5 Use Cases of Generative AI In Banking

The use of generative AI in banking can also help borrowers with problems related to loan service

Automating the lending process is possible with generative AI. When used in a risk-controlled setting, it can give the ability to make effective, risk-based credit decisions. With the help of technology, banks have a rare chance to improve customer service and streamline their lending operations.

1. Marketing and Lead generation: Chatbots powered by generative AI may communicate with potential customers and learn about their needs and preferences. Banks can utilize generative AI to generate tailored recommendations for lending products based on customer profiles.

2. Loan Application: Moreover, generative AI-based chatbots can assist clients in completing forms and responding to queries as they move through the loan application process. Also, by having a discussion with customers in natural language, generative AI can be used in banking to confirm consumer data.

3. Credit Analysis: Credit analysts can utilize generative AI to analyze consumer credit ratings and financial histories to determine a customer's creditworthiness. Additionally, it may assess data from a variety of sources to gauge the riskiness of a loan application.

4. Loan Underwriting: A decision-support tool for loan underwriters is generative AI. Customer data can be analyzed by the technology, which can then use its risk analysis to offer tailored suggestions. Automation of specific credit note parts is possible with generative AI. The executive summary, business description, and industry analysis are a few of them.

5. Loan Servicing: The use of generative AI in banking can also assist borrowers with problems related to loan servicing. In particular, account management, billing questions, and payment reminders can be helped by generative AI. Based on their financial history, it can also tailor recommendations for debt payback.