AI in Fintech: How Banking Is Being Rebuilt from the Inside Out
Everyone is talking about the $41 trillion prize in private credit. The real story isn’t the opportunity, though. It’s the risk.
We’re building a new, faster, more efficient financial system on a foundation nobody is auditing. Private credit has exploded post-2008, filling a gap left by banks. With AI using complex models to underwrite loans at a scale and speed we’ve never seen before, the speed is becoming unprecedented.
Remember 2007? Complex instruments that everyone thought they understood, but which led to a bubble burst.
Here is what is happening:
- Synchronised Risk: Everyone is using similar AI models, trained on similar data. Scienaptic AI’s CEO said it best: If everyone’s running the same signals, risks don’t diversify. They synchronise.
Synchronised risk is how a localised problem becomes a global contagion.
- The Black Box Problem: These AI models are making credit decisions, but what happens when they’re wrong? A record $25 billion in software-sector leveraged loans—the very sector AI is supposed to disrupt—are already trading at distressed levels.
The models are pricing risk, but are the models themselves the risk?
- The Governance Gap: The U.S. Treasury just dropped a 230-point AI risk framework for finance. Meanwhile, 57% of banking execs plan to have AI agents fully embedded in risk and compliance within 3 years.
How many have implemented those 230 controls? My guess: close to zero.
This isn’t about being anti-AI. We build AI systems for a living at Mind IT Systems. This is about being eyes-wide-open about the systemic risks being created.
In a frantic race to adopt AI, are we forgetting the lessons of the last financial crisis? Innovation without governance isn’t progress—it’s a ticking time bomb.
So, what’s the play? It’s not to stop. It’s to get smarter.
- Demand Model Diversity: Don’t just buy off-the-shelf AI. Challenge your vendors. Run challenger models. Treat model risk like concentration risk.
- Stress-Test the AI Itself: Forget just stress-testing for market downturns. What happens if your core underwriting model fails? What is the backup plan.
- Build Human-in-the-Loop Governance: Real governance isn’t a checkbox. It’s a culture of accountability where humans question, audit, and override algorithmic decisions.
The winners in this new era won’t be the banks that deploy the most AI agents. It will be the ones who master them.
Are we building a more efficient financial system, or just a faster way to fail?
References
[1] Forbes. (2026, March 4). AI Is Reshaping The Assumptions That Built The Private Credit Boom.
[2] U.S. Department of the Treasury. (2026, February 19). Treasury Releases Two New Resources to Guide AI Use in Financial Sector.
[3] Accenture. (2026). Banking Technology Vision 2026.
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About the Author
Shailendra Gupta
(Co-Founder and CEO of Mind IT Systems)
Shailendra is Co-Founder and CEO of Mind IT Systems and is responsible for strategy and business relations.
With around two decades of experience in getting things done in marketing, sales, strategy, delivery, or technology, he has a successful track record of leading startups and mid-size companies and being a prime contributor to stakeholder management, growth, and value creation. A thought leader in the geo-social space, he is highly respected for realizing new paradigms in marketing, solutions, and approaches.