EP960: Unlocking the Power of AI in Working Capital Solutions

In this episode of The Big Interview, Raja Debnath, MD, and Chairperson of Veefin Group, discusses the evolving future of working capital management, where AI and automation are becoming central to financial stability. He highlights how Veefin is leading AI-driven risk control and multi-lender orchestration to transform liquidity management for MSMEs. He also shares key lessons from scaling Veefin across $30bn disbursements and 15+ diverse financial ecosystems, offering insights into legacy modernization, modular architecture, cloud adoption, and effective data strategies.
 
 With an eye on global expansion, Veefin is focused on deepening product innovation and forming strategic partnerships in emerging markets like Africa and Asia. Tune in to discover how AI is reshaping the landscape of working capital finance and driving growth across global financial ecosystems.

Transcript

SPEAKER_01 0:00

Welcome to uh the deep dive. Whether you are actively managing a global team, running a business of your own, or just completely fascinated by how money actually moves behind the scenes of the world economy, you are in exactly the right place today.

SPEAKER_00 0:14

Aaron Powell You really are, because we're looking at something that affects basically everything.

SPEAKER_01 0:18

Aaron Powell Right. Today is essentially your shortcut to understanding the hidden nervous system of global commerce, which is working capital. And more specifically, we're looking at how artificial intelligence is completely rewiring that nervous system from the inside out.

SPEAKER_00 0:32

It's um it really is the invisible engine of global trade. I mean, we rely on working capital constantly. Every single time a product hits a shelf or a service is delivered, that engine is running. But most of us never actually see how it operates.

SPEAKER_01 0:45

Yeah, we just expect the shelves to be full.

SPEAKER_00 0:46

Exactly. But today we are looking at how that engine is getting this massive structural upgrade.

SPEAKER_01 0:53

And our source material for this deep dive gives us an incredible look under the hood. We're exploring a highly revealing interview from the IBSI FinTech Journal. It's an October 2025 interview with Raja Debnath, the managing director and chairperson of VFIN Group, and it was conducted by assistant editor Puja Sharma.

SPEAKER_00 1:12

It's a fantastic piece.

SPEAKER_01 1:14

It really is. And you know, acknowledging that today is March 5th, 2026, looking back at this piece from late last year is just fascinating. It serves as this incredibly prescient roadmap for exactly the massive shifts we are watching play out in the financial sector right now.

SPEAKER_00 1:29

It provides the perfect vantage point, really, because that interview captures the exact moment when the theoretical ideas about AI in finance started turning into massive scalable realities for major institutions.

SPEAKER_01 1:41

Right. It stopped being just a white paper concept. But before we jump into the mechanics of those realities, I have to mention the striking visual that accompanies the article because it perfectly sets the tone for everything we're going to discuss today.

SPEAKER_00 1:52

Oh, the digital city image, yes.

SPEAKER_01 1:54

Yes. The artwork shows this glowing, futuristic digital cityscape. But this entire city is resting in the palm of a single human hand. And surrounding this city are these floating, interconnected icons. You have money bags, saving symbols, global trade charts, and banking institutions. It looks very sci-fi, but it perfectly symbolizes the digital first financial ecosystems we're about to explore.

SPEAKER_00 2:19

That image actually does a lot of heavy lifting. It immediately signals to the reader that we are no longer talking about dusty ledgers or isolated siloed banking software. We are talking about highly connected living digital environments that crucially still require careful human management.

SPEAKER_01 2:35

Which brings us directly to our mission for today's deep dive. We are going to demystify how AI is completely rewiring working capital. We are going to break down the exact strategies that massive financial institutions are using right now to balance blazing technological speed with responsible risk management.

SPEAKER_00 2:51

Because that is the tightrope everyone in the financial sector is walking today. The primary challenge is figuring out how to move capital faster than ever before without accidentally breaking the entire system.

SPEAKER_01 3:01

Okay, let's unpack this. In the interview, Roger Devnath makes a very bold statement right out of the gate. He argues that working capital management is no longer just about operational efficiency. He says it's fundamentally about financial stability and has become a board level priority where liquidity, resilience, and sustainability all converge.

SPEAKER_00 3:23

Yeah, that's a huge shift.

SPEAKER_01 3:24

So why is the boardroom suddenly so focused on what used to be essentially a back office plumbing job?

SPEAKER_00 3:31

What's fascinating here is how the global perspective has shifted purely out of necessity. For decades, as you said, working capital was just the plumbing. It was a basic math problem of making sure a company had enough cash on hand to pay the bills and keep the lights on this month.

SPEAKER_01 3:44

Just routine accounting.

SPEAKER_00 3:46

Right. But Debneth points out several massive shifts that have pushed this conversation straight up to the boardroom. The first major shift is the move toward digital first ecosystems. Chief financial officers and corporate treasurers are simply no longer tolerating fragmented tools.

SPEAKER_01 4:02

Because they can't afford to.

SPEAKER_00 4:03

Exactly. They are leaning heavily into unified platforms that embed AI, application programming interfaces, and automation into every single layer of the cash flow process.

SPEAKER_01 4:14

Right. Because if your systems can't talk to each other in real time, you are essentially flying blind in a very fast economy. So that digital consolidation makes total sense. But it doesn't really matter how good your software is if the actual supply chain snaps, which brings up another major shift he mentions regarding resilience.

SPEAKER_00 4:33

Yes, supply chain resilience has become an existential priority now. The global shocks we have all witnessed over the past few years proved that traditional financing models are incredibly fragile.

SPEAKER_01 4:43

They just break under pressure.

SPEAKER_00 4:44

They do. So businesses are now adopting financing structures that are deliberately designed to protect their suppliers across all tiers. Think about a massive automotive manufacturer. If a mid-sized supplier who makes a very specific crucial microchip goes under because they ran out of cash, the whole line stops. The entire multi-billion dollar production line grinds to a halt. Financing now has to ensure the continuity of cash flow for everyone involved in that chain, not just the giant corporation at the top.

SPEAKER_01 5:13

You can't just protect the top of the pyramid anymore. The whole thing collapses if you ignore the base. And I imagine to manage a massive web of suppliers like that, you need serious processing power, which leads to the shift where AI really fleses its muscles, which is data-driven agility.

SPEAKER_00 5:30

This is where we see the most profound operational change. Decisions are moving from being backward-looking to highly predictive. Historically, if a business needed capital, a bank would look at their past performance. Maybe three years of tax returns and historical audits to decide if they should lend to them.

SPEAKER_01 5:46

Looking in the rearview mirror to drive forward.

SPEAKER_00 5:48

Exactly. But now banks are investing heavily in AI credit models that analyze real-time data to predict future viability. They are looking at live inventory turnover, current market conditions, real-time cash flow. And the result of that shift, they are reducing turnaround times for credit decisions from weeks down to literally minutes.

SPEAKER_01 6:07

Going from weeks to minutes is a staggering operational leap. If you're a business owner trying to make payroll or secure raw materials for a sudden massive order, a three-week wait could kill your company. Minutes changes the entire dynamic of how you operate.

SPEAKER_00 6:21

It really does. And DevNath expects that predictive trend to just keep accelerating. But there is another shift driving the boardroom conversation. And it is how sustainability is being treated as a core strategy rather than just a public relations effort.

SPEAKER_01 6:36

ESG integration.

SPEAKER_00 6:37

Right. Working capital programs are now actively embedding environmental, social, and governance metrics into their actual lending structures. Financing terms are increasingly structured to directly reward suppliers who can demonstrate sustainable practices with better rates or faster access to cash.

SPEAKER_01 6:53

So sustainability and liquidity are fundamentally becoming two sides of the same coin. The greener your operations, the greener your cash flow. That is a massive paradigm shift.

SPEAKER_00 7:03

It absolutely is.

SPEAKER_01 7:04

But hearing all of this, especially the AI reducing complex credit decisions from weeks to minutes, it brings up a fairly concerning thought. The article tackles this head on with a fantastic quote. Debnuff says, speed without responsibility is a recipe for systemic risk. That's the core tension right there. So how are these massive banks deploying AI at this scale without accidentally driving the whole economy off a cliff?

SPEAKER_00 7:30

This raises an incredibly important question about trust in financial systems. If an AI hallucinates or misinterprets data at that speed, the cascading effects could be disastrous. VIFIN's approach to preventing this, as outlined in the interview, is built on four essential pillars that balance that blistering speed with highly responsible risk management.

SPEAKER_01 7:50

Okay, let's go through those.

SPEAKER_00 7:51

The first pillar is the deployment of advanced AI. They use models that scan millions of real-time transactions specifically to flag anomalies at the earliest possible stage. The goal is to respond to subtle threats or irregularities before they spiral into systemic risks.

SPEAKER_01 8:06

Okay, so the AI is acting like an incredibly fast, highly perceptive security guard, analyzing millions of data points a second to catch things a human reviewer would definitely miss.

SPEAKER_00 8:17

Exactly.

SPEAKER_01 8:18

But what happens when that AI flags something or outright denies a business a critical loan? Does anyone actually know why the computer made that specific decision?

SPEAKER_00 8:28

That is the exact problem the second pillar addresses, which is explainable AI. DevNeth is very clear that financial institutions cannot afford to rely on black box models where the decision-making logic is hidden inside a complex algorithm.

SPEAKER_01 8:42

Aaron Powell Right, where it just spits out a yes or no.

SPEAKER_00 8:44

Exactly. In an industry that is entirely built on regulatory trust, things like fairness, transparency, and accountability are non-negotiable. If a system denies a loan, you have to be able to explain to a regulator or to the client themselves the exact logical steps the AI took to reach that conclusion.

SPEAKER_01 9:01

So no one is allowed to just shrug and say, because the algorithm said so, that level of transparency seems crucial. How do they maintain that over time, though? Because markets and risks are constantly shifting.

SPEAKER_00 9:12

They manage that through the third pillar, continuous oversight. Even the most sophisticated explainable AI cannot just be deployed and forgotten. These systems rely on regular audits, rigorous stress tests, and multi-layered defense mechanisms. Fraud tactics evolve daily.

SPEAKER_01 9:29

And international regulatory requirements change constantly.

SPEAKER_00 9:32

Exactly. So the oversight has to be continuous so the system doesn't become outdated and vulnerable. But the fourth pillar is arguably the most crucial piece of the entire puzzle, and it is the human-in-the-loop approach.

SPEAKER_01 9:43

Aaron Powell Which brings us right back to that artwork of the giant human hand holding the digital city.

SPEAKER_00 9:48

Aaron Powell Precisely. The philosophy here is that technology should not be making the ultimate critical calls in total isolation. Machines are unparalleled at processing massive data sets and identifying complex mathematical patterns, but they do not understand human nuance.

SPEAKER_01 10:04

Give me an example of that.

SPEAKER_00 10:05

Well, a machine might see a sudden drop in a supplier's output and flag them as a massive credit risk. But a human operator can look at that same data and see that the drop is due to a temporary, localized, natural disaster that the supplier is already recovering from. Humans bring judgment, broader context, and ethical reasoning to the table.

SPEAKER_01 10:26

The core thesis in the article is so powerful on this point. It says the future of finance isn't about humans versus machines, but about building systems where each strengthens the other. AI provides the raw precision and the incredible speed, but humans deliver the interpretation and bear the ultimate accountability.

SPEAKER_00 10:44

And that deliberate synergy is what creates long-term stability, which is essential as the sheer volume of digital transactions continues to surge globally.

SPEAKER_01 10:52

Here's where it gets really interesting, though, because all this theory sounds amazing. AI credit models, unified platforms, real-time oversight. But for anyone who has ever worked in a large legacy corporation, you know that existing IT infrastructure is usually ancient, highly fragile, and frankly, terrifying to touch.

SPEAKER_00 11:10

Oh, absolutely terrifying.

SPEAKER_01 11:12

Upgrading the core systems of a massive established bank sounds like an absolute nightmare. How do you modernize legacy banking infrastructure without breaking the very systems that process millions of dollars a day?

SPEAKER_00 11:27

If we connect this to the broader reality of corporate IT, the historical approach to modernization was often rip and replace. A bank would try to tear out the old system entirely and drop a massive new one in its place. It was incredibly disruptive and very risky.

SPEAKER_01 11:42

I can imagine.

SPEAKER_00 11:43

Deb Nath explains that true legacy modernization has entirely moved away from that model. Instead, the playbook is all about building agile, composable platforms.

SPEAKER_01 11:53

Composable, meaning you aren't dealing with a monolith, but something you can put together piece by piece.

SPEAKER_00 11:58

Exactly like that. Think of a legacy banking system like a giant solid block of concrete. If you want to change the internal plumbing, you have to smash the whole block. Composable platforms are more like Lego bricks. You use modular architectures so you can upgrade the system piece by piece.

SPEAKER_01 12:12

Okay, I see.

SPEAKER_00 12:13

You can swap out the risk assessment module or upgrade the loan approval module without having to tear down the entire banking infrastructure.

SPEAKER_01 12:20

That modular approach has to be a massive relief for chief information officers who are usually terrified of a single point of failure crashing the whole bank.

SPEAKER_00 12:29

It reduces the risk profile significantly. And the next major part of their modernization playbook is the aggressive adoption of cloud and software as a service model. Deb Nath points out a staggering reality of legacy systems. Right now, routine maintenance eats up roughly 20 to 30 percent of an institution's IT budget.

SPEAKER_01 12:48

Just keeping the lights on.

SPEAKER_00 12:49

Just keeping the servers running. By moving infrastructure to the cloud, banks can redirect that massive chunk of capital away from maintenance and put it toward actual product innovation.

SPEAKER_01 12:59

Reclaiming 30% of a massive financial institution's IT budget. When you multiply that across the industry, that is billions of dollars globally being freed up to build better tools.

SPEAKER_00 13:10

It's a massive unlock of capital. But even with cloud infrastructure, you still have to move the historical data, which is highly sensitive. So the third part of the playbook involves a very meticulous data migration strategy. This means running small-scale pilots and executing phased rollouts to essentially de-risk the change. You never flip a single massive switch. You turn the dial slowly to ensure stability at every step.

SPEAKER_01 13:37

And what ensures that all this new technology actually gets used effectively once it's implemented?

SPEAKER_00 13:42

That is the final and often most overlooked part of the playbook, which is broad stakeholder buy-in. DebNath emphasizes that modernization almost always fails when it is treated solely as an isolated tech project. It cannot be confined to the IT department. Trevor Burrus, Jr.

SPEAKER_01 13:57

Right. Everyone has to be on board.

SPEAKER_00 13:58

It requires business-wide transformation with total alignment across all leadership. The technology investments have to be directly tied to solving actual business problems and accelerating growth. Otherwise, it is just expensive new software that no one wants to use.

SPEAKER_01 14:12

So what does this all mean? We have talked a lot about the giant financial institutions, the complex AI models, and the massive system upgrades. But how does this actually hit the ground? How does all this high-level infrastructure affect mid-sized suppliers and local manufacturers, the smaller businesses that actually keep the physical economy moving?

SPEAKER_00 14:33

For those businesses, the ultimate pain point has almost always been liquidity, simply getting access to affordable cash exactly when they need it to fill an order or pay their staff. And Debneth introduces what he views as the ultimate game changer for this specific problem, which is multi-lender orchestration.

SPEAKER_01 14:51

Multilender orchestration. That sounds like a very intense financial term. What does it actually look like in practice?

SPEAKER_00 14:57

It's essentially a unified digital marketplace. A perfect example of this in action is a platform in India called PSB Exchange, which VIFIN built and currently manages. Traditionally, a small or medium-sized business would be entirely dependent on a single bank for a loan. They would have to accept whatever terms, interest rates, and timelines that specific bank dictated?

SPEAKER_01 15:17

Take it or leave it.

SPEAKER_00 15:18

Exactly. Multilender orchestration changes that dynamic by giving the business access to multiple lenders simultaneously on one single platform.

SPEAKER_01 15:27

Wait, but why would massive banks voluntarily join a platform that forces them to compete openly? Doesn't that risk driving them into a price war over small business loans and hurting their profit margins?

SPEAKER_00 15:40

It's a great question, but the banks actually see massive benefits that outweigh that risk. First, it allows for shared risk. Lenders can spread their capital exposure across a much wider variety of smaller loans, which builds broad resilience for the bank's portfolio. Second, the platform provides incredible operational efficiency. Because these platforms utilize a unified digital layer for all the data and verification, it essentially eliminates the traditional mountains of underwriting paperwork.

SPEAKER_01 16:07

Which means the bank spends far less time and money processing the loan in the first place.

SPEAKER_00 16:12

Exactly. The institutional capital is deployed much more efficiently. And for the small business, the benefits are life-changing. Because lenders are competing on the platform, that competition naturally translates into better pricing and far more flexible loan terms. Plus, because the paperwork is digitized and unified, cash disbursements happen drastically faster. It fundamentally democratizes access to liquidity.

SPEAKER_01 16:37

Which, for a mid-sized manufacturer, could literally be the difference between surviving a rough quarter or having to close their doors entirely. And VFIN isn't just testing this concept out in a small theoretical sandbox. When you look at the sheer scale of what they have achieved, they have processed over$30 billion in disbursements across more than 15 diverse financial ecosystems. You simply do not move$30 billion globally without learning some very hard lessons about what actually works.

SPEAKER_00 17:03

Absolutely not. Scaling a financial platform to that magnitude is an intense crucible. Deb Nath synthesizes their massive growth into a core philosophy rather than just a list of technical upgrades. For instance, they learn very quickly that a one-size-fits-all approach is guaranteed to fail in global finance.

SPEAKER_01 17:22

It has to be tailored.

SPEAKER_00 17:23

Yes, every single market they enter requires deep contextualization. The regulatory environments, the business cultures, the specific pain points, they all differ wildly from region to region. Their ability to adapt their core technology to meet local nuanced needs has been the main driver of their global adoption.

SPEAKER_01 17:43

That makes total sense. You can't just take a banking platform designed for a Western market, drop it into an emerging economy, and expect it to hum perfectly on day one.

SPEAKER_00 17:51

It never works. Another major lesson was the absolute necessity of seamless integration. When VFIN approaches a major bank, they know that the bank does not want to hire 10 different software vendors to patch a solution together. Banks want one highly trusted partner whose platform can plug directly into their existing core banking systems and enterprise resource planning software effortlessly.

SPEAKER_01 18:12

Right. If you cause friction for the IT department, they'll just pass on you.

SPEAKER_00 18:15

If you can't be that deeply integrated, seamless solution, you won't survive the procurement process.

SPEAKER_01 18:20

Do they face challenges keeping up with the legal side of expanding that fast?

SPEAKER_00 18:24

Compliance was perhaps their steepest learning curve, and it is now a non-negotiable pillar of their architecture. Success across multiple distinct geographies only happens when you build regulatory agility right into the absolute core of the software. When financial laws change in a specific country, the platform has to be able to pivot and comply immediately without breaking the wider system.

SPEAKER_01 18:47

So it sounds like VFIN realized that you can't build a massive global platform by just throwing brilliant tech at a wall. It requires deep localized listening. How did that focus on customer centricity actually change the code they were writing or the products they were building?

SPEAKER_00 19:01

It shaped everything they do. Listening to clients isn't a corporate buzzword for them. It dictates their actual feature development. In fact, their entire strategy of building broad ecosystem platforms like PSB Exchange was born directly from listening to what clients were actually struggling with on the ground. And that ties into their final core lesson, which is the commitment to never stop iterating.

SPEAKER_01 19:24

They're constantly evolving.

SPEAKER_00 19:25

DebNath points out that the complex product they are selling today is vastly ahead of the original platform they launched seven years ago. They are constantly challenging their own assumptions to rethink what is possible.

SPEAKER_01 19:38

Which naturally leads to the biggest question: what is possible next? Where are they taking this platform now that they have hit that$30 billion milestone?

SPEAKER_00 19:46

VFIN's next chapter is highly focused on achieving global scale with deep product penetration. They are expanding their innovation beyond just traditional supply chain finance. They are moving very deeply into broader trade finance and complex cash management.

SPEAKER_01 20:01

For those who might not live in the corporate treasury world, what does expanding into broader trade finance actually mean for the businesses using the platform?

SPEAKER_00 20:10

It means they aren't just helping a business pay its immediate suppliers anymore. They are using their AI to manage the entire lifespan of a company's cash pool. This includes handling complex global shipping guarantees, managing cross-border letters of credit, and optimizing daily liquid assets. They are embedding their predictive AI into the very core of how a global business manages its total financial health.

SPEAKER_01 20:37

And what about that multi-lender orchestration model, the marketplace concept where banks compete for the loans? Is that staying centralized in India where it was proven?

SPEAKER_00 20:45

Aaron Powell Not at all. Exporting that model is their second major anchor for growth. They are heavily focused on ecosystem partnerships, and they are taking that proven multi-lender marketplace model and launching it in five new countries over the next nine months.

SPEAKER_01 20:59

Launching a highly regulated financial marketplace in five new countries in nine months is an incredibly aggressive rollout schedule. Where geographically are they focusing that energy?

SPEAKER_00 21:10

That is the third anchor of their strategy. They have established Nigeria as their primary African hub with very concrete plans for more countries in that region to follow shortly. Their primary growth engines over the next few years are going to be the emerging markets across Asia, Africa, and the Middle East.

SPEAKER_01 21:26

So they're targeting areas experiencing rapid growth.

SPEAKER_00 21:29

Yes. These are regions where digital transformation is leapfrogging legacy systems entirely. Meanwhile, they expect highly developed Western markets will increasingly look to them for very niche, highly specialized working capital solutions. Their ultimate stated goal is to become the global platform of choice for any institution thinking seriously about working capital finance.

SPEAKER_01 22:00

To fit together globally. We have covered a massive amount of ground today. We started by looking at how working capital has completely transformed from a routine, back office plumbing job into a high-speed, AI-driven global ecosystem that commands boardroom attention.

SPEAKER_00 22:15

It's a completely different world now.

SPEAKER_01 22:17

We explored exactly how major financial institutions are walking the tightrope of balancing the blistering speed of predictive AI with the absolute essential need for human judgment and continuous oversight.

SPEAKER_00 22:29

And we dug into the reality of how legacy banking systems are being modernized piece by piece, unlocking billions and tied up capital. That capital is then being routed through highly efficient, multi-lender platforms to actually help mid-sized businesses thrive and access the liquidity they need. I always believe that knowledge is most valuable when it is actively applied to how we view the world.

SPEAKER_01 22:50

Very true.

SPEAKER_00 22:51

In an environment where we are constantly overloaded with fragmented daily information, understanding these massive systemic shifts in global finance helps you see the broader context. It gives you the lens to understand exactly how modern businesses survive, compete, and ultimately grow in a digital first world.

SPEAKER_01 23:10

Machines bring speed, but only humans bring the judgment. That core philosophy from the article is going to stay with me for a long time. It feels like the perfect summary of exactly where the future of finance is heading. But before we wrap up this deep dive, I want to leave you with a final provocative thought. We talked earlier about how sustainability and liquidity are fundamentally becoming two sides of the same coin. The source noted that financy terms will increasingly and directly reward suppliers who can actively demonstrate sustainable practices.

SPEAKER_00 23:38

It's a massive shift in incentives.

SPEAKER_01 23:40

So think about the long-term implications of that. If complex AI systems are increasingly tying a business's access to its daily lifeblood cash flow directly to its environmental, social, and governance goals, will the future of business survival depend more on a company's environmental footprint than their actual traditional profit margins? If your access to operational cash gets cut off because an algorithm determines you aren't green enough to offset systemic risk, your historical profits won't matter at all. It is definitely something to chew on the next time you see a massive corporation updating its sustainability goals. It might not just be a public relations exercise. It might quite literally be their lifeline to their next critical loan. Thank you so much for joining us on this deep dive. Keep questioning the systems around you, and as always, stay insanely curious.