Common generative AI use cases in banking include:
Customer service and support: Generative AI-powered chatbots and virtual assistants can handle a multitude of customer inquiries, providing instant responses and personalized assistance. These AI systems can answer questions about account balances, transaction histories and financial advice, improving customer satisfaction and reducing the workload on human support teams.
Credit approval and loan underwriting: AI integration in credit scoring and risk assessment allows for accurate evaluation of credit scoring, credit risks, improving decision-making in loan applications and credit card issuance. In loan underwriting, generative AI can automate the creation of credit memos, including executive summaries and sector analyses, speeding up the process and reducing manual effort.
Debt collection: AI can aid in debt collection efforts by interacting with borrowers to provide repayment options, identify patterns of delinquency and recommend appropriate collection strategies, improving recovery rates and customer relationships.
Fraud detection and prevention: Generative AI can analyze large volumes of transaction data to identify unusual patterns and potentially fraudulent activities. By continuously learning from new data, these AI systems become more accurate over time, helping banks to proactively detect and prevent fraud such as account takeover (ATO) and money laundering.
Personalized marketing and lead generation: AI-based systems can interact with potential clients to understand their needs and preferences, creating personalized product recommendations. This targeted approach improves marketing efficiency and enhances customer acquisition efforts.
Pitchbook creation: Pitchbooks are sales presentations that a bank uses to persuade a client or potential client to purchase the bank’s services. Generative AI can gather, process and summarize information from various sources to quickly create these pitchbooks.
Regulatory compliance and reporting: Generative AI can assist in summarizing and preparing regulatory reports, ensuring that banks stay compliant with industry regulations. It can automate the extraction and organization of relevant data, reducing the time and effort required for compliance tasks.
Risk management: Generative AI can analyze market trends, financial indicators and credit histories to provide more accurate risk assessments. This ability helps banks make better-informed decisions about lending, investments and other financial activities.