Consumer Finance Monitor

On May 12, 2026, we produced a 90-minute webinar in which we explored one of the most important and rapidly developing issues in consumer financial services law: coerced debt and the emerging legislative efforts designed to address it. The webinar has been re-purposed into a two-part podcast series, the first of which was released this past Thursday, June 11th, and the second of which is being released today, Thursday, June 18th. Alan Kaplinsky, Founder, former Chair for 25 years and now Senior Counsel of the Consumer Financial Services Group at Ballard Spahr, LLP hosted and moderated this discussion. The discussion examines the growing recognition that individuals, often survivors of domestic violence, elder abuse, human trafficking, or other forms of coercive control, can be manipulated, threatened, or deceived into incurring debt without meaningful consent. The program focuses in particular on New York's newly enacted coerced debt statute, which creates a framework allowing consumers to challenge the enforceability of debts incurred through coercion and requires creditors and debt collectors to investigate such claims. This topic was covered in Part 1. The episodes feature an outstanding panel of experts from academia, legal services organizations, consumer advocacy groups, and private practice. Professor Angela Littwin of the University of Texas School of Law discusses her groundbreaking research on coerced debt, including empirical studies demonstrating the prevalence of the problem and the inadequacy of traditional legal remedies such as divorce proceedings, bankruptcy, and fraud defenses. Representatives from CAMBA Legal Services, Brooklyn, New York, Divya Subramanyam and Naomi Young, explain how the New York statute is intended to operate in practice, including the evidentiary requirements imposed on survivors, creditor obligations upon receipt of a coerced debt claim, and the practical challenges survivors face in seeking relief. Part 2 of the program being released today begins with a discussion of the broader national landscape. Carla Sanchez-Adams of the National Consumer Law Center discusses similar legislative initiatives developing across the country, including laws enacted in states such as California, Texas, Connecticut, Minnesota, Maine, Illinois, and Vermont, as well as pending legislation elsewhere. Carla and the panel further analyze the interaction between coerced debt claims and existing federal laws such as the Fair Credit Reporting Act and Truth in Lending Act, while also addressing ongoing efforts to expand federal protections. Finally, Ballard Spahr attorney, Dan Wilkinson, offers an industry perspective on the significant operational and compliance issues created by these laws for banks, finance companies, debt collectors, and other financial institutions. The discussion highlights the challenges of identifying coerced debt claims, conducting investigations while protecting survivor confidentiality, training frontline personnel, and balancing consumer protection concerns with fraud prevention and risk management obligations. Consumer Finance Monitor is hosted by Alan Kaplinsky, Senior Counsel at Ballard Spahr, and the founder and former chair of the firm's Consumer Financial Services Group. We encourage listeners to subscribe to the podcast on their preferred platform for weekly insights into developments in the consumer finance industry.

Artificial intelligence is rapidly transforming the consumer financial services industry. From underwriting and fraud detection to customer engagement and collections, financial institutions are increasingly deploying advanced AI tools to automate processes, personalize services, and improve operational efficiency. We are releasing today, on our Consumer Finance Monitor Podcast show, a discussion of what may be the next major technological shift for the industry: Agentic AI in Consumer Financial Services — AI systems capable of acting autonomously, making decisions, and interacting directly with consumers. The discussion featured Professor Oren Bar-Gill of New York University School of Law, along with Ballard Spahr partners Joseph Schuster and Adam Maarec. The discussion was hosted by Alan Kaplinsky, the founder and practice group leader for 25 years of the Consumer Financial Services Group and now Senior Counsel. The panel examined how agentic AI differs from earlier forms of automation, the benefits it offers financial institutions and consumers, and the significant legal and regulatory risks it may create. Below are the key takeaways from the discussion. What Is Agentic AI? Agentic AI refers to AI systems that can independently take actions on behalf of users or organizations. Unlike traditional automation, which performs predefined tasks, or generative AI, which primarily produces content, agentic AI systems can: · Make autonomous decisions · Interact directly with consumers · Initiate actions such as transactions or communications · Learn from prior interactions In financial services, these systems may soon conduct customer service interactions, initiate collections calls, execute payments, or manage purchasing tasks for consumers. While these capabilities promise major efficiencies, they also raise complex legal questions regarding accountability, fairness, and consumer protection. Understanding AI-Driven Consumer Harm Professor Bar-Gill framed the discussion by examining potential consumer harms associated with AI-powered decision-making. Drawing on his recent book with Cass Sunstein, Algorithmic Harm: Protecting People in the Age of Artificial Intelligence, he explained that the impact of AI depends largely on the type of market in which it operates. The book is available on Amazon here. Sophisticated vs. Unsophisticated Markets Bar-Gill distinguishes between: · Sophisticated markets, where consumers are generally able to make informed decisions · Unsophisticated markets, where consumers are more likely to misunderstand complex products In sophisticated markets, AI-driven personalization, such as individualized pricing, can increase efficiency and expand access to products by offering lower prices to consumers with lower willingness to pay. In contrast, in markets involving complex financial products, such as credit cards, mortgages, or insurance, AI-powered personalization may harm consumers who misjudge product costs or benefits. For example, if a consumer mistakenly overestimates the value of a financial product, an AI system may set the price just below that mistaken valuation, leading the consumer to pay more than the product is actually worth. Algorithmic Price Discrimination One area of growing concern is AI-enabled price discrimination, where algorithms tailor prices to each consumer's willingness to pay. Examples cited during the discussion included: · Airlines experimenting with AI-based pricing strategies · Online retail platforms offering individualized prices for identical products · Insurance companies using algorithms to optimize premiums While pricing based on individual risk, such as in insurance underwriting, is widely accepted, pricing based on willingness to pay raises significant consumer protection concerns. As these practices expand, they are likely to attract increased attention from regulators and lawmakers, particularly at the state level. AI Use Cases in Consumer Finance The panel also highlighted several areas where AI is already being deployed across the consumer financial services lifecycle. Marketing and Customer Acquisition Financial institutions are using AI to analyze large data sets and create highly personalized marketing campaigns. Large language models can generate customized messaging tailored to specific demographic groups or individual consumers. While this personalization improves targeting and engagement, it also creates compliance challenges related to: · Misleading advertising · Disclosure requirements · Potential discriminatory targeting Underwriting and Credit Decisions AI-driven underwriting tools allow lenders to analyze alternative data, such as cash-flow information, to assess creditworthiness. These tools may expand access to credit for consumers who previously lacked traditional credit histories. However, they also raise fair lending concerns under laws such as the Equal Credit Opportunity Act and its implementing regulation, Regulation B. Because many AI models operate as "black boxes," institutions may struggle to explain how decisions are made, an issue that can complicate discrimination analyses and regulatory oversight. Fraud Detection AI is particularly powerful in fraud detection, where pattern recognition is essential. Advanced models can analyze transaction behavior in real time to identify suspicious activity while minimizing unnecessary transaction declines. These tools also allow financial institutions to communicate with customers instantly, confirming transactions or investigating suspicious activity through automated interactions. Servicing and Collections Agentic AI may soon conduct both inbound and outbound customer interactions, including: · Customer service conversations · Dispute resolution · Collections calls In some cases, AI-driven voice systems can conduct conversations that are indistinguishable from human interactions. While this technology may improve efficiency and reduce costs, it raises legal concerns about consumer deception, harassment, and compliance with debt collection laws. Core Legal Risks Despite the novelty of the technology, many of the key legal risks arise from existing laws, not new AI-specific statutes. Liability for AI Actions As Joseph Schuster emphasized, AI is a tool, not a liability shield. Institutions remain responsible for the actions of AI systems just as they would for the actions of employees or third-party vendors. Traditional legal doctrines, including agency law, vicarious liability, and unfair or deceptive acts or practices, continue to apply. UDAP Risks AI systems interacting with consumers may create risks under federal and state UDAP laws if they: · Provide inaccurate information ("hallucinations") · Fail to deliver required disclosures · Exhibit overconfidence in uncertain responses · Engage in manipulative behavioral targeting. Fair Lending and Discrimination AI models can unintentionally produce discriminatory outcomes, even when protected characteristics are not used as inputs. As Professor Bar-Gill noted, future litigation may increasingly focus on disparate impact analysis, which examines whether outcomes disproportionately affect protected classes regardless of the model's internal logic. Governance and Risk Management Given these risks, institutions are increasingly adopting governance frameworks for AI deployment. Common practices include: · AI governance committees with cross-functional participation · Model inventories and risk-tiering systems · Vendor due diligence for AI providers · Data mapping and validation processes · Continuous monitoring of AI outputs. Financial regulators are already asking supervised institutions detailed questions about how AI is being used. Institutions that implement structured governance processes are better positioned to respond to these inquiries. The Rise of Agentic Commerce One emerging application of agentic AI involves autonomous purchasing. For example, a consumer might instruct an AI assistant to plan and purchase supplies for a birthday party. The AI would then select vendors, place orders, and initiate payments using the consumer's stored payment credentials. But what happens if AI makes a mistake, such as ordering supplies for 1,000 guests instead of 10? Such scenarios raise difficult questions involving: · consumer authorization · merchant liability · payment network rules · dispute resolution These issues are only beginning to receive attention from regulators and industry participants. Key Takeaways for Financial Institutions The panel concluded with several recommendations for institutions exploring AI deployment. First, distinguish beneficial uses from harmful ones. AI can deliver significant consumer benefits, but firms must remain vigilant about potential misuse or unintended harm. Second, prioritize governance. Robust policies, oversight structures, and risk management processes are essential. Third, remember that existing laws still apply. AI systems must comply with the same consumer protection, fair lending, and disclosure requirements that govern traditional processes. Finally, institutions must recognize that failing to adopt AI also carries risks. As fraudsters increasingly deploy advanced technology, financial institutions may need AI tools simply to keep pace. As AI technology continues to evolve, the legal framework governing its use in financial services will also develop. For now, however, the most important lesson is that innovation must proceed hand-in-hand with careful legal and compliance oversight. Consumer Finance Monitor is hosted by Alan Kaplinsky, Senior Counsel at Ballard Spahr, and the founder and former chair of the firm's Consumer Financial Services Group. We encourage listeners to subscribe to the podcast on their preferred platform for weekly insights into developments in the consumer finance industry.

In a recent episode of the award-winning Consumer Finance Monitor podcast, Alan Kaplinsky was joined by Nick Bourke, Kate Griffin, and Ballard Spahr partner Joseph Schuster to discuss a groundbreaking new report from the Aspen Institute Financial Security Program: United We Stand: A National Strategy to Prevent Scams. The episode builds on Nick and Kate's prior appearance on the podcast last July, when the report was still in development. Now finalized, the report offers one of the most comprehensive frameworks to date for addressing what has become a systemic threat to American households and the broader financial system. The Scope of the Problem: A Systemic Threat Frauds and scams are no longer isolated consumer protection issues. According to the report, U.S. households are losing an estimated $196 billion annually to scams — roughly $1 billion every couple of days. One in five American adults reports having lost money to an online scam. As Nick Bourke explained, today's scams are: · Technology-enabled · Highly organized and industrialized · Often operated by transnational criminal organizations · Accelerating due to AI and faster payment systems The so-called scam "lifecycle" includes four stages: 1. Lead – Hooking the victim 2. Deceive – Building trust (often through impersonation or relationship-building) 3. Bleed – Extracting funds 4. Clean – Laundering proceeds, often through cryptocurrency or offshore channels Different sectors see only fragments of this lifecycle; social media platforms may see the "lead," financial institutions the "bleed," and law enforcement the "clean." That fragmentation allows criminals to scale operations while defenders remain siloed. Why Scams Are Rising Despite Heavy Investment As Kate Griffin noted, industry and government are investing heavily in prevention. Yet scams continue to grow. Why? · Fragmentation across sectors: No single actor sees the entire attack sequence. · Outdated reporting infrastructure: Federal systems at agencies like the FBI and FTC remain manual and technologically antiquated. · Regulatory uncertainty: Financial institutions and technology platforms face unclear expectations about what data they can use and share. · Speed of modern payments: Faster money movement means faster losses. Joseph Schuster emphasized that many financial institutions are strongly incentivized to prevent fraud as they often bear reputational and financial risk when scams succeed. But legal ambiguity, especially under statutes like the Fair Credit Reporting Act, can chill data-sharing and innovation. Core Recommendations from the Aspen Report The report outlines both high-level national reforms and granular operational improvements with more than 180 specific ideas. 1. Elevate Scam Prevention to a National Priority The report calls for: · A designated federal lead (or "czar") to coordinate strategy · A whole-of-government approach · Clear national goals and metrics Without centralized leadership, enforcement and regulatory actions remain fragmented. 2. Modernize Law Enforcement Reporting Systems Federal reporting portals, including Suspicious Activity Reports (SARs), the FBI's complaint systems, and the FTC's databases, require modernization. The report recommends: · Streamlined, automated reporting · Backend data interoperability across agencies · Advanced analytics and AI tools for enforcement 3. Establish Clear Duties to Act Paired with Safe Harbors One of the most important themes discussed was the need for: · Clear expectations for banks, telecom companies, and digital platforms · Safe harbors that protect companies when sharing scam intelligence in good faith Countries like Australia have already codified such frameworks. The U.S. has yet to establish similarly coordinated standards. 4. Build a Cross-Sector Information-Sharing Ecosystem Effective scam prevention requires: · Exchange of scam indicators (malicious URLs, compromised phone numbers, device patterns) · Interoperable information-sharing platforms · Privacy-preserving architecture · Legal clarity to mitigate antitrust and consumer reporting concerns Joseph noted that industry appetite for collaboration is strong but clarity and guardrails are essential. 5. Consider a U.S. National Anti-Scam Center The report explores the idea of a centralized "front door", potentially something like stopscams.gov, that would: · Serve as a national reporting hub · Provide victim resources · Facilitate coordination among law enforcement · Support public education campaigns Social Media and Platform Responsibility The discussion also addressed the evolving role of digital platforms. Scam activity frequently originates through: · Paid advertisements · Dating applications · Direct messaging · Fake investment websites Compared to banks, social media companies operate within a less clearly defined regulatory structure. Courts are increasingly developing theories of "platform liability," but statutory clarity is lacking. The report urges policymakers to define reasonable expectations for platforms — paired with safe harbors and practical tools that empower prevention rather than merely assign blame. What Happens Next? The key question: who implements this strategy? Kate Griffin emphasized that this is a whole-of-society problem requiring coordinated action by: · Federal leadership · Congress · Financial institutions · Telecom and digital platforms · Law enforcement · Civil society There have been encouraging developments, including: · Treasury and State Department sanctions targeting transnational scam networks · A joint DOJ–FBI–Secret Service initiative targeting Southeast Asian scam operations o But much more remains to be done. Nick Bourke suggested that, one year from now, real success would include: · A designated federal anti-scam lead · A congressional commission · Measurable national prevention goals · Corporate adoption of formalized anti-scam strategies Joseph Schuster added that industry innovation is ongoing, particularly in artificial intelligence, biometrics, and authentication, but warned that fragmented state-level regulation could complicate progress. Key Takeaways Alan Kaplinsky closed the episode with several important observations: · Fraud and scams are now a systemic threat, not a niche compliance issue. · Prevention, not just reimbursement, must be the organizing principle. · Coordination matters as much as authority. · Good-faith companies need regulatory clarity, not just enforcement pressure. · Reducing scams strengthens trust in the U.S. financial system and digital economy. The Aspen report reframes the debate. Rather than assigning blame, it calls for aligned incentives, shared responsibility, and coordinated national action. If the title of the report, United We Stand, becomes reality, the United States may finally begin to bend the curve on one of the most costly and fast-growing threats facing consumers today. For more insights on consumer financial services developments, visit Ballard Spahr's Consumer Finance Monitor blog and explore the full Aspen Institute report here. Consumer Finance Monitor is hosted by Alan Kaplinsky, Senior Counsel at Ballard Spahr, and the founder and former chair of the firm's Consumer Financial Services Group. We encourage listeners to subscribe to the podcast on their preferred platform for weekly insights into developments in the consumer finance industry.