From automation to autonomy: the Agentic AI revolution in banking and FS

By Venkatesan R, Head – Core Banking Practice, Profinch Solutions

Automation, the first quiet ripple in banking’s digital evolution! And Agentic AI is the wave that’s now unmistakably cresting. Unlike earlier hype cycles where technology over-promised and under-delivered, this shift feels and is different. It’s not about banks doing the same things faster anymore. But it’s about banks reimagining what they CAN DO in the first place.

For a very long time, automation has been the industry’s dependable workhorse. Cleaning up reconciliations, routing service requests, and nudging transactions along their predefined lanes. Useful, yes. Transformative, not quite. It solved inefficiencies but rarely expanded possibilities. Agentic AI flips that equation on its head.

Instead of simply executing scripted tasks, AI “agents” can observe, reason, decide, act, and continuously improve, and that too, rapidly. They behave less like software and more like proactive digital colleagues. Those who work around the clock don’t get overwhelmed during quarter-end and can parse a 200-page regulatory circular before their coffee brews. Welcome to autonomy. And the BFSI sector is uniquely primed to benefit.

The Leap: From Automated to Autonomous

Traditional automation thrives in stable, predictable workflows. The moment the environment becomes dynamic (new customer intent, ambiguous data, shifting rules…), the system’s efficiency nose-dives. That’s where agentic AI shines, because it brings:

Contextual understanding

Agents don’t just “follow instructions.” They understand patterns, nuances, and the WHY behind a task. Example: a complaints-handling bot doesn’t only triage, it can infer emotional tone, assess urgency, check account history, and decide escalation paths.

Multi-step reasoning

Agents can plan, evaluate multiple scenarios, and choose optimal paths. Example: an agent can design a personalised saving plan based on spending behaviour and market forecasts, not just categorise transactions.

Autonomy with governance

They act independently but within well-defined boundaries. Banks get intelligence, with control. This is where the real magic begins. Without replacing teams, but amplifying human capability.

Where Agentic AI Is Already Redrawing BFSI Workflows

BFSI leaders have long dealt with the push-pull between improving operational efficiency and delivering quality customer experience. Agentic AI unlocks both without compromise.

Every efficiency gain seemed to come with trade-offs. Faster back-office came at the cost of flexibility, and personalised service required more people, not less. Agentic AI dissolves that long-standing tension. It introduces a new operating logic where workflows can be both intelligent AND fluid, both scalable and deeply personalised.

By understanding context, reasoning across multiple steps, and taking autonomous action, AI agents reshape processes end-to-end without forcing banks into the old “either-or” decisions. Instead of squeezing value out of existing workflows, agentic AI helps reinvent them while unlocking operational speed, accuracy, and customer delight simultaneously.

Here’s how:

1. Autonomous Customer Servicing

Imagine an AI agent that understands a customer’s question even when it’s vague, fetches account-specific information, processes intent (loan closure, limit increase, dispute resolution), runs eligibility checks, completes backend actions, and closes the service request end-to-end.

What traditionally took hours now becomes a seamless 30-second interaction. And the best part? The agent learns from every customer session and improves.

2. Compliance That Predicts, Not Reacts
   

Regulations shift often, and legacy systems struggle to adapt.

Agentic AI can:

• analyse new regulatory circulars the day they’re released,
• identify impacted processes,
• propose control changes,
• simulate risk exposure,
• and generate draft compliance reports.

This turns compliance from a costly defensive function into a strategic advantage.

3. Credit and Risk Decisions That Think Like Experts

Agentic models synthesise bureau data, internal behavioural patterns, macroeconomic signals, historical risk indicators, and sectoral stress to deliver human-like credit recommendations, with every decision fully explainable and rigorously transparent.

4. Autonomous Treasury Helpers

As co-pilots for treasury desks, AI agents are capable of:

• tracking market volatility,
• evaluating hedging strategies,
• alerting on liquidity drifts,
• suggesting allocation adjustments,
• and running simulations.

Not replacing judgment, just widening the radar.

5. Operations That Practically Run Themselves

Trade finance, reconciliation, dispute handling, and payments exception processing- these are ripe for agentic autonomy. Instead of rules-based systems that escalate everything, agents can self-resolve most cases using reasoning plus contextual learning.

Why BFSI Is the Ideal Playground for Agentic AI

If there’s any industry tailor-made for agentic AI, it’s financial services. FIs’ generate the perfect storm of conditions these intelligent agents thrive in massive volumes of data, high-stakes decisioning, tightly governed workflows, and an endless stream of complex cases that can’t be resolved by static rules alone.

But what truly sets BFSI apart is the groundwork already laid over the past decade. Financial services produce exactly what agentic AI thrives on. high volume data + high-stakes decisions + repeatable workflows + complex scenarios. But more importantly, the industry has been primed by years of digital adoption, CBS upgrades, API layers, RPA deployments, cloud shifts, and journey digitisation. The foundations are built.
Agentic AI is the layer that ties them all together.

Add to this:

• Real-time processing demands
• Customer expectations shaped by fintechs
• Operational cost pressures
• Regulatory scrutiny

…and you have an environment where autonomy isn’t just exciting, it’s inevitable.

Human + Agents: The Future Operating Model

A fear that often surfaces is: “Will AI agents replace jobs?”

The answer: they replace tasks, not roles.  Just like ATMs didn’t eliminate bank jobs but reshaped them, agentic AI will shift focus from transactional work to judgment, strategy, and empathy-led roles.

The future looks like this:

• Agents handle data-heavy, repetitive, decision-driven workflows.
• Humans handle exceptions, strategy, relationships, and creativity.
• Together, they operate at a level neither could achieve alone.

This is not man vs. machine. This is man and machine, finally at scale. Instead of asking ‘Should we adopt agentic AI?’, a better question will be: “Where can autonomy unlock the most business value this year?”

Some areas could be around:

• Which processes crumble under volume spikes?
• Where does your customer experience feel slow or disjointed?
• Which compliance functions are drowning in manual reviews?
• What insights are we not leveraging because of bandwidth?

Final Word, A New Era of Possibility

Agentic AI is not another tech buzzword waiting its turn to fade. It’s the beginning of autonomous banking, where systems anticipate instead of react, where processes adapt instead of breaking, and where decisions become faster and more ‘trust’-worthy. Banks and FIs that embraced automation gained efficiency. Banks and FIs that embrace autonomy will gain an advantage. This is the revolution that’s far bigger than just cost optimisation. Started perhaps with a ripple, and is becoming a wave. The question is, will you be ready to ride it?