Generative AI in Financial Institution: A Global Survey of Opportunities, Threats, and Regulation

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Authors: Bikash Saha, Nanda Rani, Sandeep Kumar Shukla

Published: 2025-04-30 12:25:30+00:00

AI Summary

This global survey examines the adoption of Generative AI (GenAI) in financial institutions, analyzing its opportunities and threats. It explores GenAI's applications across various functions, including customer engagement, risk management, and compliance, while highlighting emerging cybersecurity risks like deepfakes and adversarial attacks. The survey also delves into the evolving global regulatory landscape and proposes best practices for secure and responsible GenAI adoption.

Abstract

Generative Artificial Intelligence (GenAI) is rapidly reshaping the global financial landscape, offering unprecedented opportunities to enhance customer engagement, automate complex workflows, and extract actionable insights from vast financial data. This survey provides an overview of GenAI adoption across the financial ecosystem, examining how banks, insurers, asset managers, and fintech startups worldwide are integrating large language models and other generative tools into their operations. From AI-powered virtual assistants and personalized financial advisory to fraud detection and compliance automation, GenAI is driving innovation across functions. However, this transformation comes with significant cybersecurity and ethical risks. We discuss emerging threats such as AI-generated phishing, deepfake-enabled fraud, and adversarial attacks on AI systems, as well as concerns around bias, opacity, and data misuse. The evolving global regulatory landscape is explored in depth, including initiatives by major financial regulators and international efforts to develop risk-based AI governance. Finally, we propose best practices for secure and responsible adoption - including explainability techniques, adversarial testing, auditability, and human oversight. Drawing from academic literature, industry case studies, and policy frameworks, this chapter offers a perspective on how the financial sector can harness GenAI's transformative potential while navigating the complex risks it introduces.

Key findings

GenAI offers significant opportunities for financial institutions, enhancing customer engagement and automating tasks. However, it also introduces substantial cybersecurity risks, including deepfake-enabled fraud and adversarial attacks on AI systems. Global regulators are responding with various approaches to mitigate these risks, emphasizing principles-based guidelines, risk-based regulations, and collaborative sandboxes.

Approach

The authors conduct a global survey of GenAI adoption in the financial sector, examining its applications, benefits, and risks. They draw upon academic literature, industry case studies, and policy frameworks to provide a comprehensive overview and propose best practices for secure and responsible implementation.

Datasets

UNKNOWN

Model(s)

UNKNOWN

Author countries

India

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