EXCLUSIVE: “Keeping a finger on the pulse” – Haytham Kaddoura, SmartStream in ‘The Fintech Magazine’

As CEO of a technology solutions company that works with the majority of the world’s top 100 banks, Haytham Kaddoura has an insider’s view on how recent events in the US are impacting cash and capital management. Here, he explains how SmartStream AI can play a significant role in improving it

THE FINTECH MAGAZINE: The banking shocks of early 2023 have put banks’ liquidity management practices firmly in the regulatory spotlight. What have you observed as a result of that?

HAYTHAM KADDOURA: The situation with the US banks created a specific momentum for us to show, particularly in regard to cash management and stress testing, how our solutions could help clients avoid situations just like that. We’d always found stress testing to be much more of a priority issue in Asian and European markets than with some of of their American counterparts. After the crashes of the three institutions [Silicon Valley Bank, Signature Bank and First Republic Bank], people were taking a much more serious look at it. It’s definitely moved up the seniority scale, in terms of who is looking at this, who wants to make sure that their institutions are not exposed. It’s been good for us, highlighting how institutions could better manage their risk.

TFM: And how can those institutions better manage risk?

HK: We’ve been saying it for ages, but you simply cannot rely on data that’s a day old, or a few hours old. I mean, if you are a senior executive, a CEO, or a stakeholder today at a bank, you need to understand where your risk factors are to the second. You need to be much more reactive to market situations and conditions. The term ’keeping your finger on the pulse’ has taken on a much more significant meaning.

TFM: SmartStream recently released its latest version of SmartStream Air Exception Management, using your flagship AI technology, to onboard cash balances faster and more accurately in an effort to improve cash reconciliations. Why is that particularly important now?

HK: As a result of some of the new regulations coming into the space to do with capital requirements and capital adequacy, some institutions will need to find ways to increase their capital base by as much as 20 per cent. That’s a massive amount of money that then cannot really be deployed. It’s not money that banks lend out. It’s going to be sitting there, and financial institutions are going to have to start covering that revenue opportunity for their shareholders.

“If you’re a senior executive, a CEO or a stakeholder today at a bank, you need to understand where your risk factors are to the second. You need to be much more reactive to market situations and conditions”

They need to ensure they’re enhancing their cost structures, and enhancing their revenue structure. That necessitates an instantaneous understanding of their cash situation, and how and where their capital is deployed, making sure that it comes in when it’s supposed to come in, etc.With the current cost of capital and interest rates, institutions cannot afford to take in a major deposit and not do anything with it until the morning. It’s a costly proposition for any institution today.

So I think we are moving to the millisecond environment. Increasingly, institutions need to be super-efficient in how their assets are deployed. If a major payment comes in, or if a payment is delayed, for example, what are the correct measures taken within an institution? This should be way, way up on a treasurer’s, or even a CEO’s, agenda today. The premise of AI is to make things much easier, much more simplistic, so we can move the human element to a more strategic, and intellectual role… doing things that only humans can do. And Air has been phenomenal at applying AI to understanding cashflow.

TFM: Financial institutions are increasingly looking to AI to reduce cost and improve efficiency, but all of these things are dependent on predictive modelling. You need to know exactly where you are before you make any decisions, right?

HK: Exactly – it means having the inherent ability within the organisation to analyse thousands and thousands of datapoints as the markets move across the globe. This drive towards a faster ability to process ever-increasing volumes of data has been a priority in the last two years, but now it’s moving quite significantly higher. It’s really quantum leaps, as opposed to a natural growth. We are processing not just thousands, but hundreds of millions of records of data for clients in minutes.

TFM: The reason AI models like ChatGPT and Midjourney have been so successful, in part, is because they’re so accessible – it’s very easy for someone to log in and start using them. Are business applications of AI going the same way?

HK: The financial industry is increasingly moving towards low-code/no-code. A lot of the discussion we’ve had with our clients are about wanting to move control away from their tech departments and closer to their business user community – again, in an effort to expedite the decision-making process. Air is really a low-code/no-code solution. Users are quite comfortable running that, and analysing the data that comes through from it. The flexibility that it gives institutions in looking at hundreds of fields of data, and letting them narrow down and filter what they need, is second to none in our industry today.

We are also working with corporates and with players in the insurance sector on big data initiatives. So it’s not only banks that are looking at how they can best use the data they have.

TFM: There have been some dramatic things happening in financial services over the past year. Looking over the next six to 12 months, what challenges will be keeping people in the industry up at night, do you think? And what will they be able to solve?

HK: I think there will definitely be continued focus on better risk management, the way regulators are re-examining foundation institutions – institutions that we have, as a community, thought are too big to fail.They are now making sure that modern infrastructure requirements are in place, to ensure that institutions don’t get trapped by legacy infrastructure and data moving very slowly. So, the dynamics are moving, both organisationally and technically, to ensure that risks are better understood, and that the institutions themselves are much more responsive to changing market situations.

For us, as a player in the sector, it means we’ll definitely have even greater focus on AI, stress testing, on giving our clients a better understanding of their inherent operational efficiencies and readiness to mitigate some of their operational risks.There are a lot of areas that we are playing in that will address market needs in the coming 18 to 24 months.

This article was published in The Fintech Magazine Issue 29, Page 16-17