India’s digital economic system is witnessing unprecedented momentum. Fueled by authorities initiatives resembling Digital India, Jan Dhan-Aadhaar-Cell (JAM) trinity, and the speedy adoption of UPI, the nation has turn into a fertile floor for digital transformation. Digital funds are rising at a compound annual progress charge (CAGR) of over 30%, with greater than 17 billion UPI transactions month-to-month as in April 2025. As cellular penetration deepens and shopper conduct shifts on-line, banks are accumulating huge volumes of knowledge—structured, unstructured, and semi-structured—throughout each touchpoint.
For India’s public sector banks (PSBs), this explosion of knowledge presents each a problem and a transformative alternative. From transactional information and scanned paperwork to voice logs, app interactions, and behavioral insights, the info generated holds immense potential. One of many key focus areas on account of this enhanced digitalization is SME lending, whose rising digital footprints throughout GST, banking, and transaction methods now make it possible to evaluate creditworthiness with far higher pace and precision.
On this state of affairs, conventional analytics fashions—centered on retrospective dashboards and regulatory reporting—are now not enough. To stay aggressive and future-ready, PSBs should undertake analytics at scale – not only for effectivity, however to unlock new progress areas resembling SMB lending fashions, danger adjusted cross-sell fashions, personalisation, and so forth. They have to harness superior analytics and synthetic intelligence (AI) to foretell, prescribe, and prosper.
Why Conventional Analytics Is No Longer Sufficient
Conventional information analytics has largely been backward-looking—providing summaries of what occurred and why. Whereas helpful for compliance and strategic reporting, it fails to ship the predictive foresight or real-time intelligence wanted in at present’s hyper-digital banking surroundings.
For Public sector banks, conventional analytics has largely centered round analysing historic information to generate regulatory experiences, MIS summaries, and help strategic planning. These approaches, whereas invaluable, usually concentrate on retrospective insights — what occurred, when, and why — with out providing foresight or actionable intelligence.
Nonetheless, banking at present is now not prepared to attend. That is significantly related in areas like SMB and retail lending, the place expectations round turnaround time, credit score personalization, and digital servicing proceed to rise.
Three forces are accelerating the shift towards superior analytics in PSBs:
- Demand for Actual-Time Responsiveness
- Want for Hyper-Personalization
- Urgency to Modernize Legacy Knowledge Platforms
Laying the Basis: The Position of a Trendy Knowledge Platform
Superior analytics fashions—be it predictive credit score scoring, danger monitoring or generative AI —are solely as highly effective as the info they ingest. For PSBs to allow smarter lending they have to put money into a contemporary, cloud-ready information platform that gives
– Centralized information ingestion from core banking, GST methods, Bureau experiences, CRM, digital channels, and different related ecosystem companions
– In-built information governance, lineage monitoring, and high quality assurance
– Scalable, real-time processing for analytics and AI workloads
– Safe, compliant structure aligned with RBI and sectoral mandates
This platform isn’t just infrastructure—it’s the strategic enabler for unlocking worth throughout the banking worth chain.
Persistent hurdles impeding superior analytics adoption
- Poor information high quality and fragmented views of buyer and enterprise accounts
- Siloed infrastructure that separates operational and transactional insights
- Restricted integration of other information (e.g., GST, digital funds, and so forth)
- Scarcity of expert information science and engineering expertise to translate fashions into manufacturing outcomes
Key enablers for PSBs to undertake superior analytics
Efficiently adopting superior analytics in public sector banks (PSBs) requires extra than simply deciding on the precise know-how. It calls for strategic alignment, modernized structure, and organizational readiness throughout a number of dimensions. Based mostly on widespread implementation challenges and confirmed remediation methods, a sensible readiness framework could be anchored across the following pillars:
Outline a Enterprise-Aligned Analytics Technique
Begin with high-impact use instances like fraud detection, credit score scoring, and churn prediction to show early worth and safe stakeholder buy-in.
Develop Organizational Capabilities and Tradition
Set up analytics Facilities of Excellence (CoEs) to institutionalize finest practices, drive expertise growth, and foster a data-driven tradition the place selections are guided by perception fairly than instinct.
Construct Scalable Knowledge Merchandise
Keep away from suboptimal tech stacks and quick-fix options that create long-term technical debt. Additionally guarantee interoperability by selecting platforms that help open APIs and middleware, permitting seamless integration throughout methods.
Strengthen Knowledge Governance and High quality
Guarantee trusted, constant information by means of centralized dictionaries, role-based entry, and strong metadata administration frameworks.
Construct a Resilient Knowledge platform and Structure (Lakehouse)
Modernize legacy methods by adopting cloud-native platforms with real-time processing and robust information governance. Construct scalable, high-performing information lakes to allow dependable, large-scale analytics
Embed Safety, Compliance & Threat by Design
Combine privateness, consent, and localization controls early. Guarantee full alignment with RBI and sectoral rules when working with cloud or exterior distributors.
Whereas public sector banks already function on scalable information platforms, evolving these architectures to help superior analytics capabilities is crucial.
Tangible Influence: Use Instances Driving Worth Right this moment
This layered view illustrates how core banking features throughout retail, shopper and SMB lending, playing cards, industrial, and enterprise operations could be elevated by means of Enterprise Intelligence, Superior Analytics, and Generative AI. Every horizontal enabler brings progressively deeper insights — from automated reporting to predictive decision-making and AI-driven personalization. Collectively, they type a unified intelligence material to speed up data-driven transformation throughout the financial institution.
Superior analytics will not be futuristic—it is already delivering actual outcomes throughout the banking enterprise:
Value Effectivity & Compliance
30–40% discount in compliance prices through automation
Actual-time anomaly detection reduces danger
Streamlined documentation and automatic credit score memo technology in a wiser lending context specifically for retail and SMB loans
Decrease processing prices for small-ticket loans by means of digital workflows
Prime-Line Progress
Smarter underwriting improves credit score high quality
Early warning methods mitigate NPA dangers
Personalised presents enhance conversions
Money circulate–primarily based scoring improves credit score attain to thin-file SMBs
Enhanced Buyer Expertise
Quicker mortgage selections
Clever product suggestions
24/7 self-service analytics
Digital-first onboarding journeys for SMB debtors
AI-powered chat help for mortgage standing, eligibility, and documentation help
Conclusion
Within the digital age, information is the brand new core capital. For public sector banks, embracing superior analytics at scale isn’t just a know-how improve—it’s a strategic crucial. By investing in scalable information infrastructure, aligning analytics with enterprise priorities, and fostering a data-driven tradition, PSBs can unlock a virtuous cycle of innovation and influence.
The authors are Dibyanshu Lahiri, Director, BCG; Shray Jain, Director, BCG; Vipul Singh, Lead IT Architect, BCG and Nishchal Pawar, Senior IT Architect, BCG.
