Indian leaders across sectorsare scaling digital services at an extraordinary pace. Financial institutions, public sector bodies, and healthcare institutions are onboarding customers and citizens remotely, expandingdigital ecosystems, and running mission‑critical operations on cloud-based platforms. In this environment, data has become the currency of every digitalinteraction, and identity is the thread that determines how that data is interpreted, trusted, and acted upon. Every service action, whether it is a policy issuance, loan approval, claim settlement, patient record access, or benefit disbursement,is ultimately driven by identity data. Yet across much of the ecosystem, identity governance has historically been treated as a technical necessity rather than a strategic data risk discipline. That approach is increasingly misaligned with today’s fraud landscape and regulatory expectations.
Director of Customer Advisory
SAS India
Recent fraud trends, including sophisticated impersonation-led scams, underscore a broader shift. As digital transactions and services become instant and ubiquitous, fraud is no longer confined to predictable patterns. Instead, it increasingly exploits trust: impersonating authority, mimicking legitimate behavior, and operating just below traditional detection thresholds. In this context, the question facing Indian organizations is no longer simply whether fraud can be detected, but whether unknown and emerging risks can be identified early, explained clearly, and acted upon with confidence.
This is where identity governance intersects directly with fraud management. Fraud does not occur in isolation; it unfolds through identities interacting with data across processes. Regulatory pressure in India is reinforcing this reality. Supervisory and compliance frameworks across sectors are increasingly focused on how organizations govern the use of data across service delivery, digital engagement, and operational workflows as these become more interconnected and automated. The Digital Personal Data Protection (DPDP) Act further elevates expectations by requiring organizations to demonstrate that personal and sensitive data is used for clearly defined purposes, that its movement can be traced and explained, and that accountability is maintained across the data lifecycle. Identity governance is what operationalizes these principles by linking data usage back to responsibility.
Despite this, manyorganizations still rely on fragmented processes and infrequent reviews to monitor how data flows through their operations. Over time, data is reused, repurposed, and consumed across more channels than originally intended. These blind spots often remain unnoticed, only surfacing during regulatory inspections, internal audits, or after fraud incidents.What is now emerging is a move away from checkbox compliance toward risk‑aware, data‑centric identity governance. Instead of applying uniform oversight, leading organizations are prioritizing scrutiny based on data sensitivity, operationalcriticality, and behavioral context. The focus shifts from static definitions to understanding how data is actually being used.
From a SAS perspective, this mirrors how fraud prevention and data governanceare evolving. Legacy rule‑based approaches were designed for known threats, but struggled to detect adaptive, fast‑moving fraud. Across SAS’ work with Indian organizations, a consistent insight has emerged: risks become visible much earlier when identity signals are analyzed alongside transactional and behavioral data.
These identity signals can range from a recent privilege change indicating elevated fraud risk, a dormant account unexpectedly reactivated, multiple failed login attempts that may signal a credential attack, or access occurring outside normal office hours. When identity context is layered with behavioral analytics, organizations can detect these anomalies in real time, well before financial loss or regulatory exposure occurs. In the public sector, this same approach is enabling more efficient data sharing and program operations by consolidating identity and beneficiary data from across departments into one system, as a single source of truth.
Artificial intelligence enables this shift by continuously learning what “normal” looks like as patterns change.This approach is particularly relevant in scenarios such as authorized push payment fraud, mule account activity, or synthetic identity fraud. Identity governance, informed by advanced analytics, provides the context needed to distinguish genuine activity from manipulated or compromised trust.
As Indiabalances rapid digital expansion with tightening regulation and increasingly sophisticated fraud, identity governance is emerging as a critical control plane that connects data governance, fraud intelligence and regulatory accountability. The future is not about managing identities or transactions in isolation, but about understanding how identities, data and behavior interact in real time and using that understanding to make high-trust decisions at scale.
Authored by Dr. Radha Krishna B, Director of Customer Advisory at SAS India
