Why responsible AI is becoming a competitive advantage in financial services

As AI becomes embedded across financial services, Ian P. Moloney explains why success will depend less on the technology itself and more on governance, human oversight, and applying AI where it creates measurable value.

Ian, could you please introduce yourself and share more details about your professional background and your role at American Fintech Council? 

I started my work in the fintech space in 2017 during my time at the U.S. Government Accountability Office (GAO). In addition to drafting reports for the U.S. Congress on fintech, small business lending, as well as other tech and financial services related issues, I helped build GAO’s internal fintech working group. In my last year of working with GAO, I concurrently worked as a researcher for the Cambridge Centre for Alternative Finance where I co-authored several reports about fintech regulatory frameworks across the globe. While I always enjoyed conducting research in the fintech space, I found myself wanting to move into the implementation of laws and regulations. So, in 2022, I joined Cross River Bank, where I led the bank’s policy and regulatory engagements while navigating the operational and compliance realities of bank-fintech partnerships from the inside.   

Recognising the importance of engaging on both bank and fintech issues to help develop the modern banking system, I joined the American Fintech Council (AFC) in 2023, where I now serve as Chief Policy Officer, leading our regulatory and policy strategy. Through my role as Chief Policy Officer, I have been able to engage in nearly every policy issue facing innovative banks and fintech companies at both the federal and state levels. The mix of domestic and international experiences in my background allows me to engage critically with the regulatory environment and advocate for pragmatic, risk-based frameworks that protect consumers while fostering responsible innovation.  

AI has moved beyond experimentation and is increasingly embedded into credit decisioning, fraud detection, compliance, customer service, and operational processes. Where are you seeing the most meaningful value today, and where are institutions still struggling to move from pilot programs to measurable outcomes?  

We see tremendous value in AI when it is deployed as a tool to expand and improve on the existing products, services or processes in financial institutions. Fintech companies and innovative banks are able to leverage these AI tools so effectively because innovation is core to the institutions’ overall strategies. Particularly, we are seeing these technologies being used across core functions including fraud detection, risk monitoring, compliance operations, and customer service, and doing so in full compliance with regulations. Ultimately, both consumer-facing and back-office use cases that leverage AI are helping improve customer experience, as well as the safety and soundness of the financial institution. At this point, not innovating increases risk.  

Using AI effectively relies on a deep understanding of the product-market fit, and AFC’s member companies have focused on that piece throughout their engagement with various AI tools to improve their products, services, and processes. When implemented responsibly, AI tools enhance operational efficiency, strengthen risk management, and expand consumer access to financial services. However, it is always important to ensure that whoever is using the AI tool has a proper understanding of what the technology can do well, and what it cannot do well. AI, while often times discussed as a monolithic panacea, is not either of those completely. Thus, financial institutions should carefully consider the type of AI solution they are implementing. Particularly in the compliance space, financial institutions should ensure that the AI tool is used to improve, not replace their existing processes and workforce and that it is not over-relied on as a crutch that entirely replaces a financial institution's existing processes. Simply put, financial institutions should be using AI to augment, not replace the process.   

Many institutions argue that existing regulatory frameworks can adequately govern AI when it supports existing financial products and services. Do you agree, or do emerging AI use cases require new regulatory approaches? 

It is important to remember that while AI is a truly revolutionary technology, it is still a technology that is overlayed upon existing financial services, products , and processes. These services, products, and processes all have existing and long-standing regulatory frameworks. At AFC, we advocate for a pragmatic approach to innovative technology, and we believe that AI governance frameworks should build on the strong, well-established risk management and compliance structures that regulated financial institutions already maintain. We have outlined three core principles for effective AI governance in financial services: data privacy and security, transparency in how AI systems operate, and meaningful human oversight.   

These principles align seamlessly with existing risk management systems and can be integrated into current supervisory frameworks without adding unnecessary complexity. Effective governance should be grounded in proportionality and flexibility. Policymakers and regulators should focus on how AI systems are used in practice rather rushing to regulate the latest newsworthy item. We have seen this “rush to regulate” in certain states, and I would caution legislatures from pursuing such activities without first taking a careful look at the existing regulatory frameworks that have worked quite well for many years.  

As AI adoption accelerates across financial services, how can banks and fintechs balance innovation with accountability while ensuring consumer protection, fair outcomes, and regulatory compliance? 

AI is becoming an increasingly important tool across financial services, helping institutions detect fraud, strengthen compliance efforts, improve operational efficiency, and better serve consumers. As its use continues to expand, the focus should be on ensuring these technologies are deployed responsibly and with appropriate oversight. 

From my perspective, regulation should be risk-based and tailored to the specific use case rather than treating all AI applications the same. Financial institutions already operate within robust consumer protection, privacy, and compliance frameworks, and AI governance should build on those existing safeguards. Clear, flexible standards that address real risks without limiting beneficial innovation will help ensure consumers can benefit from new technologies while maintaining trust in the financial system.  

Further, at a minimum, there needs to be a strong focus from policymakers on harmonisation of state and federal laws around AI. Given that AI, like most innovations, does not have geographic constraints, state and federal governments need to ensure a unified approach to any regulatory framework. Pursuing a fragmented or patchwork system will not help improve AI adoption or ultimately provide the best protections to consumers. 

What does effective AI governance look like in practice for banks and fintechs in 2026, particularly when managing model risk, third-party providers, and operations across multiple regulatory jurisdictions? 

Effective AI governance in 2026 starts with ensuring financial institutions have clear visibility into how AI is being used and who is accountable for its outcomes. As innovative banks and fintech companies deploy AI for fraud detection, compliance, underwriting, and customer service, they should maintain strong governance practices, including model testing, validation, ongoing monitoring, and documentation. Institutions must also ensure appropriate human oversight, so AI supports decision-making without diminishing accountability. 

Good Governance also extends to third-party providers. Innovative banks are used to this process in their other fintech partnerships, and bringing in AI tools is no exception. The same due diligence processes these institutions use for fintech partners should be used when engaging with AI tools. Institutions should conduct thorough due diligence, establish clear expectations around performance and data security, and continuously monitor those relationships. Regardless of whether a tool is built internally or sourced from a vendor, financial institutions remain responsible for its use and outcomes. 

Institutions operating across multiple regulatory jurisdictions face the challenge of navigating an increasingly fragmented regulatory environment. AFC has consistently advocated for clear, risk-based frameworks that provide institutions with consistent rules of the road while recognising that AI use cases present different levels of risk. Governance frameworks should build upon existing risk management, compliance, and consumer protection programs, allowing institutions to adapt to evolving regulatory expectations while continuing to deploy AI responsibly and deliver benefits to consumers.  

As generative AI becomes increasingly customer-facing, what safeguards are essential to maintain trust, transparency, and appropriate human oversight?  

Everything in financial services comes down to trust. As consumers increasingly interact with AI-powered chatbots, virtual assistants, and agentic financial planners, maintaining trust depends on ensuring those systems are accurate, transparent, and subject to appropriate oversight. Consumers should know when they are engaging with AI, understand the nature of the information being provided, and have the ability to quickly connect with a human representative when addressing complex financial questions, disputes, or issues that could materially affect their finances.  

Financial institutions should also implement strong governance and monitoring practices to ensure AI-generated outputs remain accurate, reliable, and consistent with consumer protection requirements. This includes regularly evaluating system performance, protecting sensitive consumer data, and maintaining clear accountability for outcomes. Going forward, the most effective approach will be one that uses these tools to enhance customer service and access to information while preserving meaningful human oversight and consumer confidence. Trust and transparency go hand-in-hand for the consumer experience.  

Looking ahead, which AI use cases do you believe remain underestimated by the industry, and where do you see the greatest potential for transformation across financial services over the next three to five years? 

One of the most underestimated applications of AI is its ability to strengthen financial crime prevention. As fraud schemes become more sophisticated and increasingly leverage technologies such as synthetic identities, deepfakes, and automated scams, AI will play a critical role in helping financial institutions detect suspicious activity in real time, identify emerging threats, and respond more quickly to protect consumers. AI is inherently better than humans at taking in large amounts of data and recognising patterns or anomalies: two key factors in combating fraud. The technology's ability to analyse vast amounts of data and recognise complex patterns makes it particularly well-suited to staying ahead of rapidly evolving financial crime risks. 

Another underestimated area is AI’s ability to modernise regulatory compliance and supervision. AI-powered regulatory technology and supervisory technology have the potential to identify risks earlier, reduce compliance burdens, improve monitoring and reporting, and enable more efficient collaboration between financial institutions and regulators. I have been speaking with regulators for years about the need to leverage AI in their supervisory and examination processes. Of late, I have been quite encouraged by where these regulators are heading and believe that they truly understand the need to innovate on their side.  

Over the next three to five years, we are likely to see AI become increasingly embedded across the full lifecycle of financial services operations, including compliance, fraud prevention, customer service, risk management, and product development. The institutions that successfully leverage AI as a tool to augment human expertise, strengthen decision-making, and deliver better outcomes for consumers will be best positioned to drive responsible innovation while maintaining trust and accountability. Further, regulators will follow suit and move to have AI tools across their agencies, helping with everything from rulemakings to examinations. Ultimately, these developments on both the industry and regulatory side will improve customers’ experiences, industry resilience, and engagements between regulators and their regulated entities. 

About the interviewee

Ian P. Moloney is Chief Policy Officer for the American Fintech Council (AFC), leading the association’s policy strategy across the fintech ecosystem. Ian has been in the fintech space since 2017 and has published reports on the topic for the Federation of American Scientists, Cambridge Centre for Alternative Finance, and the United Nations. Ian holds an MBA from Johns Hopkins University and a bachelor’s degree from Central Michigan University.

About the organisation

A standards-based organisation, the American Fintech Council (AFC) is the largest and most diverse trade association representing financial technology (fintech) companies and innovative banks. On behalf of over 150 member companies and partners, AFC promotes a transparent, inclusive, and customer-centric financial system by supporting responsible innovation in financial services and encouraging sound public policy. AFC members foster competition in consumer finance and pioneer products to better serve underserved consumer segments and geographies.