The recent news that the average U.S. FICO score has fallen year over year for the first time in over a decade has understandably sparked concern. According to the latest data, more Americans are missing payments and slipping into lower credit tiers, a worrying signal for lenders and consumers alike.
But focusing on this decline risks missing the bigger, more urgent story. The problem isn’t simply that some people’s scores are going down, it’s that tens of millions of adults in the U.S. are "credit invisible" or have "thin" credit files locked out of the financial system not because they are risky, but because the system was never designed to see them. Young adults, recent immigrants, gig workers, and cash-preferring households are invisible to the traditional scoring model, even when they consistently pay rent, utilities, or other recurring bills on time.
If we want to build a healthier, more resilient credit ecosystem, the goal shouldn’t be to shore up a rigid, exclusionary scoring system; it should be to finally bring invisible consumers into it.
The conventional wisdom has long held that the narrowness of traditional underwriting standards is the biggest part of the problem. But a deeper analysis reveals a more fundamental flaw: the high cost of the lending process itself. The operational and administrative costs of acquiring and servicing a customer are so significant that banks must be highly selective, only taking on customers who are guaranteed to be profitable. The expense of a loan officer's time, the overhead of manual reviews, and the simple inefficiencies of paperwork all add up, making it unprofitable for financial institutions to lend to anything but the most pristine credit profiles.
It's a lesson I learned the hard way over my career: the cost of a loan often dictates who gets to apply for one, and it's a structural barrier we've never been able to dismantle. This high-cost structure created a vicious cycle. The need to guarantee profitability drove a reliance on narrow credit standards, which in turn forced lenders to be overly conservative, rejecting countless applicants who would have been perfectly reliable borrowers. It is a system that works for the few at the expense of the many, and one that has remained stubbornly resistant to change. The fintech community has tried to chip away at this problem for years, but the cost barrier has always been a formidable wall.
The promise of the internet and then mobile was to democratize credit. They offered a more efficient, accessible, and inclusive experience. And while these technologies did make the process more accessible, the promise of democratization ultimately fell short. The industry replaced paper forms with digital ones and a branch visit with a web portal.
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Poor digital customer experience drove more multi-channel interactions, increasing costs for the bank, frustrating would be customers, and failing to address the root causes of the friction. The experience became transactional, not human. During the mobile revolution, we believed that putting a bank in every pocket would solve everything. At Moven, we were focused on using technology to drive financial wellness, but what we discovered was that a cool app alone isn’t enough. Technology and digital design limitations at the time forced us to do the best we could: build a digital facsimile of an analog process.
The digital user experience was (and still largely is) highly impersonal. It places the burden of navigation and decision-making on the customer, and when they inevitably get confused or need help, the experience breaks down. Customers who need human support to complete complex applications or to make the right financial choices are left with impersonal call centers or slow email chains. This ineffective client experience is a lose-lose: it's a poor experience for the customer, and it means a stunning 68% of online credit applications are abandoned before completion, a rate that has been steadily increasing.
This is where AI enters the narrative, and why it is different this time. The solution to this paradox is not a more polished digital form, but a new kind of intelligence altogether. Artificial intelligence is now poised to move the financial industry from an exclusive club to a genuinely open marketplace. Its power lies in its ability to directly address the two core problems of the legacy system: by enabling the use of richer, alternative data for underwriting and by creating a truly "human" and low-cost client experience. This is the new engine that finally allows us to build the human-centered, low-cost experience we've been chasing for decades.
Instead of relying solely on a FICO score, AI-powered systems can use alternative data to build a more comprehensive and accurate picture of a borrower's financial health. This includes a wealth of information previously ignored, from a customer's on-time utility and rent payments to their consistent cash flow and savings habits. This isn’t about making riskier loans; it’s about knowing customers more deeply; it’s about making smarter, more informed decisions by making visible the millions of "invisible" consumers and giving them a fair shot at credit. We can finally realize that decades-long vision of a fairer, more accessible system.
AI also allows us to provide a radically different customer experience. One that customers don’t abandon and perhaps even find enjoyable and valuable. We can use AI-powered mobile platforms to give customers a human-centered experience, at scale. Imagine an applicant completing a loan application on their phone but it’s not a transactional, sterile experience.
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It’s like working with a personal coach. The AI can ingest, analyze, and respond to customer questions & concerns in real time, reducing the multi-channel handoffs that increase costs for the bank and almost always frustrate the customer.
I believe this is the biggest market opportunity the industry has ever seen. AI-powered lending can unlock specific, high-growth business opportunities by profitably serving distinct customer segments that the legacy system has ignored.
First, there is the mass affluent, a segment that often has complex financial needs but is overlooked by private banking. AI can deliver a concierge-like experience at a fraction of the cost, proactively suggesting home equity loans or tax-efficient lines of credit based on a client’s portfolio. Then there is the massive opportunity presented by the underbanked, a population of over 19 million U.S. households that has been historically underserved. For this group, AI is a force for inclusion, offering credit for the first time by using alternative data and a seamless, mobile-first experience. Because the cost-to-serve is so low, a bank can profitably offer micro-loans and small lines of credit. Finally, there are small businesses, the engine of the economy, who often face the longest and most cumbersome lending processes. An AI system can analyze a business's real-time cash flow to make a decision in minutes rather than weeks. This also applies to out-of-footprint customers where a bank can expand its market reach without the need for physical branch infrastructure, unlocking significant loan volume in new geographies. From my experience in in the space, I believe, a bank could acquire up to 20% of new loan volume from outside its traditional operating territory through a digital-first strategy, a market valued in the tens of billions of dollars. From my seat, this isn't just a technology trend; it's the culmination of everything we've learned over the last 30 years.
The democratization of lending is not a utopian ideal; it is an economic and technological imperative. By moving past outdated underwriting models and embracing a mobile-first, AI-driven experience, financial institutions can unlock a new era of growth and inclusion. For consumers and businesses, this means a fairer chance at the capital they need to build their futures. For the lending industry, it means moving from a limited, risk-averse model to one that is more dynamic, efficient, and genuinely accessible to everyone. The path forward is clear.
The recent news that the average U.S. FICO score has fallen year over year for the first time in over a decade has understandably sparked concern. According to the latest data, more Americans are missing payments and slipping into lower credit tiers, a worrying signal for lenders and consumers alike.
But focusing on this decline risks missing the bigger, more urgent story. The problem isn’t simply that some people’s scores are going down, it’s that tens of millions of adults in the U.S. are "credit invisible" or have "thin" credit files locked out of the financial system not because they are risky, but because the system was never designed to see them. Young adults, recent immigrants, gig workers, and cash-preferring households are invisible to the traditional scoring model, even when they consistently pay rent, utilities, or other recurring bills on time.
If we want to build a healthier, more resilient credit ecosystem, the goal shouldn’t be to shore up a rigid, exclusionary scoring system; it should be to finally bring invisible consumers into it.
The conventional wisdom has long held that the narrowness of traditional underwriting standards is the biggest part of the problem. But a deeper analysis reveals a more fundamental flaw: the high cost of the lending process itself. The operational and administrative costs of acquiring and servicing a customer are so significant that banks must be highly selective, only taking on customers who are guaranteed to be profitable. The expense of a loan officer's time, the overhead of manual reviews, and the simple inefficiencies of paperwork all add up, making it unprofitable for financial institutions to lend to anything but the most pristine credit profiles.
It's a lesson I learned the hard way over my career: the cost of a loan often dictates who gets to apply for one, and it's a structural barrier we've never been able to dismantle. This high-cost structure created a vicious cycle. The need to guarantee profitability drove a reliance on narrow credit standards, which in turn forced lenders to be overly conservative, rejecting countless applicants who would have been perfectly reliable borrowers. It is a system that works for the few at the expense of the many, and one that has remained stubbornly resistant to change. The fintech community has tried to chip away at this problem for years, but the cost barrier has always been a formidable wall.
The promise of the internet and then mobile was to democratize credit. They offered a more efficient, accessible, and inclusive experience. And while these technologies did make the process more accessible, the promise of democratization ultimately fell short. The industry replaced paper forms with digital ones and a branch visit with a web portal.
Poor digital customer experience drove more multi-channel interactions, increasing costs for the bank, frustrating would be customers, and failing to address the root causes of the friction. The experience became transactional, not human. During the mobile revolution, we believed that putting a bank in every pocket would solve everything. At Moven, we were focused on using technology to drive financial wellness, but what we discovered was that a cool app alone isn’t enough. Technology and digital design limitations at the time forced us to do the best we could: build a digital facsimile of an analog process.
The digital user experience was (and still largely is) highly impersonal. It places the burden of navigation and decision-making on the customer, and when they inevitably get confused or need help, the experience breaks down. Customers who need human support to complete complex applications or to make the right financial choices are left with impersonal call centers or slow email chains. This ineffective client experience is a lose-lose: it's a poor experience for the customer, and it means a stunning 68% of online credit applications are abandoned before completion, a rate that has been steadily increasing.
This is where AI enters the narrative, and why it is different this time. The solution to this paradox is not a more polished digital form, but a new kind of intelligence altogether. Artificial intelligence is now poised to move the financial industry from an exclusive club to a genuinely open marketplace. Its power lies in its ability to directly address the two core problems of the legacy system: by enabling the use of richer, alternative data for underwriting and by creating a truly "human" and low-cost client experience. This is the new engine that finally allows us to build the human-centered, low-cost experience we've been chasing for decades.
Instead of relying solely on a FICO score, AI-powered systems can use alternative data to build a more comprehensive and accurate picture of a borrower's financial health. This includes a wealth of information previously ignored, from a customer's on-time utility and rent payments to their consistent cash flow and savings habits. This isn’t about making riskier loans; it’s about knowing customers more deeply; it’s about making smarter, more informed decisions by making visible the millions of "invisible" consumers and giving them a fair shot at credit. We can finally realize that decades-long vision of a fairer, more accessible system.
AI also allows us to provide a radically different customer experience. One that customers don’t abandon and perhaps even find enjoyable and valuable. We can use AI-powered mobile platforms to give customers a human-centered experience, at scale. Imagine an applicant completing a loan application on their phone but it’s not a transactional, sterile experience.
It’s like working with a personal coach. The AI can ingest, analyze, and respond to customer questions & concerns in real time, reducing the multi-channel handoffs that increase costs for the bank and almost always frustrate the customer.
I believe this is the biggest market opportunity the industry has ever seen. AI-powered lending can unlock specific, high-growth business opportunities by profitably serving distinct customer segments that the legacy system has ignored.
First, there is the mass affluent, a segment that often has complex financial needs but is overlooked by private banking. AI can deliver a concierge-like experience at a fraction of the cost, proactively suggesting home equity loans or tax-efficient lines of credit based on a client’s portfolio. Then there is the massive opportunity presented by the underbanked, a population of over 19 million U.S. households that has been historically underserved. For this group, AI is a force for inclusion, offering credit for the first time by using alternative data and a seamless, mobile-first experience. Because the cost-to-serve is so low, a bank can profitably offer micro-loans and small lines of credit. Finally, there are small businesses, the engine of the economy, who often face the longest and most cumbersome lending processes. An AI system can analyze a business's real-time cash flow to make a decision in minutes rather than weeks. This also applies to out-of-footprint customers where a bank can expand its market reach without the need for physical branch infrastructure, unlocking significant loan volume in new geographies. From my experience in in the space, I believe, a bank could acquire up to 20% of new loan volume from outside its traditional operating territory through a digital-first strategy, a market valued in the tens of billions of dollars. From my seat, this isn't just a technology trend; it's the culmination of everything we've learned over the last 30 years.
The democratization of lending is not a utopian ideal; it is an economic and technological imperative. By moving past outdated underwriting models and embracing a mobile-first, AI-driven experience, financial institutions can unlock a new era of growth and inclusion. For consumers and businesses, this means a fairer chance at the capital they need to build their futures. For the lending industry, it means moving from a limited, risk-averse model to one that is more dynamic, efficient, and genuinely accessible to everyone. The path forward is clear.
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