud ERP software vendors and system integrators are poised to reap the benefits of years of migration project work. The Challenges of Bank Integration For corporations,  ERP cloud migration projects are often global in nature — and many will need to tackle the complexity of a global banking integration project. This element of ERP migration is particularly challenging, significant coordination is needed with the company’s banks, and there is a considerable disparity between the payment formats required by different geographic regions and clearing systems. Indeed, bank integration is often cited as one of the riskiest and most challenging elements of ERP cloud migration. Simplify and Accelerate The good news is that companies can considerably simplify and accelerate a major component of cloud ERP migrations: bank integration for reporting and payments. Connectivity-as-a-service (CaaS) providers deliver pre-delivered, pre-tested capabilities for bank reporting and payments formats that shave months off the migration project, and reduce connectivity and format costs by up to 80 percent. In this Ebook You will learn about the key areas to look at during an ERP cloud migration payments project, including: Following banks’ schedules Navigating variations due to geography, banks, statutory reasons Connectivity with your specific cloud ERP software (SAP, Oracle, Microsoft Dynamics, etc.) Resourcing challenges You’ll also find out how you can significantly reduce the cost and time required to complete your ERP cloud migration project. Bank and ERP Cloud Integration: What’s Involved? Bank integration is unlike any other system integration. Today’s corporate IT teams are experienced in building interfaces between different back-office systems—but these are typically stagnated interfaces that do not require additional resources. In contrast, when working on a bank interface, the IT team will typically need many different resources to coordinate with each other, including IT, treasury, accounts payable (AP), the connectivity team, the bank’s tech team, and others. What’s more, the project timeline is usually at the mercy of the bank’s schedule. Bank ERP integration can similarly be time-consuming. IT first has to determine if the cloud solution is compatible with their ERP. Then, the data needs to be extracted out of the ERP and re-formated. IT departments are often stymied and reliant upon outside consultants to deliver integrations or core capabilities within the ERP. Furthermore, once the initial specifications for these connections are determined, they need to be tested - and they rarely pass on the first try. As a result, the development team will need to rebuild, re-test and work through the coordination effort all over again. In some cases, two to five rounds of testing may be needed. What are the Challenges in ERP Cloud Migration? For IT, the bank integration component of an ERP cloud migration brings a number of additional challenges. Working on the Banks’ Timelines Delays in the ERP migration project often arise due to delays by the company’s banks. If the company has a robust relationship with a core banking partner, it may be able to move up the project queue for that particular bank. But with many corporations needing to manage dozens of banks globally, the IT team will be forced to follow those banks’ schedules—which means working across different time zones and navigating banking holidays and seasonal moratoriums on testing. Navigating Geographical Variations No two banks are the same, and it’s a common misconception that SWIFT is a standard message type across banks. While SWIFT is moving from MT to XML, each bank will still have its own unique requirement in terms of how it will accept incoming files. For any payment type, companies will need to ensure that payments are formatted correctly for a specific bank’s requirements and that they contain the information the bank needs to complete the payment. Most corporations will need multiple formats per bank, which might include different formats for low value, high value and FX transactions. Given the complexities, it’s no surprise that IT firms routinely take two years or more to work through all these bank connections and payment format testing. Payments Integration and Fraud Prevention Payments integration is a challenge, given the ever-increasing threat of fraud. Even with effective tools like artificial intelligence (AI) and machine learning, the threat level is the highest it's been yet, according to Strategic Treasurer's 2021 Treasury Fraud & Controls Survey. In addition to financial loss, fraud events damage a company’s reputation and lead to the loss of essential data or assets. It is therefore essential to use ERP integration as a way to put technology in place to protect your organization. This should include digitizing payment workflows, standardizing controls and screening payments as part of an integrated payments hub. Complexities for IT Adding to these challenges, bank integration brings a number of complexities where IT is concerned. Limited IT bandwidth Corporate IT teams are already thinly spread across numerous projects and support requirements. As such, the time involved in undertaking a bank integration project can be particularly onerous. No Reusable Data When IT teams work on an ERP implementation, they have to develop their banking interfaces as a one-off exercise. While ERPs may be moving to the cloud, ERP solutions are still typically private cloud providers—and no ERP in the market has readily available, reusable banking formats that can be shared among users. Multiple Stagings Bank and payment format development is no different than for any other interface or application, as IT has to work through the same rigorous processes. If the business users need a new payment format, such as a new ACH for an existing bank, they will still need to go through the process of testing, QA, nonproduction and production. This process can take months, meaning there will be a considerable delay before the end user has access to the payment format. Resource Requirements Once formats are in production, the IT infrastructure team will need to manage those formats going forward. This involves activities such as troubleshooting bank issues, editing formats as required by the bank and working with the business to add new banks when the need arises. Depending on the company’s banking footprint, two to five people will likely need to be tasked with managing these connections on an ongoing basis. Integration Made Easy Standard ERP integration is a lengthy process that is incredibly taxing on IT. But there is an easier way. Leading technology providers should offer a pre-built, pre-tested connectivity solution that takes minimal time to get up and running and provides access to even greater functionality immediately. Leading ERP and Bank Connectivity Technology Considerations ERP integration brings many challenges to IT - but these can be overcome by adopting a technology solution that simplifies both bank and ERP connectivity. With 20 years experience in connectivity, Kyriba can integrate bank reporting and payments, while mitigating risk--all in record time thanks to our use of application programming interfaces (APIs). Accelerate your ERP Migration Project and Reduce Costs Our out-of-the-box, bolt-on bank connectivity can help you achieve exceptional time and cost savings on bank integration. While standard integrations might required months of testing, our connections are pre-tested and ready to go. Access a Payment Format Library As a multi-tenant application, Kyriba is unique in the marketplace as our entire 2,500-strong customer base uses the same predeveloped and tested payment formats. What’s more, we have full-time staff whose sole responsibility is to build and test payment formats. As a result of 20 years of development, we offer more than 45,000 pre-developed and bank-tested unique payment scenarios. Simplify Interfaces Minimal IT resources are needed when it comes to interfacing between the ERP software and Kyriba. Using both SFTP and API, we take all payment files into our prebuilt interfaces with no code specs needed from IT. Focus on the Wider Project Kyriba’s connectivity platform frees IT up from the daunting task of bank integration—so you can focus on keeping the ERP project on schedule and on budget. Avoid the Need for Swift Connectivity and Certifications When you use Kyriba for connectivity, IT won’t need to manage the Alliance Lite2 SWIFT connection— and there will be no need for annual testing and certifications. Manage Ongoing Maintenance and Support When the project is over, Kyriba will handle all ongoing maintenance and will act as the banking IT support arm for business users, meaning you won’t need dedicated IT resources to troubleshoot bank issues. Connectivity as a Service By offering Connectivity as a Service (CaaS), Kyriba can actively manage bank connections on your behalf. As a result, no IT support will be needed to manage your company’s bank connections or undertake file testing with banks—and with Kyriba's API capabilities, companies can also add new banks in a fraction of the time that would be needed for custom development within the ERP. Market-Leading Payment Fraud Protection With IT increasingly tasked with risk mitigation, Kyriba’s market-leading payment fraud solution adds considerable value. The solution uses machine learning to detect any anomalies or suspicious activity, and provides alerts to stop payments for investigation before they are sent to the bank. Payment Tracking Kyriba offers real-time payment tracking with four levels of acknowledgement. By harnessing SWIFT gpi, Kyriba is able to track the entire lifecycle of the transaction. Innovation and Agility Hub Payment technology is evolving rapidly. Kyriba’s innovation and agility hub can deliver Real Time Payments (RTP) and can connect with other clearing systems and payment solutions. Smart Assignment Kyriba’s machine learning will have visibility to your banking partners and costs associated with each payment. Smart assignment can intelligently route your payments through the lowest cost provider. Bank Monitoring Kyriba offers global bank monitoring of all incoming and outgoing files. Kyriba clients can rest assured that they have fully outsourced banking support. Established Partnerships As an Oracle GOLD partner, Kyriba's Payments Network supports over 1,000 Oracle customers. Our payments solutions have also achieved SAP-certified integration with the SAP NetWeaver® technology platform and SAP S/4HANA. APIs and Connectivity The future of connectivity lies in Application Programming Interface (API) technology. This is where Kyriba has a key advantage. As the leader in connectivity in treasury and finance, Kyriba understands how to maximize the power of APIs to help finance leaders drive digital transformation and more informed decision-making. Bank APIs APIs offer an expedited pathway for bank connectivity, as well as a gateway to real-time business intelligence and digital solutions. Unlike file transfer protocol (FTP), APIs do not require files to be sent or downloaded. Data is exchanged point to point between the systems immediately, allowing for instant data transmission and eliminating substantial risk. Kyriba connects with over 600 global banks every day on behalf of our 2,500 clients using a variety of connection protocols, including APIs. Banking services available via API vary by bank, but can include real-time payments, domestic payments, cross-border payments, bank balance and transaction reporting, and SWIFT gpi payment tracking. Users receive immediate responses from banks, and the ability to access new data and notifications in real-time. ERP APIs Kyriba also works with ERP system providers to embed other systems via API integration into their workflows so that the user doesn’t need to take any action outside their ERP. These add-ons perform the initial formatting so that files can be exported from the ERP, translated to the API provider’s format and pushed out to the connectors. Corporate end-users can also integrate APIs into their ERPs on their own. These plug-and-play solutions are facilitated through our Open API platform, which provides users with common ERP integrations that connect to their own applications. Kyriba users can browse our online catalog, which lists all our available APIs and their prospective use cases. Here are a few examples: Bank Account Groups: This API allows for the creation of new account groups to filter and/or group accounts in processing and reporting. Users can modify the set of accounts that belongs to a specific group, and retrieve or update the pooling account of the group. Companies: This API allows for the setup of companies. Users can get a list of the companies located in a country, receive a list of companies whose name contains specific characters, and obtain all the setup fields of a specific company. Third Parties: With this API, users can manage and set up third parties who represent the companies they manage. Users can retrieve and update third-party details, and create or delete third parties via API. Optimized Bank Connectivity Conclusion There are many challenges for IT when deploying an ERP project, from working around banks’ schedules and specifications, to navigating the complexities of geographical variations - all while juggling an already heavy workload. Fortunately, Kyriba’s in-house developed, complete CaaS solution encompasses all ERP software vendors, internal financial systems, third party providers, and over 600+ pre-configured, pre-tested connections with banks across the globe - allowing for fast and simplified ERP migration. Payment and connectivity costs can be reduced dramatically, while the time spent on bank integration can be streamlined by as much as 80%. What’s more, freeing up the IT team from having to work within the constraints of the banks will help you keep the wider ERP project on time and on budget. Check out this webinar to learn how Treasury and IT worked together at Hilton Grand Vacations with Kyriba to speed up connecting more than 10 banks and 300 bank accounts as part of their Oracle ERP cloud migration project. 

 A Strategic Treasury Focus Boosts Cash Flow and Minimizes Risks Treasury operations manage the lifeblood of their companies: cash liquidity. CFOs know that their treasury teams are critically important, handling everything from cash flow...

 A Strategic Treasury Focus Boosts Cash Flow and Minimizes Risks Treasury operations manage the lifeblood of their companies: cash liquidity. CFOs know that their treasury teams are critically important, handling everything from cash flow forecasts to optimizing working capital, along with foreign exchange currency risk and investing and borrowing. The team’s performance has a direct impact on the bottom line. Yet, 22% of CFOs and senior finance executives say they don’t see their treasury team as a profit center, according to a recent survey by CFO Research and Kyriba. And only a quarter of the executives say their treasury operations are operating at a high level with a strategic approach. This report examines what the survey says about the links between treasury and overall performance, the obstacles that treasury teams face and how CFOs can boost their treasury performance to improve overall profitability. Which of the Following Best Describes Your Role? KEY POINTS Senior finance executives expect treasury teams to manage critical tasks linked to cash flow and risk, according to a survey. That three-quarters of finance executives view their treasury operations as strategically lacking. Obstacles faced by treasury teams include complex financial structures and siloed systems, and a lack of technology investments, real-time business intelligence, expertise and process automation. A lack of spending on treasury and a focus on everyday tasks over strategic objectives block progress for treasury teams. Working capital optimization is the top treasury concern of financial executives moving forward. The surveyed finance executives also acknowledge that their treasury organizations need to make technology and process improvements to meet industry best practices. Predictive analytics, payments automation and cash management are the top three technology and process improvements that treasury teams need to make, according to the survey respondents. WHY TREASURY PERFORMANCE SHOULD DEMAND YOUR ATTENTION There is widespread agreement among CFOs and other senior finance executives: Treasury performance is critical to the health of their organizations, and they expect their treasury teams to manage a range of critical tasks. According to a 2020 CFO Research/Kyriba survey, senior finance executives give similar weighting to a range of treasury department priorities: accurately forecasting cash flow, operational efficiency, fraud prevention, compliance, optimizing working capital and FX risk management are somewhat evenly matched. Rather than singling out one or a few of the priorities, the 156 surveyed executives indicate that all are nearly equally important. The survey also reveals another theme: finance executives tie treasury performance directly to cash and liquidity management. The surveyed executives measure treasury performance based primarily on free cash flow, cash used for working capital, productivity and efficiency, investing and borrowing performance, and reduced risk exposure. These are all important, of course -- liquidity drives business performance, CEOs often give guidance to the investment community about meeting free cash flow targets and cash is needed for working capital. What Are Your Current Priorities Related to Treasury? But whether or not the finance executives formally track these factors as key performance indicators for their treasury teams, nearly all of the executives have the same expectations. They want better returns from cash, more optimized investment and borrowing, best practices executed for liquidity and cash management, and protection against fraud. On the topic of the best ways for treasury teams to optimize liquidity, the survey respondents again see almost-equal priorities rather than one or two favorites, giving nearly the same importance to reducing borrowing costs, increasing returns on excess cash, generating free cash flow, mobilizing global cash more efficiently and implementing supplier financing programs. They also give similar weights to each of eight areas where their treasury teams could make a better contribution to overall business performance. Increasing cash flow is the favorite at 41%, followed by increasing interest earned on excess cash, protecting against payments fraud, improving treasury team productivity, centralizing treasury data and processes, reducing currency volatility impacts, providing secure and efficient global payments, and providing business continuity planning for global treasury. Finance executives expect their treasury teams to meet all of these cgoals, and if they aren’t done right, it costs their organizations in financial losses or missed opportunities. CFOs recognize that cash is the lifeblood of their organizations. When treasury can manage cash and liquidity well—if it can provide visibility to cash and deploy it effectively, optimize investment and borrowing, and protect cash from fraud and currency risks—then it sets itself up to optimize how cash is made available and deployed, such as for cash operations, stock dividends or company growth in other parts of the world. THE CURRENT STATE OF TREASURY Despite the consensus that treasury operations are integral to company success, the survey also shows that treasury operations are lagging considerably behind the vision that the CFOs and other finance executives have for them. Surprisingly, 22% of the surveyed executives say they don’t see their treasury team as a profit center. On behalf of those who don’t share that view, 53% of the surveyed executives say their treasury teams contribute as a profit center by earning greater returns on cash and 34% say they contribute by unlocking supplier discounts for early payments. Rounding out the profit-center views, 28% see contributions from treasury’s FX intercompany management and 24% from viewing treasury as an in-house bank. On the bright side, 78% of the CFOs and other senior finance executives in the survey view the role of treasury as actively contributing to the bottom line. And most are earning greater returns on cash from areas such as investment income on the large cash balances that companies frequently hold in today’s economy. They also value cash management and see cash as something that can help create profitability and improve margins. The glass-half-empty view? The executives in the 22% contingent probably are not aware of the potential links of treasury to value creation, and are likely not investing in things like cash forecasting or technology that will help their treasury teams contribute in strategic roles, viewing cash merely as a means to pay bills, and not much more. How Do You See Your Treasury Team Contributing as a Profit Center? When asked about their current state, only one quarter of surveyed finance executives describe their treasury operations as “strategic,” the highest level, meaning that treasury “creates value through enterprise-level insight and intelligence.” Three out of every 20 finance executives surveyed say treasury is operating at an “ad-hoc” level, or the lowest level, which is primarily reactive. Anything below strategic is suboptimal. But why are treasury teams being placed in the not-strategic category? The surveyed finance executives report several internal obstacles that restrict the CFO’s ability to support organizational growth and bottom-line value, with a fairly even distribution between those obstacles: complex financial structures, siloed or disparate financial systems, lack of resources, insufficient technology investments, lack of real-time business intelligence, lack of expertise and lack of process automation. All of these obstacles point to a mindset that the company hasn’t invested the time and money necessary to improve treasury processes and the systems that support them. They also signal a lack of collaboration and coordination in the way the financial structure is set up. A lack of spending on treasury and a tactical focus, where time is spent on completing everyday tasks at the expense of forward-looking achievements, translates to lower productivity for treasury teams, especially for the range of critical tasks and high expectations that CFOs have set out for them. Companies are getting in their own way when they fail to prioritize treasury operations and don’t invest in the capabilities and tools that treaury needs. HOW TO GET BETTER CFOs value the importance of treasury operations, and most of them recognize that their treasury teams haven’t reached a strategic level yet. So how do they set up treasury to achieve its full potential? The key barrier is that treasury teams often get so bogged down in reactive tasks that they don’t create opportunities to work on strategic tasks. If treasury can get around its mountain of tactical work, it can be more proactive with insights and analysis. One way that CFOs appear to be attacking this issue is through technology. The survey shows that more than one-third of the respondents use connectivity middleware/payment hub software, data visualization/business intelligence software and mobile devices for multifactor authentication with their finance teams. A slightly lower percentage of the surveyed finance executives employ application programming interfaces to banks and trading partners, as well as machine learning and robotic process automation. All of these technologies help harness data and can make treasury teams more effective and analytical, which helps them make better decisions about managing cash and liquidity. Fostering more analysis of data and information creates an opportunity for treasury and finance to become more strategic. TREASURY ORGANIZATIONS NEED TO MAKE TECHNOLOGY AND PROCESS IMPROVEMENTS TO MEET INDUSTRY BEST PRACTICES. PREDICTIVE ANALYTICS ARE AT THE TOP OF THE LIST, CITED BY 45% OF THE RESPONDENTS AS AN AREA OF INTEREST, FOLLOWED BY PAYMENTS AUTOMATION AT 32% AND CASH MANAGEMENT AT 31%. In Which of the Following Areas Does the Treasury Organization Need to Imporve Its Technology and/or Process to Match Industry Best Practices? The surveyed finance executives also acknowledge that their treasury organizations need to make technology and process improvements to meet industry best practices. Predictive analytics are at the top of the list, cited by 45% of the respondents as an area of interest, followed by payments automation at 32% and cash management at 31%. The number of organizations utilizing technology that still acknowledge the need for improvement show a level of aspiration. CFOs and their organizations are recognizing they need to make changes to achieve the performance standards they’ve set for their treasury teams based on free cash flow and other factors. What Are Your Top Three Treasury Concerns for 2020 and Beyond? Looking ahead, the top three treasury concerns for 2020 and beyond are working capital optimization, according to 41% of the surveyed executives, followed by payments fraud for 29% and low interest rates for 28%. The other items on the treasury concerns list include treasury operating costs, treasury productivity, currency volatility and business continuity. The diverse pattern of responses indicate that other than with working capital optimization, every organization will have its own individual set of priorities for fortifying its treasury operations. Also, with no consensus about treasury deficiencies, each organization will have to carefully examine and gain a better understanding of its own treasury team, which could lead to visibility that hasn’t previously existed. The bottom line is that CFOs and other finance executives value their treasury teams, and they have a good understanding of all the vital benefits that their teams can deliver—a point made repeatedly through the survey results. Although there may not be a simple fix, they’ve identified a list of internal obstacles that they must overcome to improve treasury. They also recognize the opportunity at hand: to bring their treasury operations up to a strategic level where they can fulfill their potential. To make that happen, they need to arm their treasury teams with the right tools to understand and analyze data, and to make better decisions. Starting with some simple investments in technology, CFOs can improve the efficiency and effectiveness of treasury. And as that efficiency and effectiveness grows, it increases the probability of good outcomes like increased profitability. CONCLUSION Treasury performance is tied directly to cash and liquidity management. CFOs know that accurately forecasting cash flow, operational efficiency, fraud prevention, compliance, optimizing working capital and FX risk management are all critical tasks that their treasury teams must manage to sustain the health of their companies. Most of them also recognize that their treasury teams need work. Most treasury operations fail to achieve their full potential because they get bogged down in tactical, reactive work. Treasury teams need investments in predictive analytics, payments automation and cash management. As technology and process improvements help treasury teams to harness more data and employ more analytics, those teams will become more strategic and capable of meeting their CFOs’ expectations. And companies will enjoy improvements in free cash flow, cash usage for working capital, productivity and efficiency, investing and borrowing performance, and reduced risk exposure.     Check out this on-demand webinar and learn how 2021 AFP Pinnacle Award Winner HCSC transformed into a data-driven treasury with 1000+ hours of productivity improvement and 90% reduction in working capital requirements.

It seems counterintuitive. Even as businesses spend more time and money than ever combatting payments fraud, the crime itself becomes more ubiquitous. In a new study by CFO Research, 40 percent of senior finance...

It seems counterintuitive. Even as businesses spend more time and money than ever combatting payments fraud, the crime itself becomes more ubiquitous. In a new study by CFO Research, 40 percent of senior finance executives report that organizations in their industries are experiencing a much higher incidence of payments fraud than they did two years ago. Payments fraud is any fraud that involves falsely creating or diverting payments. Check fraud, credit card fraud, access fraud, and “spear-phishing” are common varieties seen by CFOs. Some finance chiefs report that the risk associated with payments fraud now approaches the materiality of foreign exchange risk and other high-value uncertainties. Indeed, beyond the sometimes substantial hard-dollar costs, payments fraud can result in lower productivity among employees tasked with dealing with the fallout, adverse customer experiences, the actual loss of customers, a stained corporate reputation, and, for publicly traded companies, losses in stock market valuation. For CFOs charged with safeguarding corporate coffers, there is no silver bullet that can stop payments fraud in its tracks. Managing and minimizing the problem is a discipline unto itself. Done well, it is a holistic, proactive undertaking that combines best-practice processes with dedicated detection and monitoring programs built on the latest advanced technologies. Done well, it also allows CFOs to do a better job of keeping corporate directors apprised of the risks their companies face in this area, and the safeguards in place to mitigate them. Figure 1. The Biggest Challenges My Finance Team Faces in Trying to Combat Payments Fraud Identifying—and Resolving—The Challenges to Success The biggest challenge that CFOs face in combatting payments fraud is finding and implementing the right technology. Technology was cited as a key challenge by nearly one-in-two (45 percent) of survey respondents in the recent CFO Research survey. Conducted in collaboration with Kyriba, the survey polled 167 U.S. finance executives at companies with more than $100 million in annual revenues across a wide range of industries. (See Figure 1). Other commonly cited obstacles include securing the budget for anti-fraud initiatives (38 percent), and finding the time to pursue them (37 percent). Rounding out the top five challenges, finance executives say it’s a challenge to assemble a team with the skill sets (29 percent) and knowledge base (25 percent) needed to fight payments fraud effectively. And, anecdotally, some respondents also suggest that companies aren’t doing enough on the front lines to fight fraud. “Work with the clerks and managers that are likely to be the first people to be contacted or become aware of a fraud attempt,” one survey respondent advises. “They can stop attempts before they get to the payment phase.” Another finance executive suggests it is simply time to buckle down to the task at hand and do a better job of it. “Set aside sufficient budget, do the proper research, then employ the right specialists to get this in place,” the respondent admonishes. “Invest in strong technology and air-tight workflow,” writes another. “Allocate the people and resources to combat and reduce fraud—(the) benefits fall to the bottom line,” writes still another. Report from the Front: Fraud Is on the Rise Payments fraud is on the rise. Four in ten (40 percent) of survey respondents say organizations in their industries are experiencing a much higher incidence of payments fraud than they did just two years ago. Another 15 percent say they can’t confirm or rebut the idea, leaving open the possibility that increases in payments fraud are broader still. These findings are directionally consistent with other studies, including the 2017 AFP Payments Fraud and Control Survey conducted by the Association for Financial Professionals. It found that 74 percent of organizations had experienced attempted or actual payments fraud in 2016, up from 62 percent in 2014 and the highest level recorded since the AFP began tracking the problem in 2006. Contrary to what one might expect, it isn’t always smaller, less sophisticated enterprises that are being impacted by payments fraud. In 2016, the AFP survey found, organizations with at least $1 billion in annual revenue were actually more likely than their smaller counterparts to have been hit by the crime. And while the majority of the respondents to that survey reported that their company’s direct payments-fraud losses were relatively small—less than $100,000—32 percent of financial professionals at companies with at least $1 billion in revenue and more than 100 payment accounts reported losses exceeding $500,000. Within that group, 16 percent said their losses exceeded $2 million. The reason behind the growing incidence of payments fraud isn’t hard to fathom. Throughout history, criminals have demonstrated a remarkable dedication to trying to outsmart their victims, and the advent of new technologies such as social media and mobile shopping and mobile banking have simply widened the field of opportunity. While check fraud remains the most common type of payments fraud, for example, criminals today are increasingly exploiting the digital technologies that make it faster and easier for companies and consumers to interact with each other. Last June, the Federal Bureau of Investigation felt compelled to issue an alert warning about the growing problem of “business email compromise,” in which fraudsters target businesses working with foreign suppliers, or businesses that regularly make wire transfer payments. The relentless enthusiasm exhibited by criminals searching for new ways to defraud businesses means that businesses must combat their efforts with equally relentless countermeasures. Elevating Payments Fraud Detection to a First-Order Priority Only 10 percent of the executives in the CFO Research survey feel strongly that most finance teams in their industry have strong processes and technologies in place to capably and efficiently detect fraud or ensure fraud-related compliance. It is a weak endorsement of current strategies for managing payments fraud. And where companies do seek to battle back, the tactics they use often are aimed at historical threats rather than evolving fraud strategies. Asked which are the most important tactics used by their companies, 45 percent of survey respondents cite auditing (audit trails). That’s followed by expanded use of electronic payments (41 percent) and daily reconciliations (35 percent). All three are valuable tools, to be sure. By contrast, consider that only about one-third of survey respondents (34 percent) say they employ dedicated fraud detection and monitoring systems that can proactively ferret out fraud attempts. The CFO too often appears to be checking the rear-view mirror instead of scanning the road ahead for trouble. Many finance executives also admit that they need to be doing more to support their boards of directors in this area. Asked where their boards most often fail to receive critical information and decision-support data from the CFO, 43 percent list fraud monitoring and mitigation—more than any other area. Thirty-seven percent also say their organizations lack the tools or technology to enable the board to make good decisions on this issue. Figure 2. Tactics for Managing Payments Fraud That My Finance Team Should Substantially Improve The Way Forward: Fraud Detection Where to begin? Dedicated fraud detection and monitoring systems top that list of tactics that the finance team should substantially improve. Cited by 36 percent of survey respondents, fraud detection and monitoring handily outpaces other tools and practices that include limiting the use of paper payments (26 percent), automated approval workflows (24 percent), audit trails (22 percent) and daily reconciliations (22 percent). (See Figure 2). Several survey respondents noted that the ever-shifting and expanding payments-fraud landscape is sufficiently daunting that they advise turning over the work—particularly fraud detection and monitoring activities—to third-party providers for whom it is a core capability. As one survey respondent puts it, “Outsource much of the fraud function to companies that have strong controls. Third parties may be better at this than your team.” Ten Best Practices for Combatting Payments Fraud Understand your vulnerabilities. With so many types of payments fraud, it’s impossible to do a good job of combatting them without understanding what they are. Examples include external threats such as hacking of treasury systems by third parties, as well as a raft of internal threats. The latter include fraudulent payments sent by employees to a company’s bank, either willfully or as an unknowing consequence of a spear-phishing attack; and fraudulent purchase orders and invoices created by employees that are then paid out to related third parties. Erect roadblocks to unauthorized access to corporate information systems. Deploy robust login and user authentication procedures, including dual-factor and in some cases multi-factor authentication. Move finance data to the cloud. While data security has long been cited as a reason for not moving data to the cloud, the growing consensus today is that cloud providers, for whom security is a core competency, offer greater, not weaker, security systems and protocols than most companies can deliver on their own. Because a significant percentage of payments fraud originates internally, moving corporate finance data to the cloud can reduce the opportunity for it to occur. Boost control over global bank accounts. Maintaining a handle on bank accounts becomes more difficult as companies grow and expand globally, but it’s a task that can’t be ignored. Companies need to make sure they have systems that can provide transparency into accounts, authorized signers and account documentation; track all bank activity; and efficiently reconcile accounts with banking partners. Make use of digital signatures. All commerce and banking today is electronic at some point in the payments cycle. Digital signatures, which can help authenticate transmitted payment files, can minimize opportunities for payments fraud. Centralize payments activity in a single system. Coupled with multiple, standardized and electronic approvals, an integrated payments system allows for a complete and detailed electronic paper trail for all payments, minimizing opportunities for fraud. Standardize settlement instructions for financial trades. For any kind of investment transaction, including foreign exchange and derivatives transactions, embedding standardized settlement instructions in corporate financial systems can not only improve efficiency but also help block any redirection of funds to unauthorized accounts. Educate employees. Even the best anti-fraud program will spot fraud only after it’s occurred. That’s still extraordinarily valuable, especially when the system is able to spot the fraud quickly. But one of the best ways to prevent payments fraud is to educate employees about the various types of fraudulent schemes they may encounter, so that they can avoid being duped by them and prevent fraud from occurring in the first place. Update and test your fraud-detection capabilities. Corporations should review their payments-fraud detection/monitoring systems and protocols to make sure they’re working. Some companies may have the resources to do this internally, but many will find it makes sense to engage a third-party expert to both create defense systems and to test them regularly. Regularly participate in opportunities to share with and learn from other organizations. Few “industries” adapt and evolve faster than the payments-fraud industry. A company can no more allow its fraud detection and prevention program to remain static than it could allow its products or services to remain unchanged. Companies should make sure the finance function, and any others that touch on the payments process, participate in conferences and workshops where they can share with and learn from other organizations combatting the same challenges. Conclusion Focusing on the five core challenges to addressing payments fraud is a strong way to get started. Technology, Budget, Time, Skills, and Knowledge are all critical components to developing and implementing an effective strategy. The sidebar, “Ten Best Practices for Combatting Payments Fraud” adds some tactical specificity to the CFO’s search for an answer to payments fraud. No matter which route CFOs take, it’s clear that getting going sooner rather than later makes sense—especially if they count their own organizations among those that are only modestly effective at managing payments-fraud risk today. CFOs increasingly feel that fraud detection and monitoring must become one of their core responsibilities, because it is the only chance they have of staying at least even with an evolving threat. And that threat is not only about the money; it is about the customer, and the brand, and the business. “You need to start already,” concludes one survey respondent. “The criminals are adapting faster than we are.” You Need to Start Already. The Criminals Are Adapting Faster Than We Are.” Check out this on-demand webinar and learn from cybersecurity experts from Corelight and Kyriba on how to build B2B payment fraud defense programs to maximize end-to-end protection.