# Banking & Finance ### **KYC verification automation** Automate KYC verification process for banks so as to be able to scale for large number of customers. ### **Credit Card Transaction Fraud** Predict if a given transaction is fraudulent or not. This can be challenging since only a small percentage of transactions is fraudulent and flagging genuine transactions often can create a negative customer experience. ### **Loan Default Prediction** Predict if a given customer is going to default on a loan product or not, before even handing out the loan. Must ensure such models are non-discriminatory and free from bias. ### **Portfolio Optimization** Predict the optimal allocation of funds against the various investments, given the varying risks and rates of return. ### **Credit Risk Assesment** Assess the potential credit risk of entities / individuals before signing up for a banking product. ### **Customer Churn Prediction** Predict which customers are at the risk of churning based on various characteristics and transactional behavior. ### **Anomaly detection for Money laundering** Identify potential instances of money laundering from transactional and customer information ### **Facial Recognition** Identify individuals from images and videos, allowing for more accurate and efficient security screening and monitoring. ### **Fraud Detection** Analyze financial transactions and identify patterns of fraudulent behavior, reducing the risk of financial losses. ### **Customer Service** AI-powered chatbots can provide quick and efficient customer service, answering common queries and resolving issues without the need for human intervention. and many more --- # Agent Instructions: Querying This Documentation If you need additional information that is not directly available in this page, you can query the documentation dynamically by asking a question. Perform an HTTP GET request on the current page URL with the `ask` query parameter: ``` GET https://eigenmaps.gitbook.io/eizen-generative-ai/use-cases/banking-and-finance.md?ask= ``` The question should be specific, self-contained, and written in natural language. The response will contain a direct answer to the question and relevant excerpts and sources from the documentation. Use this mechanism when the answer is not explicitly present in the current page, you need clarification or additional context, or you want to retrieve related documentation sections.