For NBFCs, banks and fintech lenders in India
Credit Underwriting Software for MSME and Business Lending
Underwrite in about 15 minutes instead of 3 hours. CarmaOne reads GST returns, bureau data, bank statements, financials, MCA and litigation records together, applies your credit policy to every file the same way, and hands your credit committee an Auto-CAM memo, then keeps watching the borrower after disbursement.
- Analyst time per file, down from ~3 hours
- ~15 min
- Analyst time per file, down from ~3 hours
- Auto-CAM credit memo
- < 10 min
- Auto-CAM credit memo
- Automated GST checks
- 2,200+
- Automated GST checks
- Indian bank statement channels
- 77+
- Indian bank statement channels
Automated underwriting
What automated credit underwriting does for a lender
Most Indian business lenders still underwrite by hand: an analyst downloads a bureau report, asks the borrower for six or twelve months of bank statements, pulls GST returns, spreads the financials in Excel, and writes a credit appraisal memo. Every step is slow, and the quality of the decision depends on which analyst picked up the file. Automated underwriting software runs the same steps in parallel and applies one policy to every application.
Collects and normalises data
Pulls bureau, GST, bank, KYC and company data into one borrower record instead of five portals and an email thread.
Cross-checks every source
Flags contradictions such as healthy GST filings alongside frequent bank bounces, or a struck-off promoter behind a clean bureau record.
Recommends and documents
Scores the borrower against your rules, recommends exposure and produces a committee-ready credit memo your team can review and sign off.
The bigger gain is usually consistency rather than speed. When the same rules run on every file, decisions stop varying by analyst, deviations become visible, and the credit team spends its time on judgement calls instead of data entry. For a deeper walkthrough of each stage, read our guide to the credit underwriting process for NBFCs in India.
Data sources
Data sources used in GST based credit assessment and beyond
CARMA Assess triangulates 13 core data engines into a single risk view. Each source answers a different question, and the value comes from checking them against each other.
GST returns
Turnover trends, filing discipline, buyer and supplier concentration, related-party signals and HSN-based benchmarking.
Credit bureau
Repayment history, delinquency patterns, existing leverage across lenders and score drift over time.
Bank statements via Account Aggregator
Consent-based statement fetch through the AA framework, or PDF upload, for real cash-flow strength and bounce behaviour.
Financial statements
Balance sheet and P&L auto-spread into ratios, with DSCR and industry benchmarking.
MCA records
Ownership structure, director linkages, charge creation and corporate compliance history.
Statutory & litigation
Recovery actions, adverse proceedings and enforcement history against the entity and its promoters.
CPV / field investigation
Contact point verification and field investigation outcomes folded into the same file, not tracked in a separate spreadsheet.
Bank data can be fetched with borrower consent through the Account Aggregator framework, which avoids tampered PDFs and manual uploads. Field checks can be ordered and tracked through CPV and field verification so the physical verification result sits in the same file as the financial analysis.
Bank statement analyser
Bank statement analysis that checks the cash behind the numbers
For most MSME borrowers, the bank statement is the most honest document in the file. The bank statement analyser parses PDF statements from 77+ Indian bank channels, or consumes AA-fetched data, and extracts the signals an analyst would otherwise tag by hand.
Learn the fundamentals in our glossary entry on bank statement analysis or the detailed MSME underwriting guide.
- Monthly credits and debits, average balances and cash-flow volatility
- Income quality: genuine business receipts versus self-transfers and round-tripping
- Existing EMI burden, useful for FOIR and repayment-capacity checks
- Cheque and ECS bounces, and inward return patterns
- Customer and vendor concentration in inflows and outflows
- Stress indicators and circular banking patterns
- Bank inflows mapped against GST-declared turnover and bureau exposure, with mismatches flagged automatically
GST analytics
GST analytics with 2,200+ automated checks
GST data turns into a live view of the borrower's business. The GST Analysis module runs 2,200+ automated checks and produces a GST behaviour score that often surfaces risks a bureau score or ITR alone would miss. See how lenders are using it in AI credit scoring with GST data.
- Sales trends, growth patterns and seasonality
- Buyer and seller concentration and related-party relationships
- GSTR filing regularity and reconciliation behaviour
- HSN-based industry benchmarking
- Working capital cycle indicators
- Declared turnover compared with actual bank inflows
Policy engine
Scorecards and a configurable business rule engine
Your credit policy should live in a system, not in an analyst's memory. The Business Rule Engine converts policy into rules that run on every application, with a 6-dimension borrower rating and industry-aware weighting, tuned for tickets from Rs 5 Cr to Rs 5,000 Cr.
Eligibility and knock-out rules
Vintage, turnover, bureau and banking thresholds applied automatically, with deviations routed to the right approver.
Repayment-capacity ratios
Financial statements are auto-spread into ratios including DSCR, benchmarked against the borrower's industry.
Approval hierarchy
Configurable Delegation of Powers matrices, with every comment and approval captured in the audit trail.
Auto CAM
Auto-CAM: a committee-ready credit memo in under 10 minutes
Writing a Credit Appraisal Memo (CAM) is normally a 2-3 day manual task. Auto-CAM, part of CARMA Core, reads financial statements, GST returns, bank statements and bureau data simultaneously, cross-references them for consistency, and assembles the memo in under 10 minutes.
It is multi-signal aware: contradictions between what GST filings, bank inflows and bureau records say about a borrower are called out in the memo, and recommendations are confidence-rated rather than a black-box score, so the credit committee can see the reasoning.
What goes into the memo
- Borrower and promoter profile with MCA and KYC details
- Banking, GST and financial analysis in one narrative
- Bureau summary, existing obligations and leverage
- Policy checks passed, failed and deviated
- Red flags and cross-source contradictions
- Recommended exposure with a confidence rating
Post-disbursement monitoring
Post-disbursement monitoring and Early Warning Signals
Underwriting does not end at sanction. Early Warning Signals re-read the portfolio on a monthly-to-quarterly cycle and separate temporary liquidity stress from structural credit deterioration, so action happens before a slow decline turns into a default. Read more in our article on early warning signals for NBFCs.
Missed or irregular GST filings
Bureau score drift and new unsecured borrowings
Rising bank bounce rates and EMI bounce streaks
Covenant breaches and late MIS submissions
When a threshold is breached, the account can be flagged automatically, limit enhancements blocked, disbursals paused, or the case routed to collections, turning your credit policy into an always-on decision engine rather than a quarterly review exercise.
Comparison
Manual vs automated underwriting
How a typical MSME loan file moves through a manual process compared with CarmaOne. For a deeper comparison, see automated credit underwriting software in India.
| Step | Manual underwriting | Automated with CarmaOne |
|---|---|---|
| Data collection | Analyst logs into separate portals and chases PDFs over email | Bureau, GST, CKYC, NSDL and Account Aggregator pulls run in parallel |
| Bank statement review | Line-by-line reading and spreadsheet tagging | Parsed from 77+ bank channels with cash flow, EMI burden and bounces extracted |
| GST analysis | Spot checks on a few returns | 2,200+ automated checks and a GST behaviour score |
| Cross-verification | Depends on the analyst noticing a mismatch | GST turnover, bank inflows and bureau exposure reconciled on every file |
| Credit policy | Applied differently by different analysts | Business Rule Engine applies the same policy to every application |
| Credit memo | 2-3 days to assemble a CAM | Auto-CAM produces a committee-ready memo in under 10 minutes |
| Analyst time per file | Roughly 3 hours | About 15 minutes of review |
| After disbursement | Periodic manual reviews, often annual | Monthly-to-quarterly re-grading with Early Warning Signals |
Who it is for
Who uses automated underwriting for NBFC and bank lending
Built for regulated lenders writing business credit in India, from small proprietorships to corporates. Use our MSME loan eligibility and underwriting checklist to benchmark your current process.
NBFCs
MSME, business loan and working capital lenders that need consistent decisions as application volumes grow without growing the credit team at the same rate.
Banks
Business banking and MSME desks that want a faster, auditable appraisal layer above the core banking system.
Small finance banks
SFBs underwriting thin-file proprietorships and partnerships where bank and GST behaviour say more than a balance sheet.
Fintech lenders
Digital lenders and lending service providers that need API-first underwriting built into a digital journey.
Co-lending partnerships
Bank-NBFC co-lending programmes where both partners need to see the same data, the same policy checks and the same memo.
Supply chain finance
Dealer, distributor and vendor finance programmes underwriting many small counterparties linked to an anchor.
Integration
Integration with your LOS, LMS and core banking system
You do not have to replace your stack to automate underwriting. Choose the route that fits your technology roadmap.
Modular APIs
Keep your current LOS and LMS and add only the modules you need: Auto-CAM, GST Analysis, Bank Statement Analysis, Financial Statement Analysis, the Business Rule Engine or Early Warning Signals, as pay-per-use APIs alongside your CBS.
Full credit operations layer
CARMA Core combines LOS, LMS, supply chain finance, Auto-CAM and Early Warning Signals in one layer that sits above your core banking system and writes back through H2H and API integration. Your CBS remains the book of record.
Compliance
Built for RBI digital lending, KYC and data protection requirements
Automated underwriting has to be explainable and auditable. Lenders remain responsible for meeting the RBI Master Directions(opens in a new tab), and the platform is designed to support those obligations rather than work around them.
RBI Digital Lending Directions
Every policy check, deviation, comment and approval is captured in an audit trail, so a credit decision can be reconstructed and explained during inspection.
KYC Master Direction
CKYC and NSDL data pulls sit inside the underwriting workflow, so identity checks are recorded alongside the credit assessment.
DPDP Act, 2023
Consent-based data access through Account Aggregator, 256-bit AES encryption at rest and in transit, and SOC 2 Type II and ISO 27001 controls help lenders handle borrower data responsibly.
Deployment
How deployment works
CARMA Assess goes live in under a week with no engineering effort. A full CARMA Core deployment typically takes 4-6 weeks, with AI modules switched on progressively as usage scales.
Step 1: Policy discovery
We map your products, ticket sizes, eligibility rules, deviation norms and approval hierarchy, and translate them into Business Rule Engine configuration.
Step 2: Data integrations
Bureau, GST, Account Aggregator, CKYC, NSDL and banking connections are switched on, along with any analyser feeds you already pay for.
Step 3: Parallel run
Your analysts underwrite live files both ways so the team can compare automated outputs and the CAM format against current practice.
Step 4: Go-live
Automated underwriting becomes the default path, with deviations and exceptions routed to the right approvers under your DOP matrix.
Step 5: Monitor and extend
Early Warning Signals are switched on for the disbursed book, and further modules or products are added as usage scales.
Credit underwriting software FAQs
Common questions from NBFC, bank and fintech credit teams
Credit underwriting software automates the work an analyst does before a credit decision: pulling borrower data, reading bank statements, GST returns, bureau reports and financials, checking them against each other and against the lender's credit policy, and producing a recommendation with a credit memo. CarmaOne delivers this through CARMA Assess, which triangulates 13 core data engines into one risk view, and the Auto-CAM module of CARMA Core, which assembles a committee-ready Credit Appraisal Memo.
Lenders moving from manual review of bank statements, GST data, bureau reports and financials typically go from roughly three hours of analyst time per file to about 15 minutes, because data pulls, classification and scoring run in parallel and the analyst reviews a completed risk view instead of assembling one. Auto-CAM turns what is normally a 2-3 day credit memo exercise into a committee-ready memo in under 10 minutes.
No. The software removes data gathering, spreading and cross-checking, and applies your credit policy consistently to every file. Credit judgement, deviations and sanction authority stay with your team and your Delegation of Powers matrix. Auto-CAM outputs confidence-rated recommendations rather than a black-box score, so analysts can see why a file was flagged.
Bank statement analysis parses PDF statements from 77+ Indian bank channels and can also consume statements fetched through the Account Aggregator framework. Alongside bank data, the platform reads GST returns (with 2,200+ automated checks), credit bureau data, financial statements, MCA records, statutory and litigation records, and CKYC and NSDL data pulls.
An analyser answers what is in a document. CARMA Assess answers whether to lend, how much, and what has changed since. It adds cross-source contradiction detection (GST turnover vs bank inflows vs bureau exposure), fraud patterns that only appear across sources, post-disbursement monitoring, and portfolio-level risk views. If you already pay for an analyser, CARMA Assess can consume that feed rather than duplicate it.
Yes. You can run the full CARMA Core stack, or keep your current LOS/LMS and add only the modules you need - Auto-CAM, GST Analysis, Bank Statement Analysis, Financial Statement Analysis, the Business Rule Engine or Early Warning Signals - as APIs alongside your existing CBS. CARMA Core sits above the CBS rather than replacing it.
CARMA Assess goes live in under a week with no engineering effort on your side. A full CARMA Core deployment, including LOS/LMS configuration and integrations with bureau, GST, banking and Account Aggregator, typically takes 4-6 weeks.
The platform is SOC 2 Type II certified and ISO 27001 compliant, encrypts data with 256-bit AES at rest and in transit, keeps a complete audit trail of every action, comment and approval, and supports configurable DOP approval matrices. CARMA Core is aligned to RBI IRAC norms for asset classification and provisioning.
Further reading on credit underwriting
See automated underwriting on your own loan files
Bring a few recent MSME applications and we will walk through how CarmaOne reads the bank statements, GST returns and bureau data, applies your policy and produces the Auto-CAM memo.
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