Every meaningful technology journey begins long before a product is built. Sometimes it starts with a question that refuses to fade: why does data empower a few while excluding so many others?

For Nikhil Kurhe, that unease grew into a mission. His curiosity about systems, fairness, and the invisible forces shaping access pushed him to break down the way data works today—and rebuild it in a way that serves people first.

That instinct eventually led him to co-found Finarkein Analytics, where he now works at the intersection of open finance, digital public infrastructure, and responsible data design. His work has shaped how businesses tap into India’s evolving DPI stack, and his voice has become a trusted one in conversations on privacy, inclusion, and the future of analytics. But for Nikhil, the real goal goes far beyond technology. It’s about creating guardrails that prevent society from slipping back into old patterns of inequity.

In this conversation, he opens up about the beliefs that guide him, the problems he’s determined to solve, and the role responsible innovation must play as we build the next chapter of India’s digital future.

India’s BFSI sector has grown exponentially over the last two decades. How has the focus shifted from traditional payment systems to leveraging data as the primary driver of financial services innovation?

India first solved for digital payments at population scale, but that infrastructure created an even more powerful shift: the ability to use verified, consented data as the engine of financial services. Payments showed us what happens when a common protocol reduces friction. Data is now doing the same for credit, insurance, wealth and compliance.

The focus has shifted from merely moving money to understanding financial behaviour through data. Instead of relying on static documents or bureau records, institutions can access real-time bank statements, cash flow patterns, GST data, insurance information and more through trusted digital public infrastructure. This is transforming underwriting, KYC, fraud detection and even customer engagement.

In essence, data has become the new distribution layer. It allows products to be contextual, personalised and risk-aware from the start. The biggest change is that innovation is no longer limited to large incumbents with proprietary datasets. With AA-led consented data flows, smaller NBFCs, fintechs and new-age banks can compete on intelligence and customer experience, not just legacy scale. It is a fundamental rebalancing of the ecosystem.

Frameworks like Account Aggregator (AA), OCEN, and ONDC are reshaping lending and compliance. How are these enabling more responsible and faster credit decisions for consumers and businesses?

AA, OCEN, and ONDC solve different problems, but together they speed up and de-risk credit. AAs make verified financial data available with user consent. OCEN standardises how lenders evaluate and disburse small-ticket credit in real time. ONDC-FS brings marketplace transparency to buyer–seller interactions.

For lenders, this removes guesswork. Cash flows, liabilities, and balances are no longer inferred; they are pulled directly from trusted sources. It reduces dependency on physical documents and manual verification, which are slow and error-prone. Risk models become more accurate, fraud detection improves, and turnaround time drops from days to minutes.

For consumers and MSMEs, this builds fairness. Thin-file borrowers can be assessed using bank statements, GST, and transaction data rather than collateral or credit history alone. OCEN-enabled embedded journeys let them access credit where the need arises, not only through traditional channels.

The common thread is consented, standardised, machine-readable data. It keeps the user in control while enabling lenders to make faster, more transparent, and responsible decisions. Credit becomes more inclusive by design, not by exception.

 

How does data interoperability and consent-led sharing help build trust across banks, NBFCs, and fintechs, and why is this critical for India’s financial ecosystem?

Data interoperability removes ambiguity. When all institutions use the same rails, standards, and consent artefacts, customers know exactly what they are sharing, with whom, and for what purpose. This builds predictability, which is the foundation of trust.

Consent-led sharing also removes asymmetries. Users can review, pause, or revoke access to their data at any time. Institutions receive only what they need for the specific use case, which reduces over-collection and strengthens privacy safeguards. In a country like India, where digital literacy varies widely, this clarity is essential.

For the ecosystem, it prevents fragmentation. Without interoperability, each bank or fintech would build its own format, its own access rules, and its own interpretation of privacy. That leads to friction, inconsistent user experience, and higher compliance risks.

Interoperability and consent together create a trusted environment where data becomes a shared utility, not proprietary infrastructure. This lowers costs, enhances transparency, and allows regulated entities to collaborate without compromising competition. Simply put, it unlocks innovation while keeping user protection at the core.

 

In your experience, how are open-finance initiatives fostering collaboration rather than competition between banks and fintechs?Can you provide examples where this has led to smarter credit solutions?

Open finance replaces bilateral integrations with a common set of standards, which means banks and fintechs no longer compete on plumbing. They collaborate on intelligence, product design, and customer experience instead.

A clear example is underwriting. Traditional lenders work with fintechs to layer AA-based data intelligence on top of bureau information, enabling more accurate cash-flow-based lending. Banks benefit from improved models and reach, while fintechs gain access to regulated distribution.

Another example is collections. Banks and NBFCs increasingly rely on fintech platforms to monitor customer cash flows (with consent) and initiate responsible, automated repayment reminders. This reduces NPAs and improves customer retention.

Personal finance is another area. Fintech PFMs can build better categorisation and advisory layers while banks provide access to verified account data and regulated channels.

The key shift is mindset. Banks see fintechs as enablers of speed and innovation, while fintechs rely on banks for trust, compliance, and scale. Open finance turns this into a structured partnership model where everyone wins and the consumer benefits most.

Fraud prevention is a growing concern in data-driven finance. How can financial institutions leverage technology to detect and prevent fraud while maintaining compliance and user trust?

The strongest defence against fraud is verified, real-time data. Technologies like AA allow regulated institutions to validate customer identity, detect anomalies, and monitor accounts with user consent rather than relying on static documents or ex-post signals.

AI models can analyse behavioural patterns, cash-flow irregularities, and device-level indicators to flag suspicious activity long before it becomes a loss event. Network-level analytics help identify mule accounts, synthetic identities, and unusual transaction flows across institutions.

Compliance improves because the data is sourced from authenticated systems, not PDFs or uploads vulnerable to tampering. Every access event is tracked and auditable, which strengthens both internal governance and regulatory confidence.

Most importantly, user trust is maintained because these checks are built on consent, not surveillance. The customer authorises what is shared, for how long, and for what purpose. This transparency is essential in a high-risk environment.

Smart analytics, secure data rails, and consent-based access together create a system where fraud prevention becomes proactive rather than corrective.

 

Looking ahead, how do you see these data-driven frameworks transforming financial inclusion, lending accessibility, and overall sector growth in the next 5–10 years?

Data-driven frameworks will redefine financial access. Over the next decade, underwriting will move away from collateral-heavy or credit-score-centric methods to dynamic, cash-flow-based assessments powered by AA, ONDC, and other verified data.

This opens the door for millions of thin-file individuals and MSMEs who were previously invisible to the system. Small businesses will be able to access working capital based on real transaction data. Consumers will receive personalised credit offers embedded in the platforms where they transact.

The sector will also see a rise in hyper-specialised lending models: revenue-based finance, supply-chain lending, and usage-linked credit. As interoperability improves, regulatory compliance will be automated through real-time reporting using trusted digital rails.

On the inclusion front, agentic AI and contextual data will help institutions serve customers with limited digital literacy, reducing barriers of language, documentation, and access.

In effect, India will shift from an infrastructure-led phase to an intelligence-led phase of fintech, with data at the centre of credit, protection, and wealth management.

Read more: Finarkein Appoints Former CIBIL Business Head Subbu Sundaresh Vennelakanti As Director – Growth