Small Business Lending’s Data Deficit Filled by AI’s Real-World Insights – PYMNTS.com

The promise of artificial intelligence is that, along with machine learning, it can solve real-world problems and change business for the better.
Hicham Oudghiri, CEO of Enigma Technologies, said small business lending can be transformed with the aid of those advanced technologies — but only if data, and in particular, the right data, is harnessed effectively.
As he told Karen Webster, there’s been a sea change within financial services across the spectrum, but especially in lending. Clients used to come into the bank branch, sit down with managers and client-facing professionals, and engage in frank discussions about how business was going — and where it was headed.
Fast-forward to the pandemic and to the post-pandemic age, and the lender-client connection is done over the mobile device. The key information about the borrower is gleaned through the phone connected to the bank account.
For the lenders, he said, it’s become tougher to navigate through distorted data and the trends that might mask true business performance and attractiveness as borrowers. The pandemic and stimulus payments padded consumers’ bank accounts and kept them spending, which in turn boosted small- to medium-sized business’ fortunes. Now things are a lot more uncertain, and some SMBs are getting hit harder than ever, while others are thriving.
For the financial institutions primed to help these firms with lines of credit, seed capital or working capital loans, insight — and more specifically, actionable insight — can be gleaned through the waves of data that accumulate in real time across platforms. The industry is huge, as much as $3 trillion, and the stakes are high. There’s been a wave of tech-driven FinTechs and relatively untested, less-sophisticated lenders who need an extra set of tools when it comes to underwriting.
“You want real-world insight rather than historical intuition,” he said.
The goal of the lender, even with advanced technologies in hand, he said, “is to turn insight into action and to understand the business, holistically, from the point of customer acquisition to various points along the customer lifecycle, where you can have a relationship that’s always expanding.”
That’s easier said than done, considering the fact that “small businesses are heterogenous” and throw off reams of wildly different data points, he said. A spa’s revenue and operating profile is vastly different than that of a small construction firm.
For the banks and for other, alternative lenders, it’s a given that there’s the desire to determine who’s credit worthy. There’s the inclination to lend to the segments and small businesses that are already known quantities, and maybe already have a relationship with the lender in place.
But the more forward-thinking lenders, he said, will also need to ask themselves an essential question as they branch out beyond first-party information.
“Are they good clients for us?” he asked. “Are they folks who are going to ‘upsell?’”
That comfort level can be established using the data points — tens of millions of them — catalogued by the likes of Enigma, which gives granular views of a business’ revenue on a recurring, monthly and daily basis, gleaned from a panel of credit card transactions.
“You get a sense of how the business is performing in the real world,” said Oudghiri.
The data, he said, can help lenders fine-tune their go-to-market efforts as they improve their “funnel” of conversions and risk management and reduce the costs incurred at the front end of the lending process. The data also can help determine whether servicing the loan over time will be cost-effective or not.
In a nod to how data can help FinTechs pivot to cover SMB needs, Enigma has an affiliate company, Prime, which “plugs the gap” between merchant marketplaces that want to offer lending programs but need data-rich insights tied to the point-of-sale activity.
Looking at the swipe data can help create a “half-operational, half-financial” setup, he said, where companies can fine-tune their day-to-day operations to run more efficiently (he likened it to a “virtual COO” model).
As he told Webster of the intersection between lending, AI and ML: “Supercharging small business, making it easier to understand their growth potentials, their true risk — it’s going to be a very exciting time.”
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