How agentic AI is shaping the next phase of the BFSI sector

Across the world, banking as an industry is undergoing significant transformation thanks to autonomous AI systems. In India too, our banking, financial services, and insurance (BFSI) sector is entering a new era, driven by agentic AI. 

As a new class of artificial intelligence (AI) systems that can mimic human decision-making to solve problems in real-time, agentic AI is poised to fundamentally reshape how Indian financial institutions operate, serve customers, and manage risk.

While conventional AI models mainly rely on human prompts to take action, the autonomous capability of agentic AI makes it much more advanced. While aligning with predefined rules and policies, agentic AI can collaborate, learn, adapt, and operate across systems, making it a powerful agent in a high-volume, data-intensive industry like BFSI. 

Why the Indian BFSI industry needs agentic AI

The current generation of Indian customers are much more demanding than before. Being tech savvy, they need faster turnaround and more personalised experiences. This puts the BFSI industry under immense pressure. 

As operational costs continue to rise, regulators are also tightening compliance and reporting. While automation did transform the BFSI sector to a certain extent, surface-level inefficiencies mostly remained unaddressed. This was compounded by core issues such as fragmented systems, slow decision-making, and reactive risk management. 

It is these very challenges that are being addressed by agentic AI today. For instance, agentic AI can autonomously manage KYC, sanctions screening, risk profiling, and customer engagement, while escalating for human review only when necessary. The result is faster onboarding, reduced friction, and hyper-personalised product recommendations based on real behaviour and profile data. 

In digital banking and payments, AI agents can continuously monitor transactions and adapt to anomalies, freezing suspicious flows and alerting stakeholders instantly. By managing dynamic risk profiles and automatically adjusting flags and thresholds, these systems mitigate fraud and operational risk far more effectively than conventional approaches.

AI agents can also monitor regulatory changes, update internal policies, generate audit-ready reports, and flag inconsistencies, without needing any human intervention. In addition, they can anticipate system failures, rebalance workloads, and reroute processes, enhancing uptime and reliability.

A network of digital agents can operate independently, with the ability to collaborate, delegate, and escalate when needed. This seamless working allows institutions to move beyond task automation towards intelligent, self-optimising systems. 

The opportunity for India

India’s digital and regulatory environment uniquely positions it as a global testbed for agentic AI in finance. Indian banks and insurers are already adopting agentic automation at scale. The rising demand for intelligent process automation in Indian enterprises, even beyond BFSI, reflects broader confidence in real world returns from AI agents. Major banking institutions are piloting or exploring agentic systems to boost efficiency across workflows. 

Nonetheless, deploying agentic AI at scale is not without hurdles. The risks, right from autonomy outpacing oversight to unintended API chaining causing system failures, are real, and require robust technical guardrails, governance frameworks, and organisational accountability. The autonomy of agentic systems introduces new challenges—ranging from decision traceability and privacy risks to unintended goal pursuit and API misuse.

Data integrity, bias mitigation, explainability, and regulatory compliance are non‑negotiables. Financial institutions must pilot in low‑risk contexts and build up systematically, while also ensuring human oversight remains central. Building responsible AI governance frameworks that are transparent, explainable, and human-on-the-loop is crucial. This means ensuring that AI agents act within clearly defined guardrails, and that their actions are always auditable and aligned with regulatory expectations.

All things considered, agentic AI represents more than just the next phase of digital transformation; it’s a structural shift in how BFSI institutions think, act, and evolve. By combining autonomy with accountability, these intelligent agents offer a path to faster, safer, and more customer-centric financial services.

With the right approach to agentic AI, the sector is well-positioned to embrace this bold new era.

The author is Managing Partner, IBM Consulting India & South Asia.