16%
New-to-credit borrowers remain a meaningful but constrained share of originations.
TransUnion CIBIL via Economic Times, 2026
De-risk Credit Decisions.
TrueScore gives lenders a real-time context-aware alternative to traditional bureau scores, using Account Aggregator banking data, borrower-consented inputs, and internal risk signals to score retail and business loans more precisely.
Bureau-first underwriting cannot meet
India's ₹25 lakh crore formal credit gap.
Traditional bureau-led models are optimized for borrowers who already look financeable on paper. The gap sits elsewhere: MSMEs, self-employed applicants, and new-to-credit customers whose repayment ability shows up in banking trails and business activity before it shows up in bureau history.
14%
Only a small share of MSMEs access institutional credit today.
Deloitte via Times of India, 2026
50%
Credit access continues to be a live operating constraint for MSMEs.
LocalCircles via Economic Times, 2026
Go from Signal to Decision.
TrueScore combines bureau, banking, and lender-side inputs into a score that can be explained, governed, and deployed inside real underwriting workflows. Banks, NBFCs, and credit fintech teams can configure scorecards, approval thresholds, and policy rules around their own risk posture instead of depending on a static external score alone. That gives teams tighter control over approval quality, faster iteration on credit strategy, and clearer accountability for how decisions perform in production.
01
Bring signals together
Combine bureau records, banking behaviour, and lender-side inputs into one decision layer built for modern credit workflows.
02
Score for the user
Use scorecards tailored to retail, self-employed, and MSME use cases instead of forcing every borrower through one risk lens.
03
Set boundary conditions
Translate raw signals into approval thresholds, risk bands, and decision outputs that teams can operate with confidence.
04
Explain every outcome
Give credit teams reason codes, audit visibility, and governance controls so every approval or rejection is defensible.
05
Use it across channels
Use the same scorecards across internal and partner channels while keeping policy control and model ownership in-house.
Why TrueScore
Alternative scoring
your credit team can control.
TrueScore gives banks, NBFCs, and credit fintech teams more signal than a bureau score and more accountability than a black-box model. Combine bureau, AA banking, consented, and internal data to run scorecards, thresholds, and decision rules around your own lending strategy.
More signal
Use bureau, AA banking, consented, and internal data together.
More control
Own scorecards, thresholds, and policy rules inside your workflow.
More accountability
Deploy explainable scores with audit trails and governed delivery.
See beyond bureau depth
Repayment quality often shows up in banking behaviour, business activity, and lender-owned data before it becomes visible in bureau history.
Run your own credit policy
Set scorecards, cut-offs, and approval logic by product, borrower segment, and risk posture instead of depending on one external score.
Keep decisions explainable
Every score can ship with reason codes, audit visibility, and governance controls so underwriting teams can defend decisions in production.
Share scores without exposing IP
Serve approved scorecards through internal systems or partner channels without handing over model parameters, feature logic, or proprietary policy design.
INTEGRATION
Use TrueScore inside the systems your credit team already runs.
TrueScore does not ask lenders to replace their underwriting stack. It plugs into existing origination, risk, and servicing workflows so teams can start with the operating model they already trust, then scale the same scorecards across channels with consistent policy logic.
Fit into your current workflow
Use TrueScore inside LOS, LMS, fintech funnels, branch journeys, or partner-led sourcing without rebuilding your credit operations from scratch.
Choose the operating mode
Run real-time APIs for decisioning, batch scoring for portfolio refresh, or dashboard-led review for credit teams that need case-level oversight.
Keep policy control with your team
Thresholds, scorecards, role access, model versions, and audit logs stay visible so adoption does not come at the cost of governance.
Typical outputs include score, risk band, reason codes, model version, and timestamped decision metadata for downstream underwriting use.
Compliance
Compliance that fits
live lending workflows.
TrueScore is designed for regulated credit operations, not just model output. Consent handling, explainability, audit visibility, and model governance are treated as operating requirements so banks, NBFCs, and fintech teams can scale scoring without losing control.
Consent and data boundaries
Use borrower-consented data flows with minimised collection, controlled access, and a clearer operating path for DPDP-aligned lending use cases.
Explainable credit decisions
Give underwriting teams reason codes and decision context they can communicate internally, review operationally, and defend when scrutiny matters.
Governance built into production
Track model versions, score events, and audit history so rollout discipline is maintained as usage expands across products and teams.
Operational controls and regulatory touchpoints
- RBI Fair Practices Code - reason-code delivery per guidelines
- DPDP Act 2023 - consent management and data minimisation
- Account Aggregator - licensed fetch via Setu / OneMoney
- Model Risk Governance - champion-challenger framework
- Vintage Analysis - cohort tracking and recalibration
- Audit Trail - immutable inference logs and version pinning
- Data Localisation - India-only storage posture
- Right to Explanation - SHAP outputs surfaced per applicant decision
India's next 100 million borrowers are waiting.
Book a 30-minute demo and we will run TrueScore against sample borrower data before you commit to a rollout.