Generative AI (genAI) holds a great deal of promise for the banking and financial services industry.

However, the benefits of genAI — though far-reaching, complex, and promising — are tempered by emerging challenges and regulatory requirements. To apply genAI to their offerings, banks and financial institutions must first become familiar with a landscape that’s rapidly changing.

When applied to risk and fraud management, genAI tools can be especially useful. These tools can scan vast amounts of data, and they can identify instances of fraud that might go undetected by the human eye. By delegating rote tasks to genAI applications, companies can redirect their employees to tasks that require human innovation and thought.

Besides its prowess with structured data, genAI can also deftly interact with unstructured data. However, because the banking and financial services industry is more regulated than most, future regulations might limit genAI’s ability to make predictions, pinpoint investment opportunities, and assess risk. At the very least, genAI has already proven helpful in its ability to digest structured data and work alongside human experts. Its relevance in banking will only increase over time.

In a customer-facing role, generative AI can improve the relationships between customers and their bank. Because genAI tools are trained on vast amounts of data, they’re context-aware. Customer interactions (e.g., with a chatbot or with other natural language processing [NLP] functions) — even ones that don’t involve employee intervention — will benefit.

Here are some business benefits associated with applying genAI tools to banking services.

Fraud detection and prevention
The generation of content and ideas (e.g., via ChatGPT) related to business decisions
The analysis of numerical data for risk assessment and investment opportunities
The generation of call scripts (e.g., for employees’ conversations with customers or investors)
The generation of employee training manuals and modules

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