Reinventing financial services: The opportunity lies in smarter decisions

India's financial services are transforming with AI-driven decisions to enhance customer engagement, reduce fraud, and improve financial outcomes, leveraging digital infrastructure and responsible governance.

India's financial services industry has spent the past decade proving that digital infrastructure can operate at extraordinary scale. Payments moved from queues to QR codes, financial inclusion accelerated, and financial services became part of everyday digital journeys. In FY2025-26 alone, UPI processed more than 24,161 crore transactions worth Rs 314.23 lakh crore and served more than 55.49 crore individuals and 6.5 crore merchants. The next challenge is to turn that reach into better financial decisions.

But digitisation is no longer the destination. BFSI's next competitive shift will be defined by how effectively institutions use AI across customer engagement, products, risk, regulation and operations. Automation makes a task faster. AI can make a decision more contextual, timely and useful. Lasting advantage will come from redesigning how decisions are made across the enterprise.

Many institutions still operate digital versions of legacy models. A loan application may be submitted online, while the credit decision relies on fragmented information and manual follow-ups. A chatbot may answer routine questions, while a relationship manager lacks context on the customer's broader financial need.

AI can move intelligence closer to the point of decision -- not by removing humans from the loop, but by improving judgment. India's next financial-services advantage will come from converting trusted, consented data into better decisions.

Generative AI has captured executive attention but deploying tools does not make an institution AI-driven. The test is whether AI becomes a repeatable capability across customer engagement, underwriting, collections, finance, HR, risk and regulatory processes.

Value compounds when institutions replace disconnected pilots with reusable foundations for data, models, controls, orchestration and auditability. Agentic systems can summarise information, execute pre-approved tasks, and coordinate journeys, but only on governed data, with clear permissions and with human oversight.

AI must become an operating capability, not a collection of isolated tools. In financial services, trust is an operating requirement. Governance cannot sit downstream of innovation. As AI systems gain greater autonomy, security must be designed in from the start -- protecting sensitive data, controlling access and continuously monitoring for anomalous activity. Leaders should ask: Where is AI used, and who is accountable? Is it creating measurable value? Can the institution explain and challenge its role in a decision?

India's regulatory direction is becoming clearer. The RBI's FREE-AI Committee proposed seven principles and 26 recommendations, including board-approved policies, lifecycle governance, consumer disclosure, incident reporting, an innovation sandbox and indigenous financial-sector models. Payments Vision 2028 also calls for an AI-led, data-driven payments ecosystem centered on trust, fraud safeguards and resilience.

For financial services institutions, measures should extend beyond productivity to fraud-loss reduction, decision time, complaint resolution, advisor effectiveness and retention. Human accountability remains essential in credit, claims, collections and fraud.

Responsible AI is not a brake on adoption; governance is what allows it to scale. The real measure is better customer outcomes. For India, productivity alone is too narrow a measure of success. AI can support multilingual services, improve MSME credit workflows, strengthen fraud detection at UPI scale and give frontline employees better context.

This matters where language, geography, volatile incomes and thin credit histories can shape access. At Tamilnad Mercantile Bank, Oracle Fusion Cloud Applications have unified finance, HR, sales and customer service. Embedded AI and automation help employees handle twice as many service requests in half the time. Some Indian NBFCs use OCI Data Science and Oracle Autonomous AI Database to enhance credit scoring and accelerate loan processing.

India already has deep digital rails, a diverse customer base, expanding AI capacity and a regulatory focus on responsible adoption. The challenge is execution: governed data, secure architecture, industry-specific models, effective oversight and flexible deployment choices around residency, sensitive information, monitoring and audit.

Technology providers have a role, but AI should not become another bolt-on layer. The opportunity is to connect applications, data, infrastructure, industry workflows and controls so intelligence operates consistently across the enterprise. The winners will not be the institutions that deploy the most AI. They will be those that use it most effectively to make better decisions, strengthen trust and deliver better financial outcomes.