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Home»Finance»When AI Meets Alternative Data: How Fintech is Rewriting the Rules of Credit Risk
Finance

When AI Meets Alternative Data: How Fintech is Rewriting the Rules of Credit Risk

Michael JenningsBy Michael JenningsJun 4, 2025Updated:Jun 4, 2025No Comments6 Mins Read

Imagine borrowing a loan and being judged not on previous failures (or absence of long-term financial history) but on how responsibly you get through day-to-day life. What if punctual rent payments or even your smartphone usage told your financial story?

How Fintech is Rewriting the Rules of Credit Risk

That’s the sound of the new fintech disruptors. They’re using AI and data outside of the old normal to flip credit risk scoring on its head. The old gatekeepers (like the inflexible FICO score) are starting to lose their grip on it. And they should. This is about making credit available. To the billions who’ve been excluded or misjudged for far too long.

Let’s get into why traditional credit scores are no longer enough and how AI is bringing stale risk models back to life.

Contents hide
1 The Credit Score’s Blind Spots
2 AI + Alt Data = A New Type of Credit Vision
3 The Proof Is in the Numbers
4 A More Inclusive Future
5 Human-AI Collaboration
6 A New Chapter in Credit

The Credit Score’s Blind Spots

Credit scores have been the financial world’s crystal ball for decades. But as it turns out, that ball is a pretty foggy one for millions. Traditional credit equations rely almost solely on your credit use history. Did you have a credit card, a loan, and how did you treat them? If the answer is “I never had any,” then you don’t exist to the system.

Globally, it’s a gigantic problem. 1.5 billion people in developing economies are shut out of formal credit. All simply because they’ve never been included before. Even in America, 45 million adults (almost 1 in 5) “credit invisible.” They could be young adults, new immigrants, or low-income people who pay every bill on time but don’t have a formal “score” to their name.

As one fintech expert neatly put it: “Your credit score only considers your credit usage. It doesn’t consider your assets, your income, or the rest of your financial picture.” In other words, it’s a snapshot – oftentimes outdated, blurry, and incomplete.

What it lacks: regular rent payments, stable income sources, punctual bills for utilities, or a stable cash flow – all signs that a person is a great borrower. The irony? Most individuals who have perfect financial habits are classified as “risky”. All for the very reason that traditional systems cannot see the whole picture.

The Credit Score's Blind Spots

AI + Alt Data = A New Type of Credit Vision

There’a solution: a system that not only looks at your past credit history but also eavesdrops on how you spend money. That is where AI and alternative data come in.

Alternative data is anything outside of the typical credit bureau report:

  • rent payments, 
  • mobile payments, 
  • e-commerce purchases, 
  • employment, 
  • income history. 

Even phone use patterns or social media utilization complete the picture. Some lenders are eyeing psychometric surveys or satellite photos of agricultural land to judge asset-backed loans. It’s unconventional but more accurate.

But how do you make sense of all this data? Step in, AI.

AI-powered fintech software is able to consider hundreds (even thousands) of bits of information in seconds. They spot patterns that humans never would. AI underwriting is like looking at credit information with a microscope compared to static 5-20 variable old models.

It can spot that the income of a gig worker isn’t contradictory – it’s cyclical. Or that someone who is always reloading their phone plan might be solvent.

AI is capable of interpreting unstructured data. Text messages and app activity – natural language processing and computer vision analyse it all. It’s a question of converting raw noise into predictive signals.

And it’s not just smarter. It’s faster. One credit union saw over 60% of its loans approved in seconds using AI, compared to just 30% through conventional methods. That means quicker access to cash for borrowers and streamlined processes for lenders.

The Proof Is in the Numbers

This isn’t theory – this is reality. Here’s what is happening on the ground:

  • An American fintech company Upstart uses AI to evaluate over 1,000 points of data per applicant. Compared to traditional models, its AI approved 43% more borrowers with 53% fewer defaults. In CFPB tests, it approved 27% more borrowers at 16% lower average rates – for the same risk.
  • Zest AI helped the lenders increase approvals by 25% without rising defaults. Their models performed twice as well as average scores in assessing “middle-tier” credit customers.
  • Petal saw 30% less delinquency from customers scored on cash flow data compared with average credit histories.
  • Tala offers microloans based on data from smartphones working in emerging markets. It has a 92% repayment rate from over 4 million customers.

A More Inclusive Future

The emotional core of this change is that of financial inclusion, aside from metrics.

AI and alternative data don’t just approve more people. They approve the right people who were historically excluded. When Zest AI’s models replaced traditional ones, approval rates jumped 49% for Latino borrowers. They increased by 41% for Black applicants, and ~40% for women, without increasing credit risk.

Surveys indicate that 62% of financial institutions now employ alternative data to more effectively evaluate risk and reach underserved markets. The outcome? More individuals are accessing education, housing, business, or emergency loans. And many for the first time.

Human-AI Collaboration

AI won’t replace human judgment – it will enhance it.

We’re entering a world where credit scoring isn’t a static one-time decision but a living and breathing model. It updates in real time. Lenders could adjust credit lines monthly (or even daily) with open banking. Smart decisions are based on live financial behavior. AI will scan the trends, and humans will ensure ethics and consent.

With great power comes great responsibility. Bias and privacy are foremost among concerns. Lenders will have to be careful to prevent AI from perpetuating discrimination or abusing data. Understandably, regulators are keeping a close eye. But many fintechs are stepping up.

Zest AI, for example, builds fairness constraints into its models and emphasizes explainability. Others are investing in privacy technology and consumer education.

A New Chapter in Credit

The credit market is evolving from a black-and-white snapshot to a full-color movie of your financial past. Traditional scoring is giving way to a smarter, more advanced system. This system sees you – not just your debt history.

People who were once invisible to lenders are now being offered a chance to be seen – and trusted. And for fintechs, this is not just good business. It’s impactful.

The future of credit is not just data. It’s dignity.

Michael Jennings

    Michael wrote his first article for Digitaledge.org in 2015 and now calls himself a “tech cupid.” Proud owner of a weird collection of cocktail ingredients and rings, along with a fascination for AI and algorithms. He loves to write about devices that make our life easier and occasionally about movies. “Would love to witness the Zombie Apocalypse before I die.”- Michael

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