Impact of fintech on lending is moving from theory to hard evidence as new research by economist Xavier Vives outlines how AI, big data and digital platforms are reshaping credit markets. The analysis explains why fintech has boosted efficiency and financial inclusion, yet also heightened concerns over stability, privacy and discrimination. Crucially, it offers a framework for policymakers weighing price discrimination, open banking and how to level the playing field between banks and new entrants.
Vives, a professor at IESE Business School, and co-author Zhenyu Ye examine the mechanics behind mixed real-world findings: in some places fintech reduces rates and defaults; elsewhere results are neutral or even riskier. Their takeaway is straightforward: the impact of fintech on lending depends on how technology alters competition between banks and fintechs, how far it reduces distance between borrowers and lenders, and whether firms can price-discriminate using granular data.
What the research says and why it matters
The new framework, set out in Vives and Ye (2025a, 2025b), clarifies the drivers behind the headline results seen in the U.S., Europe and Asia. It highlights two levers that determine market outcomes:
- Differentiation: How distinct banks and fintechs are in expertise, data, convenience and customer relationships.
- Efficiency gap: How much better one group is at screening, monitoring and processing loans.
When technology narrows these gaps—especially by reducing “distance frictions” through AI, digital footprints and better connectivity—competition intensifies. That can lower prices and expand access, but it may also compress profit margins and reduce lenders’ incentives to monitor risk. In the model, investment and welfare follow a hump-shaped curve: too little competition hurts borrowers, too much can erode prudent screening. The sweet spot sits in the middle.
This helps explain why the impact of fintech on lending looks different across markets. The outcomes hinge on bank concentration, the intensity of rivalry among fintechs, whether price discrimination is allowed, the size of the unbanked population and the convenience advantage digital lenders deliver.
A quick tour of the evidence
Recent studies illustrate the diversity of results:
- Default rates: Some research finds higher delinquency for fintech-originated loans, others show lower or no difference.
- Open banking: Data-sharing regimes can enable small businesses to form new relationships with nonbanks and cut interest costs—though inclusion gains vary by country.
- Privacy and pricing: In California, stronger privacy rules coincided with better screening by fintechs relative to banks and more personalized mortgage pricing, lowering rates for some borrowers.
Put together, the literature says the impact of fintech on lending depends on policy design, market structure and the technology mix in use.
How competition is changing between banks and fintechs
At the core of the framework is a simple but powerful setup: banks and fintechs compete to lend to entrepreneurs. Banks start with advantages in funding costs and soft information gathered through relationships. Fintechs tend to lead in data processing, converting soft information into hard signals, reducing geographic or expertise “distance,” and offering high convenience—faster onboarding, smoother interfaces and flexible pricing.
Key competitive dynamics:
- Entry conditions: Fintech entry can be deterred, remain a credible threat or surge, depending on monitoring efficiency and funding costs.
- Substitutes or complements: If banks had limited competition before entry, fintech lending more often substitutes for bank lending; if banks were already competing head-to-head, fintech can complement banking capacity.
- Concentration effect: The higher the concentration among banks, the greater the room for fintech entry and loan volume expansion.
- Pricing power: If banks cannot price-discriminate but fintechs can, digital lenders can profitably enter even without superior monitoring. If banks also price-discriminate, fintechs need a true efficiency or funding edge to win share.
In practice, when fintechs excel at convenience but face higher funding costs, they may charge more and monitor less, while banks keep tighter screens. These differences in convenience, funding costs and pricing flexibility help reconcile the mixed findings on defaults and pricing.
Distance friction, data and AI
A central insight is the role of “distance friction”—the effective gap between lender and borrower in geography, industry expertise or information. Technologies that reduce distance, such as video conferencing, improved connectivity, AI-assisted underwriting and big-data search, can make lenders more alike and increase head-to-head rivalry.
- If distance falls: Differentiation shrinks, competition rises, margins narrow, and—depending on the severity of moral hazard—monitoring incentives may weaken.
- If distance stays the same: The impact of fintech on lending is still meaningful through efficiency gains, but competition effects are milder and monitoring incentives hold up better.
The nuance matters for policy. Tools that promote data sharing without encouraging vigorous competition could tilt the market toward a few dominant platforms.
Where price discrimination helps—and where it hurts
Granular data lets lenders tailor prices to risk and convenience. The framework shows that price discrimination is a competitive weapon but not automatically welfare-enhancing. It is most defensible when it expands the market—bringing more viable borrowers into the fold.
A counterintuitive result emerges for banks with location-based costs. From a welfare perspective, banks should charge higher rates to distant borrowers, where monitoring is harder and surplus is lower. In competitive equilibrium with price discrimination, the opposite may occur as banks cut rates at the fringe to match rivals. Allowing banks to price-discriminate when fintechs already can may improve welfare in markets with limited competition among fintechs by restoring some balance between borrower access and lender monitoring incentives.
Open banking and the balance of competition
Open banking can unlock credit by making data portable. But the impact of fintech on lending through open banking depends on market rivalry:
- With strong inter-fintech competition: Data access can broaden choice, lower prices and improve risk sorting.
- With weak inter-fintech competition: The same policy may entrench a leading platform within a segment, undermining inclusion and dynamic efficiency.
The cross-country evidence reflects this tension—some markets see clear gains in access and pricing, others show muted inclusion effects.
What this means for borrowers and small businesses
For consumers and entrepreneurs, the practical message is straightforward:
- Expect more personalized pricing: Data-driven underwriting increasingly tailors interest rates and terms to risk and convenience.
- Faster onboarding, but mind the privacy tradeoffs: Digital footprints reduce friction but heighten sensitivity to data governance.
- Multiple channels are your friend: A banking relationship plus a fintech lender can improve access and negotiating power.
- Shop around: As the impact of fintech on lending spreads, comparing offers across banks and fintechs can yield better rates or terms.
Industry perspectives and recent moves
Banks are responding with their own AI tools, partnerships and digital overlays on legacy platforms. Fintechs continue to push into underwriting with alternative data and embedded finance models. Regulators are clarifying data rights and model risk management as algorithmic lending becomes mainstream.
Updates to watch:
- Model risk oversight: Supervisors are issuing guidance on bias, explainability and monitoring for machine-learning credit models.
- Data portability: Open banking and data-rights rules are expanding in the U.S. through sectoral initiatives while the EU advances standardized frameworks.
- Privacy regulation: State privacy laws influence who benefits from data-enabled pricing and screening—affecting the competitive balance between banks and fintechs.
These developments shape the eventual impact of fintech on lending by setting the boundaries for data use, pricing flexibility and entry.
Policy takeaways from the framework
The research suggests a practical policy roadmap that balances competition, inclusion and risk:
- Level the playing field on data and pricing tools
- If fintechs can price-discriminate, allowing banks reasonable flexibility may improve welfare in low-competition settings by sustaining monitoring incentives.
- Ensure symmetric access to key data, alongside strict privacy and security standards.
- Pair open banking with strong competition policy
- Promote inter-fintech rivalry so data portability does not entrench a single leader within a segment.
- Monitor for tipping effects in narrow niches where one platform can scale quickly.
- Keep incentives for monitoring intact
- Structure rules so lenders do not race to the bottom on underwriting quality when margins compress.
- Encourage idempotent processes and transparent adverse action notices to help borrowers and reduce disputes.
- Target inclusion with guardrails
- Encourage responsible use of alternative data that expands access without embedding discrimination.
- Test for disparate impact in algorithmic lending and require remediation where needed.
The overarching goal is to harness the efficiency and inclusion benefits while protecting competition, privacy and financial stability.
Investor angle: signals to track
For investors in banks and fintechs, the questions are practical:
- Where does technology truly lower distance friction, and where are gains incremental?
- Do incumbents retain funding-cost advantages that offset fintech convenience?
- Are regulators moving toward pricing parity and data symmetry?
- How concentrated is the local market, and how fierce is inter-fintech rivalry?
Answers to these will shape margins, loan growth and the realized impact of fintech on lending over the next cycle.
Methodological note
Vives and Ye model a spatial oligopoly where banks are differentiated by expertise and relationships while fintechs sit “virtually in the middle,” with greater convenience and more flexible pricing. Entrepreneur participation is endogenous, and monitoring improves outcomes by boosting expected project returns or mitigating moral hazard. Within this structure, policy levers—price discrimination rules, data sharing, contestability—shift competitive intensity and thereby incentives to monitor.
Bottom line
The evidence is converging on a nuanced truth: the impact of fintech on lending is powerful but context-dependent. When technology reduces distance and competition is healthy, borrowers tend to benefit through lower prices and broader access. When rivalry is weak or monitoring incentives erode, risks rise. Smart policy can tilt the system toward the welfare-maximizing middle—leveling tools across players, pairing open banking with strong competition, and keeping robust safeguards for privacy and fairness.
As AI and data reshape credit, markets will reward models that combine speed and personalization with disciplined risk controls. That is where innovation and inclusion reinforce each other rather than collide.
Article Source: CEPR
