While the current hot topics regarding artificial intelligence (AI) and machine learning focus on how these cutting-edge technologies can help streamline operations in the debt buying and debt collection space, an area worth emphasizing is how to be mindful of the data privacy implications of these tools, and also how they can also be used to bolster consumer protection.
Artificial Intelligence and Data Privacy
As a recent article in the Harvard Business Review noted, businesses are increasingly using artificial intelligence to supplement or even replace decision-making once left to humans.[1] Artificial intelligence models can rely exclusively on public or anonymous information, like case law, statutes, and public filings. But artificial intelligence models can also use consumer information, which bring data privacy laws into play.
Within the consumer financial services industry, several federal laws and regulations govern the use of certain consumer information by covered entities. At the top of this list is the Gramm Leach Bliley Act (GLBA) and its recently amended Safeguards Rule. Notably, the federal Fair Debt Collection Practices Act also regulates the disclosure of consumer information. Additionally, a growing number of states are enacting their own comprehensive consumer privacy laws.
When artificial intelligence models rely on consumer information, they can be subject to these federal and state laws. The result is that AI Governance should be a part of a robust compliance management system. At the very least, AI Governance should address the risks of unintended disclosure or use of consumer information by a company’s artificial intelligence models under applicable federal and state law.
Leveraging Artificial Intelligence to Enhance Consumer Protection
Below are some ways that this technology can be harnessed to ensure strengthened and more efficient adherence to consumer protection laws, ultimately fostering a more transparent and equitable financial landscape.
Proactive, intelligent risk assessments that can more quickly identify vulnerabilities
Artificial intelligence and machine learning algorithms excel at analyzing vast datasets to identify patterns and trends. In the context of our industry, these technologies can be employed to conduct thorough risk assessments. By scrutinizing historical data, algorithms can quickly pinpoint potential vulnerabilities and gaps in processes, including those involving data and customer privacy. This allows companies to spend more time fixing any potential gaps by reducing the time and effort needed to identify them. The ability to more proactively address issues before they escalate fosters an environment that is more conducive to consumer protection.
Tailored and compliant outreach efforts through personalized communication strategies
One of the challenges in this industry is striking the right balance between successful communication strategies and sensitivity to consumer preference and legal/regulatory restrictions. Not only can artificial intelligence and machine learning enable the customization of communication strategies in real time based on individual consumer behaviors and preferences, but these tools can do so through an automated and intelligent method that is compliant with the many laws and regulations that govern the accounts receivables space. The added bonus? Artificial intelligence and machine learning tools are far less susceptible to human error, greatly diminishing the number of unintentional mistakes.
Streamlining regulatory compliance through automated measures
Navigating the complex web of constantly changing laws and regulations in the debt buying and debt collection space can be daunting. Artificial intelligence and machine learning technologies offer a solution by automating compliance measures. These systems can constantly monitor regulatory changes, adapt processes accordingly, and ensure that every facet of a company’s process and strategy aligns with the latest consumer protection laws. This not only mitigates the risk but also demonstrates a commitment to compliant practices.
Conclusion
The integration of artificial intelligence and machine learning technologies by debt buyers and debt collectors represents a transformative leap towards better consumer protection. Incorporating AI Governance into compliance management systems and adding consumer protection bolstering uses of these tools in tandem with what was previously discussed in the earlier articles in this series, the industry’s implementation of these technologies has a very broad upside for everyone involved – companies, regulators, and most importantly consumers.
[1] https://hbr.org/2023/10/how-ai-can-help-leaders-make-better-decisions-under-pressure, archived at https://perma.cc/XS8X-RB44