Projects
Agentic AI in Financial Services
Overview
Even as financial firms and commerce platforms wrestle with the implications of machine learning and generative AI for their businesses and customers, the next wave is already arriving. Agentic artificial intelligence (AAI) systems can be structured to respond dynamically to new information and make and execute decisions without ongoing human engagement.
In addition to simplifying and personalizing online shopping and payments, these systems have the potential to revolutionize real-time fraud and cyber defense, streamline lending and insurance processes, and provide personalized, 24-7 digital assistants that help consumers manage their daily finances and build wealth over time. Yet while AAI could impact practically every layer of personal and institutional finance, the technology has been advancing faster than data infrastructures, business practices, and regulatory frameworks.
FinRegLab has published a market scan analyzing potential use cases, challenges to adoption, risks, and critical questions. We are actively monitoring developments and considering follow up research projects to evaluate benefits and risk mitigation techniques for this powerful technology.
Related Publications
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This landscape paper details gaps in traditional systems that both make it difficult for millions of consumers to access financial services and for financial institutions to detect and protect against bad actors.
LEARN MORE: Innovations for Identity Proofing and Transaction Monitoring: Advancing Financial Inclusion Through Data & Technology -
This policy analysis explores the regulatory and public policy implications of the increasing use of machine learning models and explainability and fairness techniques for credit underwriting in depth, particularly for model risk management, consumer disclosures, and fair lending compliance.