Interview with Kyriba: Making Liquidity Planning Actionable in Real-time
Originally posted on InvoiceFinance.com by John Goodden
I recently sat down with Bob Stark, Global Head of Market Strategy at Kyriba. He was nice enough to answer a few of my questions about Kyriba’s operations, ESG and the current banking problem. Below is the interview.
I read on your website that Kyriba has been in business for 20 years. Could you tell me a little about the history of Kyriba, and how its mission has developed over the years?
Kyriba was born in 2000 as a SaaS application before software was going to the cloud.
From its inception, Kyriba’s mission has been to help our customers manage their cash lifecycle. The tools that CFOs needed to optimize cash and liquidity have changed over the years, especially in times of crisis.
While our mission has not wavered, our platform has expanded, growing from cash management and forecasting in its early days to a comprehensive platform that delivers end-to-end treasury, liquidity planning, payments, and risk management.
Today, the platform is API-enabled and built to support the CFO’s data strategy, which includes key capabilities such as multi-scenario liquidity planning, supplier and receivables financing, FX exposure management and real-time payment fraud prevention.
To date, Kyriba has more than 2,500 clients worldwide, manages more than 1.3 billion bank transactions per year, and processes 250 million payments for a total value of $15 Trillion annually.
Please tell me more about Kyriba’s liquidity platform, especially how AI is used in the platform.
Every CFO needs to harness data, in real-time. APIs unify data and AI helps make the data actionable so that finance teams can make data-driven decisions in real-time.
Our world has changed in the past decade whereas crisis, volatility and risk mitigation all happen in real-time. Whether we are looking at identifying and preventing payments fraud or improving the resilience of our cash forecast against a multitude of risk scenarios – CFOs need to make sense of data at machine speed so they can make rapid decisions to protect their balance sheets, income statements and cash flows.
The Silicon Valley Bank meltdown effectively materialized over the course of a morning, where decisions to protect liquidity needed to be made in minutes. Currency markets move every second, with the potential to wipe away millions in value in less than a minute.
Artificial Intelligence is critical as it arms CFOs with actionable intelligence. At its simplest, machine learning models are predicting events (e.g. when will this cash flow happen) and predicting outcomes (e.g. this is a suspicious payment) at a speed that cannot be replicated by people. Especially as APIs are delivering real-time payments and real-time bank reporting to treasury and ERP systems, it is critical that a finance team’s processes are not slowed by internal governance procedures. The answer is to operate at machine speed, which AI enables.
The rise of generative AI – such as ChatGPT – expands the potential of data-driven tools by embedding AI into our software to help us answer questions such as “how much cash do I have”, “why did my forecast variance increase by 5%” and “what is the biggest risk to our free cash flow target”. While generative AI tools are still immature, every FinTech is evaluating how to best embed AI within their client’s user experience. This is pivotal to how we engage with software going forward. AI will change everything.
You devote a section of your website to explaining how Kyriba adopts ESG values. What philanthropy projects has the company recently embarked upon? How has your governance been shaped by ESG considerations? And does the liquidity platform help companies identify and reward suppliers with higher ESG scores?
Kyriba has always valued philanthropy, diversity, inclusion and engaging in our community. What ESG governance has introduced is the opportunity to measure the breadth and effectiveness of your programs against yourselves and your peers. This is important to drive accountability when supporting our customers, our community and the Kyriba team.
From a Kyriba perspective, we support a culture of giving. Most Kyriba employees work remotely, so our programs include formalized initiatives in office locations balanced with support and incentives for those in other parts of the world.
In addition to Kyriba’s own efforts to do its part in creating a more sustainable, equitable and inclusive world, we are also keenly aware of the growing imperative of ESG to business leaders – including CFOs.
For companies to truly make a meaningful ESG impact, they need to include their supply chain in the process. One way Kyriba is helping its clients do this is by integrating ESG data into their supply chain financing model, to reward those suppliers that quantitatively demonstrate higher ESG performance. As this performance-based lending matures, we continue to work with our direct clients as well as banking partners who extend our platform to their own customers to further refine the data sources and influence models.
ESG is an ongoing journey and extends far beyond working capital and supply chain finance programs. Both corporates and banks, as well as technology platforms, still have a lot of work to do to include and embed ESG in all facets of operations.
In the light of the recent bank failures in the US (Signature Bank and Silicon Valley Bank) and the troubling news about Credit Suisse have you started to risk assess banks and funding institutions?
Banking failures aren’t new and while we hope this is not the beginning of a larger phenomenon, Kyriba customers continue to rely on the data and reporting in our platform to help them proactively manage counterparty risk – be it for operational cash, investments or access to liquidity. While our bank scorecard feature was very popular within the past month, the reality is that our entire platform is designed to answer the question “what if”.
“What-if” can refer to being cut off from cash and liquidity, if interest rates rise 100 bps, if the US Dollar drops by 2% or if key customers delay paying on time. It is important for finance teams to be in control over where their cash is, how they will access liquidity, and to maintain business continuity across any number of operating and risk scenarios – so they can proactively make strategic decisions to comfortably manage their liquidity before a crisis happens.
Some key takeaways for CFOs include:
- Real-time Liquidity Planning – End of day cash visibility is no longer sufficient and CFOs need the ability to see, protect and move cash in an instant.
- Reduce Vulnerability to Rising Interest Rates and FX Volatility – Finance leaders must quantify the impact of interest rates and currency volatility on their financial assets to make data-driven decisions to protect the value of their balance sheets, earnings and cash flow.
- Control of Bank Counterparty Exposure Limits – Bank meltdowns and takeovers have increased the need for on-demand counterparty reporting to ensure that changes in bank ownership or risk levels do not violate organizational risk policies. This needs to happen at machine speed to ensure that finance teams can react quickly in the event of a crisis.
What do you think is the future for tech and finance? What are possible future developments in this space?
The future of finance is about executing your data strategy. Every CFO has become, in effect, a Chief Data Officer and requires tools and processes to harness data to drive more informed and efficient decisions. AI, APIs and analytics are central to realizing that data strategy.
In fact, the recent rise of AI, including tools like ChatGPT, has changed the thinking around what ‘next’ looks like for CFOs. We have learned that generative AI tools are capable of more than writing text. These tools are becoming actionable.
AI, for instance, can already be used to improve the accuracy of cash forecasting and payments fraud detection. APIs unify data and create real-time processing, which AI then improves to predict, validate and authenticate to deliver better insight and achieve on-time compliance.
The next generation of AI will be infused into our workflows, progressing from offering insights as it does today to making financial decisions based on our guidance. AI will be executing our data strategy. While this has the potential to be threatening to the way finance teams work today, AI is the next step in automation and it is about harnessing the power of data to execute financial decisions quickly and with improved value.
And finally, is there anything else you would like to talk about that you think would be of interest to our readers?
I always like to remind CFOs that amongst all the distractions – internally and externally – the focus remains on optimizing the cash lifecycle. At Kyriba, we benchmark 2,000 companies to identify current practices and opportunities for improvement. And there is always room for improvement to improve the actionability of cash and liquidity reporting and to execute liquidity programs more efficiently – which can be both reducing the footprint and cost of managing the cash lifecycle but also introducing laser precision to treasury, payments and risk management operations. The need for efficiency only increases and our studies show that CFOs are open to large and small transformations to improve.
Thank you to Bob for the interview. He gives lots of useful insight into technological developments, and clearly explains the current paradigm for using AI and APIs to create actionable data in real-time. Also a special thanks to Christina Baviello, Senior Account Executive, Public Relations at KCSA Strategic Communications for setting up this interview.