The era of unconstrained banking: Redefining India’s financial future

India is entering an era of unconstrained banking whereby AI, open financial ecosystems, and future-ready talent can fundamentally reinvent how value is created and delivered and remove longstanding capacity constraints. Built on a strong digital foundation, progressive regulation, and a commitment to inclusion, the sector is now being engineered at its core. This is no longer an incremental improvement; it is a complete transformation of how banks operate, compete, and serve customers. 

Let’s take a look at the top trends shaping the future of Indian banking.  

1. Intensifying the battle for the balance sheet 

Indian banks are entering a new competitive reality where control over customer engagement is slipping fast. The UPI-led payment interaction has given non-banks daily access to customers, raising the risk that banks become invisible balance sheet utilities rather than primary financial partners. At the same time, credit growth is being driven by data-rich players who underwrite faster using alternative data, challenging traditional models. With Unified Lending Interface (ULI) set to shift lending discovery and distribution to marketplace platforms, banks may increasingly operate in the background through exposed Business Rule Engine (BRE) Application Programming Interface (APIs), integration with the rapidly growing digital data and services ecosystem, and balance sheets. 

As customers become more financially aware and digitally empowered, sustained long-term loyalty to a single institution is under pressure. New age investment platforms offering SIPs, bonds, and REITs are already diverting funds away from traditional deposits, bringing a structural change to banking in India. It is reflected in non-interest income rising to 32%, according to the latest RBI FSR, compared with a higher share in other global markets. 

Banks need to act decisively as fintechs and NBFCs raise the bar with rapid product and service innovation—making it clear that what has worked so far won’t work in the future. To stay competitive, banks should defend their core with new offerings that reward loyal customers, such as accelerated rewards tied to higher deposit balances or linked savings-loan products that reduce borrowing costs, while going on the offensive with AI-driven deposit optimisation, wealth guidance, and personalised credit. In this context, the focus on product innovation will be even more critical to meet evolving customer expectations and counter the shift towards alternative platforms. By strengthening internal capabilities and rethinking how value is delivered, banks can stay ahead of a fast-changing marketplace. 

2. Moving beyond apps into intent-driven experiences 

Customer expectations are shifting rapidly as AI becomes embedded in everyday life. Banking is no longer limited to websites or apps; it must appear wherever customers are, including within external AI platforms. Soon, personal AI agents will manage tasks like comparing loans or coordinating life event journeys, such as buying a home or car. 

To keep pace, banks need to build unified intent engines that blend agentic and conversational AI while ensuring apps and AI agents evolve side by side. While apps will remain the customer’s control centre, embedded AI agents will take on proactive tasks—like flagging an upcoming FD maturity in-app and suggesting reinvestment options for the customer to approve. This shift from User Interface (UI)-led to agent-first design demands standardised documentation, structured data, transparent conditions, and callable APIs that enable seamless agent-to-agent interactions. Combined with modernised physical formats and life event ecosystems, these changes will create intuitive, intelligent experiences that firmly place banks back at the centre of customers’ financial lives. 

3. Paying a high cost for technological inaction 

For years, banks have paid the hidden price of “low cost” tech—prioritising frontend digital features while deferring core modernisation. The result is a heavy load of tech debt, rising complexity, and nearly 70% of IT spend going into simply keeping legacy systems alive. With tech costs routinely outpacing banking revenues, modernisation is now a race, not a choice. For Indian banks, AI, open source, and automation offer a rare chance to simplify highly customised legacy cores through incremental, lower risk upgrades rather than disruptive replacements. At India’s scale, simplification is essential for resilience, uptime, and regulatory confidence. 

To break free from legacy complexity, they need to embed GenAI across the development lifecycle and accelerate open-source adoption for non-differentiating layers to drive speed, standardisation, and efficiency. Streamlining tech estates is equally critical: reducing hardware and operating systems complexity by consolidating vendors, diversifying workforce capabilities, and establishing governance protocols for AI agents. To truly drive value from agentic AI, banks will need to revisit and update product and risk policies to align with the new operating reality. Increasingly, banks must now treat AI and engineering as core competencies and look to strengthen their in-house capabilities and talent, converting technology from a maintenance burden into a durable competitive advantage. The cost of inaction is now far greater than the cost of transformation. 

4. Reinventing work, worker, and workplace 

The most profound shift ahead lies in how work is being reshaped. Agentic AI could enable “10× banks,” where one employee directs a team of AI coworkers across operations, sales, compliance, and credit—dramatically expanding capacity and precision without proportional cost increases. In a human-AI workforce model, the marginal cost of scaling drops sharply, compared to the linear growth of the past. The real barrier now is skilling: technology is advancing faster than workforce capability, and traditional training rarely delivers day-to-day impact. Banks need a unified, outcome driven learning ecosystem that equips leaders to set the AI vision, users to apply it confidently, and builders to design responsible, explainable systems aligned with RBI’s FREEAI framework. Co-learning, where employees and AI agents learn and adapt together, will be essential. Institutions that invest in this shared capability model will unlock India’s largest value pools: higher frontline productivity, faster decisions, and stronger business outcomes at a fraction of historical scaling costs. 

5. The trust continuum: Defining the road ahead  

As digital payments and instant credit scale, trust has become the real currency of Indian banking, and restoring it is essential. With rising fraud undermining confidence, banks need to proactively strengthen their security posture by deploying AI-led fraud intelligence and real-time intervention engines that detect anomalies, integrate Digital Payments Intelligence Platform (DPIP) checks, and trigger step-up authentication. The decade ahead will separate banks that lead from those that lag: institutions that modernise early, safeguard trust, embrace agentic AI, and build open, interoperable ecosystems will redefine customer experience and reclaim the core relationship. Banking’s values will endure, but the banks that act now will shape the future of unconstrained growth. 

(The author is MD and lead–financial services, Accenture in India. Views are personal.)