Priya Jaiswal is a distinguished authority in the banking and financial technology sectors, possessing a wealth of experience in market analysis and the intricacies of international business trends. As the industry stands at a pivotal crossroads between traditional fiscal structures and the rapid integration of artificial intelligence, Jaiswal offers a seasoned perspective on what it means to build a financial institution from the ground up using modern technology. Her insights bridge the gap between complex regulatory requirements and the agile world of fintech innovation, providing a roadmap for the future of credit. In this discussion, we explore the strategic evolution of national banking charters, the shift from state-level oversight to federal frameworks, and the financial mechanics that allow digital-only entities to achieve massive scale while maintaining deep-rooted industry partnerships.
Transitioning to a national charter and bank holding company status involves moving from a patchwork of state licenses to a single federal framework. How will this shift specifically reduce operational costs, and what regulatory efficiencies do you anticipate gaining through direct oversight by the OCC and FDIC?
Moving away from a fragmented system of state-by-state licensing is like shedding an old, heavy skin that has long restricted the speed of innovation. By consolidating under a single federal framework with the OCC and FDIC, a firm can eliminate the exhausting duplication of compliance efforts that naturally occurs when managing fifty different sets of regulations. This streamlined oversight creates a much more agile environment where product teams can launch updates and new offerings without getting bogged down in repetitive state-level approvals. Ultimately, these operational efficiencies do more than just clean up the balance sheet; they allow the institution to pass savings directly to the consumer through more frequent loan approvals and significantly lower interest rates.
With over 90% of your loans now fully automated using alternative data like job history and education, how does this AI-driven approach consistently outperform traditional credit models? Could you share the metrics or step-by-step logic that allows for higher approval rates alongside lower interest rates?
The power of this model lies in its ability to see the human potential that traditional, rigid credit scores often ignore by focusing solely on past debt. By automating 90% of the process and incorporating alternative data like an applicant’s education and employment history, the system creates a much more holistic picture of financial reliability. We have seen this logic yield incredible results, such as the 2019 data which showed loan approvals increasing by 27% over a two-year period. Perhaps more importantly for the consumer, this intelligence-led approach allowed for a 16% average drop in annual percentage rates, proving that modern data can lower the cost of borrowing while maintaining a healthy risk profile.
Your model currently involves selling 95% of originated loans to partner institutions while using brokered deposits for internal capital. How do you plan to scale this bank without becoming a direct competitor to your lending partners, and what strategies will ensure your funding sources remain diversified?
Growth in this space requires a very careful balance to ensure we are empowering our partners rather than competing for their local customers. We are firmly committed to a strategy where we continue to sell 95% of our originated loans to our network of over 100 banks, credit unions, and institutional funds, keeping us as the engine rather than the driver. To build our own internal capital, we intend to utilize brokered deposits and specific retail deposit offerings that don’t overlap with the traditional checking and savings accounts our partners rely on. This approach keeps our funding sources diversified and resilient, ensuring we have the liquidity to scale without disrupting the vital relationships that form the backbone of our business.
Moving from a regulatory sandbox to a full national bank charter requires intense transparency regarding AI model deployment and risk management. What specific protocols are you implementing to address concerns from agencies like the SEC while setting a new standard for modern AI within the banking system?
Transitioning from a sandbox environment to the full scrutiny of federal agencies like the OCC and the Fed is a rigorous journey that demands absolute clarity in how algorithms function. We are working to establish a new gold standard for transparency, treating every interaction with regulators as an opportunity to prove that our AI models are both fair and mathematically sound. While past challenges, such as the 2023 SEC subpoena regarding model disclosures, were demanding, they have helped us refine our protocols for explaining complex automated decisions to oversight bodies. By participating in “incubation events” and maintaining an open-door policy with federal examiners, we aim to demonstrate that AI is not a “black box” but a highly disciplined tool for expanding credit access safely.
Maintaining a branchless, Delaware-based entity that serves all 50 states significantly alters the traditional banking overhead structure. How does this digital-only approach impact your customer acquisition costs, and what were the primary financial drivers that enabled your recent shift from a loss to a billion-dollar revenue?
Operating without the physical weight of traditional brick-and-mortar branches allows for a lean, high-velocity financial structure where capital can be reinvested directly into technology. This digital-only efficiency was a primary driver in our recent financial turnaround, helping us reach approximately $1 billion in revenue for 2025, which represents a massive 64% increase from the prior year. We saw this momentum culminate in an $18.6 million profit for the fourth quarter, a stark and vital contrast to the $2.8 million loss we recorded during the same period a year earlier. By keeping overhead low and focusing on a seamless digital experience, we can acquire customers at a fraction of the cost of legacy banks while scaling our operations at an unprecedented rate.
What is your forecast for AI-powered banking charters?
I believe we are on the verge of a total transformation where the AI-powered charter becomes the definitive blueprint for the next generation of global finance. Last year alone, we saw 18 new banking charter applications filed with the OCC, signaling a massive wave of interest from fintechs and neobanks who realize that legacy systems can no longer keep pace. We are entering an era where the most successful institutions will be those that have fully integrated machine learning into their regulatory and operational DNA. My forecast is that within the next decade, the distinction between “fintech” and “bank” will vanish, leaving behind a landscape of highly efficient, automated institutions that provide more inclusive and affordable financial services to everyone.
