Publications
The Next Wave Arrives: Agentic AI in Financial Services
Market Scan
Report Summary
This report provides an overview of agentic artificial intelligence (AAI) applications—dynamic AI systems that can be structured to respond to new information and make and execute decisions without ongoing human engagement—as adoption accelerates in financial services and e-commerce.
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.
The paper outlines challenges that are affecting the pace of adoption in the financial sector and risks that poorly performing AAI systems could pose to consumer and small business users, individual financial services providers, and broader financial stability. It also identifies critical questions for different types of stakeholders about how to realize AAI’s benefits while guarding against errors and abuse.
Acknowledgments
This market scan is part of FinRegLab’s ongoing work to inform both market practice and policy to promote the responsible and inclusive use of AI and machine learning systems across financial services. This work is supported from FinRegLab’s general operating funds.
We would like to thank the many stakeholders in the technology, banking, fintech, research, civil society, and government sectors who engaged in interviews and conversations and provided feedback on this report. We would also like to acknowledge the FinRegLab team for their work in writing this report:
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.
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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.
About FinRegLab
FinRegLab is an independent, nonprofit organization that conducts research and experiments with new technologies and data to drive the financial sector toward a safe and responsible marketplace. The organization also facilitates discourse across the financial ecosystem to inform public policy and market practices. To receive periodic updates on the latest research, subscribe to FRL’s newsletter and visit www.finreglab.org. Follow FinRegLab on LinkedIn.
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