Himanshu Mody: Why BFSI’s next growth cycle will be built on trust, not just technology

Himanshu Mody, Partner & Head, DEPT® India, shares insights on its latest BFSI trends report, which identifies data, user experience (UX) & AI as the critical growth levers in 2026

by e4m Staff
Published: Feb 26, 2026 10:36 AM | 8 min read

India’s BFSI sector is moving into a phase where digital adoption is no longer the differentiator; digital maturity is. As customer acquisition plateaus for large banks and financial institutions, the focus is rapidly shifting from scale to precision, trust and lifetime value. With rising regulatory scrutiny, increasing instances of digital fraud, and more discerning customers, technology adoption alone is no longer enough. What matters now is how data and AI are used, and whether customers understand and trust those decisions.

These shifts are at the heart of DEPT®’s latest BFSI trends report, which identifies three forces—data, user experience (UX) and artificial intelligence, as the most critical growth levers for financial services in 2026. Crucially, these are not standalone pillars, but deeply interconnected capabilities that must work together.

Speaking in detail about the report and its implications for the BFSI sector, Himanshu Mody, Partner & Head, DEPT® India, in an exclusive interaction with exchange4media, explained how these three forces reinforce one another. “Data, UX and AI form a compounding loop. First-party data fuels AI, AI enables real-time decision-making, and those decisions surface through UX. Trust is earned, or lost, at the UX layer,” Mody said.

This interplay is evident in DEPT®’s engagement with IDFC FIRST Bank, where trust challenges were not rooted in product gaps but in performance friction across high-intent digital journeys. By systematically improving Core Web Vitals across more than 6,000 banking pages, optimising JavaScript execution, stabilising transaction overlays, and reducing render-blocking assets, mobile PageSpeed scores improved to ~75, with over 60% of pages meeting CWV thresholds. These changes reduced interaction latency across login, dashboard, and calculator journeys, reinforcing confidence at moments where even minor friction can undermine trust.

The Three Shifts Redefining BFSI In 2026

According to Mody, the strength of this compounding loop lies in its interdependence. Weakness in any one area can undermine the entire system. A clunky app or confusing dashboard doesn’t just frustrate, it erodes the AI’s entire promise, wiping out any advantage even when AI is flawless behind the scenes.

“Building this loop takes time,” Mody emphasised. “It’s a 6–10 month journey to establish robust data foundations, embed AI into decision-making, and smooth every customer touchpoint.”

Notably, the DEPT® report highlights that proprietary first-party data is becoming BFSI’s most strategic asset, especially as consent-driven usage and data protection regulations tighten. Banks already hold vast volumes of behavioural and transaction data, but the real competitive edge comes from turning that data into clear, actionable insights that customers can understand and act on.

“Instead of static dashboards showing balances or statements, BFSI brands should create advisory-led journeys. Help customers understand spending patterns, identify savings opportunities, evaluate insurance needs, and measure investment readiness. This is where data becomes trust, and trust becomes growth,” Mody added.

A practical illustration of this shift can be seen in DEPT®’s work with HDFC Bank and HDFC Life, where complex financial datasets were restructured into decision-support tools embedded directly within customer journeys. Interactive calculators, dynamically updated rate and fund information, and API-driven product logic enabled customers to evaluate outcomes, not just inputs, independently. By making rates, returns and eligibility criteria transparent and intuitive, data evolved from a backend repository into a visible trust-building mechanism within the experience layer.

This ability to productice data responsibly can play a critical role in building long-term differentiation and trust in an increasingly commoditised market.

The Trust Barrier In AI-led Personalisation

AI promises relevance and efficiency, but traditional banks often trip over trust. Regulatory confidence and customer skepticism are the brakes. According to Mody, trust and regulatory confidence are the two biggest constraints shaping how far BFSI organisations can go with AI.

“AI can’t operate as a black box. Both customers and regulators need to clearly understand what’s happening with the data. One unexplained rate, one opaque recommendation, and confidence drops,” Mody said.

Legacy infrastructure remains another major barrier. Many established banks still operate fragmented, outdated technology stacks that weren’t built for real-time orchestration or AI-driven decisioning at scale. Even the smartest AI often gets stuck in pilots.

This challenge is particularly pronounced within large NBFC ecosystems. At Tata Capital, DEPT® consolidated more than 15 fragmented websites onto a unified Adobe-powered platform, reducing go-to-market timelines by nearly 90%. Beyond speed, the transformation introduced consistent data models, shared component libraries and a single source of truth across journeys. This architectural reset enabled faster experimentation and created the foundation required for AI-led decisioning to scale sustainably beyond isolated pilots, as per Tata Capital Adobe case study.

Similarly, at Piramal Finance, DEPT® replatformed the digital ecosystem using Adobe’s Edge Delivery Services, marking the first such implementation within India’s BFSI sector. By transitioning key journeys to server-side rendering and optimised delivery frameworks, the platform significantly improved performance, SEO visibility and content responsiveness. Engagement levels rose by 90–100%, establishing the real-time digital backbone necessary for AI-driven decisioning to move from experimentation to full-scale production.
Over-personalisation is another risk. Relevance can quickly feel like surveillance if boundaries aren’t clear. BFSI brands must strike a balance—use data to add value without making customers feel monitored or exposed.

Mody cautioned that BFSI brands must strike a careful balance, using data to add value without making customers feel watched or exposed.

From Explainable AI To Responsible Governance

For AI to become a sustainable growth engine, explainability must be embedded directly into the customer experience, not hidden behind PDFs or fine print. Mody believes customers should be able to see, understand, and question why a particular interest rate, premium, or offer applies to them.

This approach is increasingly relevant in insurance and long-term financial products. At IndiaFirst Life, DEPT® supported the migration of customer and distributor journeys to Adobe Experience Cloud, enabling personalised engagement while maintaining regulatory clarity. Recommendation logic, content variations and journey pathways were designed to remain consistent across digital and assisted channels. This ensured that customers, agents and service teams accessed the same explanations for pricing, eligibility and next-best actions, reducing ambiguity and reinforcing governance through experience design rather than compliance paperwork.

“If an app shows a customer a loan rate or flags a transaction, their first question is: why this, and why now? If the answer isn’t clear, confidence drops immediately. Guided, transparent journeys, where customers can opt out of what they’re uncomfortable with, aren’t optional, they’re what make AI usable at scale,” he said.

Customers lose trust when apps, branches, chatbots, and relationship managers offer conflicting explanations. Platforms that act as a single source of truth across all channels ensure AI-driven decisions feel coherent, credible, and reliable, he added.

From a governance standpoint, Mody stressed the need for BFSI organisations to move from a gatekeeping mindset to one of continuous assurance. Privacy must be embedded by design, not handled through disclaimers. Consent-led usage, clear audit trails, and transparent explanations should be built into the experience. Defining clear “no-go” areas for AI, where automation could undermine confidence, strengthens compliance and builds trust.

This approach not only strengthens compliance but also builds long-term trust with customers and regulators alike.

BFSI’s Next Phase Of Transformation

As AI and data maturity increase, BFSI marketing and transformation budgets are also undergoing a structural shift. Mody noted that earlier, a large share of spending went into media-led acquisition and awareness. Today, for leading BFSI brands with established customer bases, the focus is moving towards data platforms, orchestration layers and AI-enabled frontline tools.

Relationship managers, insurance agents, and advisors are increasingly supported by AI-driven insights that make every interaction more relevant, reduce wastage, and enable informed conversations. Transformation budgets are now outcome-driven, closely tied to measurable KPIs such as approval speed, churn reduction, and cost efficiency.

This shift is also collapsing the traditional divide between brand building and performance marketing. Every interaction—from a recommendation to a service experience—is both a brand touchpoint and a conversion opportunity. AI-led personalisation accelerates this convergence.

The evolving landscape is reshaping the role of agencies and technology partners. BFSI clients are moving away from fragmented partnerships toward end-to-end partners who integrate data, experience, and commerce seamlessly. Enterprise-grade technology, combined with design, engineering, and operational capabilities, is now table stakes. As BFSI enters its next phase of transformation, the message is clear: AI alone is not the advantage. The winners will be those who can combine data, UX and intelligence responsibly.