In auto and commercial vehicle (CV) lending, credit losses are often attributed to market cycles, borrower behaviour, or economic headwinds. Yet, across banks and NBFCs, a less visible but equally powerful factor continues to erode portfolio performance: poor data quality at the very first mile of the lending journey.

The first mile sets the tone for every downstream decision, where customer, vehicle, and financial data are captured . Additionally, when this data is fragmented, delayed, or manually handled, lenders inherit risk that technology alone cannot fix later.

Moreover, as institutions accelerate BFSI digitization, improving first-mile data quality is no longer an operational upgrade — it’s a strategic imperative.

Why First-Mile Data Quality Matters More Than Ever

Auto lending today operates at scale, speed, and complexity. Decisions are increasingly automated, but automation only works as well as the data that feeds it.

1. Credit decisions are only as good as the data behind them

Risk models, scorecards, and pricing engines rely on accurate borrower and vehicle information. Incomplete income details, outdated bureau data, or unverified vehicle records distort risk assessment — leading to either over-exposure or missed growth opportunities.

2. Delinquencies rise when early signals are missed

Recent trends in auto and CV portfolios show rising delinquencies, especially in used-vehicle and subprime segments. While macro factors play a role, poor first-mile data often masks early warning indicators — delaying intervention and increasing loss severity.

3. Fragmented systems weaken portfolio visibility

In many institutions, origination, underwriting, dealer systems, and external data sources operate in silos. Without a unified, digital data layer, lenders lack a single source of truth — making portfolio monitoring, reporting, and regulatory compliance harder than necessary.

How Poor First-Mile Data Translates into Credit Loss

Credit loss doesn’t occur at disbursal — it begins much earlier.

1. Mispriced risk

When borrower or vehicle risk is inaccurately captured, loans are priced incorrectly. Over time, this leads to higher probability of default (PD) and loss given default (LGD), especially in long-tenure CV loans.

2. Delayed underwriting and exceptions overload

Manual data handling increases exceptions, rework, and dependency on underwriters to “fill the gaps.” This slows decisioning and shifts focus from risk evaluation to data correction.

3. Regulatory and audit exposure

Regulators increasingly expect explainable, traceable credit decisions. Poor data lineage and manual overrides raise audit red flags and increase compliance burden.

Why Digitization Alone Is Not Enough

Many lenders have digitized front ends — digital applications, portals, and APIs — yet continue to struggle with data quality. The reason is simple: digitization without orchestration still leaves gaps.

True first-mile transformation requires:

1. Automated data ingestion from trusted sources
2. Real-time validation and enrichment
3. Rule-driven workflows that adapt to product and segment complexity

This is where end-to-end BFSI digitization, not point solutions, becomes critical.

How Leading Banks Are Fixing the First Mile

As a digital transformation partner to banks and financial institutions, Decimal Technologies works closely with lenders to re-engineer first-mile data flows — not just digitize forms.

1. Orchestrated digital onboarding

Low-code, configurable onboarding journeys ensure that customer, vehicle, and financial data is captured once, validated early, and reused across credit stages.

2. Integrated data ecosystems

By integrating bureaus, CKYC, vehicle databases, GST, bank statements, and internal systems through APIs, lenders reduce manual intervention and data inconsistency.

3. Rule-based and indicator-driven checks

Automated rules flag anomalies, missing information, and risk indicators upfront — enabling faster, cleaner underwriting decisions.

4. Continuous data quality monitoring

Built-in dashboards and audit trails provide ongoing visibility into data accuracy, exceptions, and operational bottlenecks.

The result is faster decisions, lower rework, and materially improved credit outcomes.

The Strategic Shift: From Data Capture to Data Confidence

For banks and NBFCs, the real opportunity lies in shifting mindset — from treating first-mile data as an operational necessity to recognizing it as a core credit asset.

Moreover, institutions that invest in:

1. Strong first-mile data governance

2. Digital orchestration across the lending journey

3. Scalable, low-code platforms for rapid adaptation

are better positioned to manage risk, scale portfolios responsibly, and respond faster to market changes.

Conclusion

In vehicle lending, credit losses often trace back not to underwriting intent, but to early data blind spots. Fixing the first mile is one of the most powerful — yet underappreciated — levers for improving portfolio health.

As BFSI continues its digital transformation journey, lenders must look beyond isolated systems and focus on data confidence from the very first interaction. With the right digital foundation, first-mile data becomes an enabler of growth, not a source of hidden risk.

At Decimal Technologies, we partner with financial institutions to make this shift real — helping them build lending journeys where data, decisions, and outcomes are aligned from day one.