TransactIQ vs ScoreMe for Bank Statement Analysis
ScoreMe is a Mumbai-based BSA bundled with proprietary credit scoring. TransactIQ is a pure bank statement analyzer that ships policy-neutral signals to the lender's own scorecard. The honest comparison is about product shape — bundled-score versus raw-signal — not about which one is "better".
ScoreMe runs production BSA and scoring for real Indian lenders and is the right shape when the lender wants a packaged score to drop into the underwriting pipeline. This comparison is for lenders running their own scorecards, lenders running into MSME originations without audited financials, or lenders running into a deployment posture where the data must stay inside their VPC. TransactIQ is the raw-signal alternative for those cases.
Side by side
Eight dimensions where credit and risk teams usually compare the two.
| Dimension | ScoreMe | TransactIQ |
|---|---|---|
| Product shape | Mumbai-based BSA bundled with proprietary credit scoring. Outputs include parsed transactions plus a packaged score for the lender to consume. | Pure bank statement analyzer. Surfaces 40+ engineered signals and the four-layer MSME synthetic financial construction — the lender's underwriting policy and scorecard consume the signals. No bundled score. |
| Configurability for lender policy | Scoring logic is the vendor's. Configurability sits around thresholds, weightages, and policy overlays on top of the packaged score. | Signal outputs are policy-neutral. The lender owns the scorecard. 24+ industry presets and per-tenant signal tuning available. Suited to risk teams that want the raw material rather than the pre-built decision. |
| Bank coverage breadth | Strong coverage on Indian private and public-sector banks, with format coverage expanded through lender requests. | 200+ banks with explicit engineering for the degraded tail — PSU dot-matrix scans, Karnataka State Co-operative, district central co-ops, urban co-ops, payments banks, small finance banks. New parsers ship to all tenants on the tier. |
| Accuracy on degraded statements | Production-grade on machine-generated retail PDFs. Cooperative and PSU dot-matrix accuracy varies by bank format. | Trained and benchmarked specifically on the degraded tail. Customer-documented 51% → 88% match rate improvement on a real lender portfolio (TransactIG outcome stat; same accuracy posture carries into TransactIQ's BSA outputs). |
| MSME synthetic financials | Bank-statement signals feed the bundled score. Standalone MSME synthetic financial statement construction is not a documented core surface. | Four-layer synthetic construction inferred from bank activity — personal/business separation, synthetic P&L, synthetic balance sheet, synthetic cash flow. Designed for the ₹65-trillion MSME credit-demand gap where audited statements are unavailable. |
| AA integration | AA-ready with consent-flow integrations into Account Aggregators in the ecosystem. | AA-ready with full PDF parity — the same 40+ engineered signals regardless of whether the source is AA-fetched JSON or a borrower-uploaded statement. One signal contract across channels. |
| Deployment options | Primarily SaaS / cloud-delivered. Enterprise deployment shapes available on request to larger customers. | Three tiers by default: self-hosted inside the lender's VPC on AWS/Azure/GCP India, managed multi-tenant on AWS Mumbai, dedicated single-tenant private cloud. Self-hosted is a first-class product tier. |
| Security posture | Enterprise security posture with India data residency. Certifications and audit reports available under NDA. | ISO 27001:2022, AWS Mumbai by architecture, DPDP Act 2023 aligned, RBI IT-governance posture documented. Self-hosted tenants keep data inside their own VPC by construction. |
Where TransactIQ wins
The three dimensions that drive the switch conversation when it happens.
Pure BSA, lender owns the scorecard
Risk teams that want raw signals to feed their own scorecard get a deeper, policy-neutral signal palette rather than a vendor-bundled score. The underwriting decision logic stays with the lender — useful when the scorecard is a proprietary asset and regulator-facing.
MSME synthetic financials
ScoreMe's scoring is built around standard BSA signals. TransactIQ's four-layer synthetic construction (P&L, balance sheet, cash flow inferred from bank activity) opens up MSME underwriting where audited statements don't exist — a different lending product, not a feature add-on.
Degraded-tail accuracy + self-hosted
Co-operative and PSU dot-matrix coverage is first-class engineering, not a format request queue. And if a regulator conversation or board mandate requires the lender to own the data plane, TransactIQ's self-hosted tier ships by default inside the lender's VPC.
Where ScoreMe is comparable
The honest read on where the comparison is genuinely close.
Standard private-bank coverage
On HDFC, ICICI, Axis, Kotak, SBI machine-generated retail PDFs, both vendors deliver production-grade extraction. The interesting comparison is on the degraded tail, the MSME synthetic layer, and whether the lender wants a bundled score or raw signals.
AA-readiness
Both vendors integrate into the Account Aggregator consent flow. AA support alone is not a differentiator — the meaningful question is signal parity between AA-fetched JSON and uploaded PDFs, and whether the lender wants vendor-scoring or its own scorecard.
Benchmark TransactIQ on your portfolio
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