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Can Fintechs Leverage AI for Regulatory Compliance?


April 2, 2024 ( Newswire) Fintechs have been under increased regulatory scrutiny. The Consumer Financial Protection Bureau (CFPB) announced a proposed rule that would make digital wallets and payment providers responsible for compliance.

Under previous scenarios, many fintechs relied on financial institutions for compliance. After all, banks and credit unions have experience with regulatory compliance. Fintechs, on the other hand, create digital products and services. Many lack expertise in dealing with supervisory guidance from bank examiners.

However, as the fintech industry has grown and matured, regulators have concluded that digital banking companies need to take on this responsibility.

Managing compliance risk will be a heavy lift for many fintechs. If the proposed rule goes into effect, financial technology firms should plan on incorporating integrated risk management software into their products and services.

They might also consider implementing AI to handle compliance functions. We'll delve into the benefits and limitations of AI solutions for fintech banking compliance.

Can a Natural Language Model (NLM) Handle Compliance?

NLMs introduce efficiencies for fintechs in everything from handling third-party contracts to customer service. For instance, if a financial technology firm entered inputs from its customer loan portfolio into an NLM, the system could generate outputs to answer inquiries with a chatbot.

With regulatory compliance, AI use cases become more slippery because these often require a human touch.

Let's take fair lending as an example. Many financial institutions and mortgage brokers that underwrite loans use automated valuation models (AVMs) to determine the creditworthiness of applicants.

But regulators have consistently warned lenders about overreliance on AVMs for fair lending risk. AVMs do not consider the race, ethnicity, or sex of the applicant in their assessments, protected classes under the Equal Credit Opportunity Act (ECOA) and the Home Mortgage Disclosure Act (HMDA).

Given the technology's limitations, automating fair lending compliance will not work - at least not yet. Like the social media algorithms that target specific demographic populations, fintechs should tread lightly with black-box algorithms for this compliance function.

Privacy Concerns for AI

Uploading customer or proprietary information into an AI system also risks data leakage and misuse.

Compliance with the Gramm-Leach-Bliley Act (GLBA) requires financial entities to have a security plan to maintain the confidentiality and integrity of customers' personal information. Commonly used AI programs such as ChatGPT do not have the guardrails to ensure that data won't be leaked to the public.

Despite assurances from OpenAI that it doesn't store human-machine conversations, we know they have very loose protocols for securing sensitive data. When an engineer at Samsung entered proprietary code onto the platform, this information leaked to the public, leading to a company-wide ban on the use of ChatGPT.

Additional Operational Issues with AI for Fintechs

Fintechs must consider AI interoperability with its existing software systems. AI systems require extensive data in particular formats to operate effectively. A fintech's existing software systems may not be compatible with AI models, requiring a complete reconfiguration.

AI systems for compliance management also may not scale with existing software architecture. Managing AI systems might be cost-prohibitive if fintechs cannot afford a team to handle ongoing integrations.

Possible future use cases for AI compliance management systems

While it doesn't seem that AI can do much in compliance management for fintechs presently, the technology is advancing quickly. While no one can say with certainty when enterprise-grade AI tools will be helpful in this arena, it does seem that fintechs will require private-cloud AI platforms rather than open cloud-based solutions.

When it comes to AI for regulatory compliance, much will depend on how quickly companies can build platforms that comply with regulatory requirements.  

Michael Berman is the founder and CEO of Ncontracts and the author of The Upside of Risk: Turning Complex Burdens into Strategic Advantages for Financial Institutions.

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