Bank Statement Analysis for Digital Lenders and Fintech NBFCs
Realtime credit signals inside a digital-lending session, with a sync / async / webhook posture that fits short-tenor personal-loan and credit-line workloads. RBI Digital Lending Guidelines alignment built in — clean DLA / LSP / RE tenant isolation, FLDG-arrangement governance, KFS-grade data lineage, AA-first with PDF fallback.
What TransactIQ does for a digital-lending pipeline
Nine capabilities that map to the shape of a compliant digital-lending stack in India.
Sub-30-second realtime analysis
Short-tenor personal-loan and credit-line products need a decisioned signal back in the same session the borrower is in. TransactIQ is architected for the realtime tier — synchronous response within seconds for clean inputs, async fallback for the degraded tail.
Sync, async, and webhook posture
Synchronous for clean PDFs that parse within the realtime budget. Asynchronous with job-status polling for password-protected, multi-page, or degraded inputs. Webhook callbacks for the cohort that needs push notification of completion. Documented posture — not fabricated endpoints.
DLA and LSP boundaries built in
RBI Digital Lending Guidelines (Sept 2022) draw a sharp line between regulated entity, Digital Lending App, and Lending Service Provider. TransactIQ supports the deployment shapes a compliant DLA-LSP-RE arrangement actually needs — including LSP-as-tenant isolation and consent boundary enforcement.
KFS-grade data lineage
Key Fact Statement disclosure under RBI digital-lending guidelines depends on a clean lineage from raw statement to decisioned variable. TransactIQ produces a per-statement audit record — pipeline version, parser variant, signal outputs — that supports the KFS disclosure and any subsequent borrower or regulator review.
Statement freshness windows
Digital-lending credit policies typically require statement data within a defined freshness window (e.g. last 90 days of activity from statement end-date). TransactIQ surfaces statement-period coverage and freshness metadata explicitly so the policy engine can apply the cutoff rather than infer it.
AA-first with PDF fallback
Realtime digital lending is the cleanest fit for AA-only flows. TransactIQ ingests AA payloads across OneMoney, Setu, Finvu, and CAMS-AA, with PDF as the fallback when AA consent is unavailable or revoked mid-flow.
FLDG-compliant tenancy
Where a partnership uses First-Loss Default Guarantee, signal access and audit trail must respect the RE-LSP boundary. TransactIQ deployment tiers support clean tenant isolation so the RE retains primary control of the data plane while the LSP operates the user-facing app.
40+ engineered signals at realtime budget
Salary regularity, EMI obligation density, recurring vendor outflows, GST-payment outflows, top counterparties, average daily balance, weekend-vs-weekday flow — produced within the realtime envelope for the realtime tier, with the deeper variants reserved for the async path.
Bounce predictor for thin-file PL
Short-tenor personal-loan books and credit-line products lean heavily on a forward bounce signal. TransactIQ produces a bounce predictor trained on bounce/return history, salary consistency, and end-of-cycle balance posture — designed as a forward-looking signal rather than a simple historical-bounce count.
Why TransactIQ for digital lending
Four dimensions where a credit, risk, or compliance lead at a digital lender typically compares vendors.
| Dimension | Typical incumbent posture | TransactIQ |
|---|---|---|
| Realtime budget | Many BSA vendors target batch or near-realtime workloads; sub-30-second clean-input response is not always the design target. | Realtime tier architected for sub-30-second sync response on clean inputs; async path with status polling for the degraded tail; webhook callback for push-notification consumers. |
| RBI digital-lending guideline alignment | Standard vendor posture relies on the RE to enforce DLA/LSP boundaries at the application layer. | Deployment tiers (self-hosted in RE VPC, dedicated managed, multi-tenant managed) support clean tenant isolation between RE, LSP, and DLA — including FLDG-arrangement governance and consent-boundary enforcement. |
| KFS disclosure backing | Audit trail typically vendor-internal. | Tamper-evident per-statement audit record — pipeline version, parser variant, signal outputs — supports KFS disclosure and downstream borrower or regulator review. |
| AA-vs-PDF mix in production | Many vendors handle AA or PDF as the primary path with the other treated as a secondary integration. | AA payload normalisation across OneMoney, Setu, Finvu, CAMS-AA, with PDF as a first-class fallback. AA-vs-PDF accuracy delta surfaced in the audit trail. |
Benchmark TransactIQ on your digital-lending pipeline
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