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Financial Services

An Introduction: Generative AI Use Cases for the Financial Services Industry

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What is Generative AI?

Generative Artificial Intelligence, or generative AI, is a categorical or descriptive term ascribed to algorithms using machine learning to create or “generate” new content.

Generative AI ingests data and understands guidelines incredibly well. Therefore, businesses across industries are optimistic about the many ways it can help save them money and create elevated, uber-personalized customer experiences. Highly regulated industries, such as the financial services industry, are especially interested in exploring how generative AI can support ever-transient regulatory and data governance demands.

Financial Services Business Use Cases for Generative AI

Where a marketing director for an insurance company might encourage their designers to use generative AI to spice up its newest Instagram ad, a chief technology officer at a bank could use generative AI to analyze enormous sets of financial data and generate new outlooks that can be leveraged to improve fraud detection and risk management.

Here are other ways the financial services industry can employ generative AI to improve business efficiency and enhance customer experiences:

Superior Visibility into Financial and Customer Insights 

Given the financial services industry’s seemingly infinite pools of data, generative AI’s ability to use data to train large language models (LLM) works very much in the industry’s favor. An institution can use data to tailor LLM and maintain a business-critical pulse on where it stands in the market against competitors.

Risk Management, Anti-Money Laundering, & Fraud Protection

Financial institutions invest heavily in security and risk management, but prevention and recovery progress are delayed by manual reporting and disparate systems. With generative AI, reports can be autogenerated and organized, and natural language processing (NLP) can be used to catch the “red flags” that signal crime, fraud, and reputation-threatening errors. For example, using generative AI image analysis, one can determine if an image has been altered, which helps control insurance fraud and identity theft. Using generative AI for such purposes gives human resources more bandwidth to thoroughly investigate suspicious incidents.

Smart Personalization

Financial institutions can use generative AI to perform in-depth analyses of customer spending behaviors, providing the insights needed to create tailored recommendations and customized products. It can also be used to improve accessibility and “mirror” the tone and conversation style of a customer in communication channels, leading to increased customer satisfaction.


Our financial services and data experts are here to help. If you want to learn how generative AI can be leveraged for your company, consider our CX AI jumpstart.

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Kevin Colletti, Director, Digital Strategy & Innovation

Kevin Colletti is Director of Digital Strategy at Perficient. He has extensive experience working with client senior management teams to develop innovative digital strategies driven by measurable results. Creating simplified digital solutions out of complex client problems is where he thrives the most.

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