Blog

What has been the secret to Jifiti’s success and longevity in an extremely competitive space? “I think we have known how to reinvent ourselves over the years, and in many ways evolve,” explains Yaacov Martin, co-founder and CEO.

For the white-label lending technology provider, founded in 2012, this has involved a two-pronged process; on the one hand, finding standalone functions for the latest cutting-edge technology and then, once that works, integrating it into the rest of the stack, before finding what Martin calls ‘places where we can layer that innovation’.

AI is a very good example of this. “There is, almost, just a separate initiative that has to do with the gen AI, and on the other hand the incorporation of AI tools within both our product features, as well as our product development, and that is, I think, a balance,” says Martin. “If we were to start over again every six months when the hottest new technology is on the scene, we wouldn’t really get anywhere.”

For embedded finance, the benefit of a provider like Jifiti to banks and financial institutions becomes evident when looking at the challenges they face. The origination journeys on Jifiti’s platform help with accessibility on the one hand, and also take the underlying financial product – be it an instalment loan or revolving line of credit, be it B2B or B2C – into account.

“What we found is that, mostly, banks and financial institutions could be experts when it comes to underwriting, [but] they are not necessarily experts in terms of digital accessibility and technical orchestration, and that’s the value that we bring them here,” explains Martin.

The second challenge, with a nod to AI, is in the ability of the bank or lender to digitally ‘decision’ and underwrite in real-time. Institutions will often have home-grown components and gaps that need to be bridged, either with Jifiti technology or third-party solutions. Jifiti’s orchestration layer ties it all together, with approximately 30 third parties plugged into it, ranging from KYC/KYB, to AML, to even decisioning engines.

“We understood that if we were to wait for our banks to onboard a vendor for every single one of these situations, even according to our recommendation, it would become cumbersome,” notes Martin. “It would kill the deal; it would lengthen the go-to-market process. It would make it much, much more expensive.”

The aforementioned evolutionary ability is going to prove especially vital when the full potential of agentic AI comes through. A study from Forrester and AWS Marketplace published in September explored, among other things, the impact of what it called ‘hyper-personalised financial guidance’. 70% of respondents ‘anticipate using agentic AI to deliver tailored customer experiences and financial advice that was previously available only to high-net-worth individuals’, the study found.

In the same month, Martin wrote about the subject of agentic lending in a blog, positing that, pretty soon, if your loan isn’t optimised for AI agents, it ‘might as well not exist.’ “For the first time in centuries, being a reputable, experienced lender isn’t enough,” he added.

While one company in the Forrester research claimed that they already have 60 agentic agents in production today, with another 200 to arrive by 2026, Martin forecasts that the full adoption of agentic AI for financial services will be seen in around four years. He asserts that banks need to be ready for change – and compares it to the early days of search. If you weren’t indexed, you were nowhere.

“The only limitation from our perspective today is a regulatory one,” says Martin. “What we understand is that the journeys we built today may be needed, but they no longer will be exclusive. But what’s more important is that the banks are clients. If their systems are not able to communicate with these agents, are not able to respond to these agents in real-time, they will lose market share very, very fast.

“That’s why we are starting to work very, very hard with our bank partners – [they] now understand that they still need to automate their stack for underwriting,” Martin adds. “It’s become more critical than ever.”

Can institutions who have already lost ground in this race recover? “I think they have to work fast and they have to work now – and I think one of the things they have to do is no longer accept corporate banking timelines,” says Martin.

“I know for a fact that [for] some of the very smart execs, what keeps them up at night is not only whether or not their people are utilising AI in order to increase efficiencies, but the real worry is the worry of agentic AI, that later on, almost dissolves that loyal customer base that they have been banking on for decades” he adds. “That’s what they should be planning for; in my opinion, this is where they should be placing most of their chips.

“It’s not too late, but it will be if they don’t get working.”

Martin is speaking at Fintech Connect on a session titled ‘How embedded finance is reshaping business operations’, and he is keen to emphasise the impact of agentic AI, calling it ‘embedded lending on steroids.’

“We have to understand that, once upon a time, if a small business was planning its inventory, it took weeks,” he says. “Today, [it] is happening in a very short space [of time] and a very limited placement. That means all of those calculations can be made – and should be made – on the checkout page.

“The existence of finance solutions on that page are absolutely critical, and the matching of the financial solution with the type of transaction at hand is critical, and the ability for businesses to move fast, make decisions, leverage themselves, is all happening in a very short and small window.”