India's digital financial ecosystem spans banks, non-banking financial companies, insurers, payment providers, lending platforms and wealth services. AI can improve service operations and help analysts review patterns, but financial decisions require governance, explainability, privacy controls and compliance with applicable rules.
Financial institutions should distinguish low-risk productivity assistance from regulated decisions such as credit underwriting, claims settlement, fraud intervention and investment advice. Models should be tested for bias, false positives, data leakage and the ability to explain decisions to customers and regulators.
What fintech, banks and insurers can achieve
- Draft clear customer FAQs, product explanations and service messages with ChatGPT, ensuring rates, fees, eligibility and terms are verified by the institution.
- Summarise approved policy documents, product manuals and internal knowledge with NotebookLM, restricting access to authorised material.
- Organise customer-service workflows for routine account and policy questions with Intercom Fin, with secure authentication and human escalation for disputes or sensitive requests.
- Research regulatory updates and industry developments using Perplexity, then verify requirements against the regulator's official publications and legal advice.
- Prepare compliance training and product presentations using Gamma.
- Analyse aggregated website acquisition and campaign journeys with Google Analytics, subject to consent, privacy and institutional policy.
- Use specialist, validated systems for fraud detection, AML monitoring, identity verification and claims triage. Do not use a general-purpose chatbot to approve loans, move funds or provide personalised investment recommendations.