Badri Devalla
For years, digital transformation in banking has been described in the language of customer journeys. The goal was straightforward: map the steps a customer takes, digitize as many as possible, and knit the touchpoints together into a seamless experience.
That approach created undeniable improvements. Customers can now open accounts from their phones, apply for loans online, and chat with bots instead of waiting in queues. But loyalty hasn’t followed. Challenger banks and fintechs, with far smaller budgets, continue to outpace incumbents in satisfaction and retention. A smoother app is not loyalty when one broken step in a journey is enough to send customers elsewhere.
The problem here is not the intent or lack of digitization but a deeper architectural flaw. While focusing on journeys banks have forgotten a very important truth – journeys are linear, trust, however, is circular. Trust builds through loops where every interaction strengthens the next. A quick approval feeds confidence, confidence increases engagement, engagement produces richer data, and richer data powers sharper decisions. Journeys can deliver convenience but only loops can sustain loyalty.
And in the age of agentic AI driving autonomous actions, loops aren’t just preferable, they’re non-negotiable.
Autonomy as a Stress Test
Agents are not constrained to one journey or system. Unlike traditional automation, which executed deterministic rules, agents can interpret, reason, and act across processes. An agent reviewing a loan application, for instance, might pull credit bureau data, cross-check tax filings, verify customer identity, and initiate disbursement.
This dynamism promises major gains:
- Loan approval that once took weeks can be reduced to days. Agents ingest bureau scores, simulate cash flows, and propose terms while compliance checks run in parallel. McKinsey estimates that agentic AI could compress SME lending timelines dramatically, widening access for underserved firms.
- A salary deposit is no longer just a cleared transaction. Platforms can orchestrate across savings, credit, and advisory systems to trigger contextual nudges – from high-yield savings to micro-investment plans.
- Clients can receive investment advice that reflects market shifts, liquidity needs, and tax rules in real time. BCG finds that banks embedding AI into wealth workflows are delivering personalization at scale that previously required armies of advisors.
- Instead of drowning in false positives, risk teams can see prioritized cases with full provenance.
But the same quality that makes agents powerful also makes them unforgiving. They don’t stay neatly within siloed journeys; they move laterally across systems. If those systems contradict one another or lack governance, the agent doesn’t reconcile the inconsistency it magnifies it.
That is why loops matter more than ever. Agents need environments where data, governance, and decisions are consistent and compounding. Without that, autonomy stops being a productivity boost and becomes a stress test exposing fragility.
If Loops Are The Future, Why Aren’t Banks Able To Deliver Them?
The short answer: fragmentation.
Banks have made enormous strides in digitization, yet fragmentation remains the industry’s defining constraint. Credit decisions still take weeks because customer data is scattered across bureaus, tax filings, and internal systems. Fraud alerts overwhelm compliance teams because monitoring tools operate in silos. Wealth advisors spend more time gathering information than advising clients.
The issue is not investment – we all know the industry has spent billions on digital transformation – it is architecture. As digital capabilities evolved, each wave of technology was layered on top of the last: RPA for efficiency, mobile apps for convenience, SaaS for speed, and so on. These additions created value locally, but collectively left institutions structurally brittle. In an era where intelligence itself is becoming part of the financial enterprise’s infrastructure, that brittleness is no longer sustainable.
The scale of the problem is staggering. One North American bank juggling over 1,000 applications estimated its technology debt at more than $2 billion annually. Another bank nearly spent $100 million to retire a single outdated platform, only to realize it was so tightly interwoven with other systems that removing it would solve little. These examples underscore how deeply entrenched IT sprawl has become.
Fragmentation, however, is only part of the challenge. Banks also face weak guardrails, where autonomy without accountability risks compliance breaches. Scaling remains elusive, with 75% of banks stuck in pilots and proof of concepts. And even when agents perform, a trust deficit stalls adoption: employees second-guess outputs and regulators demand transparency systems cannot yet provide. Together, these hurdles explain why promising demos rarely translate into production value.
The opportunity (and the challenge) is to re-architect banking around unified platforms designed for autonomous intelligence. Done right, this will help banks and financial institutions leap beyond incremental productivity and move the needle on more customer aligned outcomes – faster credit, sharper compliance, more personalized wealth, and continuous customer relationships built on trust.
Opening the Door For Autonomy with Unified Platforms
Unified platforms are the modern structural backbone that allows loops of trust to actually function with a maze of legacy systems.
Three qualities make them essential.
- First, they create a single, coherent environment for agents to operate. Today, a credit decision may require pulling tax filings, bureau scores, and internal records – each in a different format, governed by different rules. A unified platform provides the policy-aware interface that makes those sources interoperable, so agents don’t stall or contradict one another.
- Second, they provide governance at the point of action. In an autonomous environment, compliance can’t be retrospective. Platforms embed lineage, masking, and auditability directly into workflows. This is how regulators can demand real-time transparency into a sanction check or loan decline and get it.
- Third, they enable scaling without fragmentation. The problem with today’s pilots isn’t that they fail; it’s that they can’t be replicated. Each is built differently, with bespoke integrations and oversight. Platforms supply the orchestration layer that manages agent lifecycles, standardizes tools, and allows models to be swapped or optimized without rebuilding the house each time.
And the most advanced platforms go one step further: they balance human oversight with autonomy. They allow banks to progress gradually from direct supervision, to occasional intervention, to trusted independence with seamless handoffs between agents and employees. This allows leaders to build confidence inside the institution and credibility outside it.
BOX: The Leadership Imperative
- Stop pouring energy into optimizing linear journeys. They collapse the moment autonomy pushes against them.
- Start designing loops of trust. Closed systems where data, governance, and decisions reinforce one another – creating resilience rather than leakage.
- Elevate platforms from IT investments to strategic infrastructure. They are the architecture of trust in the age of autonomous intelligence.
- Govern agents as enterprise assets, with identity, accountability, and transparency built in. And redeploy human expertise where it matters most: shaping products, building ecosystems, and strengthening customer relationships.
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Crafting the Next Era of Financial Services With AI
The last decade of financial innovation was marked by layering – apps on the surface, bots in the back office, analytics in pockets. That strategy delivered quick wins but left the enterprise fragmented. As autonomous intelligence becomes the new system of work, fragmentation has turned from inefficiency into liability.
The leadership imperative is clear: re-architect now. Unified platforms are not a technology choice but a business strategy. They are the only way to scale agentic AI responsibly, embed trust into workflows, and turn transactions into enduring loyalty.
The institutions that act today will not only meet regulatory demands and efficiency goals; they will craft the next era of financial services, where intelligence is woven into the fabric of every decision, and trust becomes the currency of growth.
Disclaimer Any opinions, findings, and conclusions or recommendations expressed in this material are those of the author(s) and do not necessarily reflect the views of the respective institutions or funding agencies.
