Ask about any borrower's bank data. See the reasoning behind the answer.
Finarkein connects consented AA data to plain-language risk answers, showing each calculation for team audit.
Consent-first. RBI AA framework. No data stored after query.
Analyst asks:
Result
Avg EMI: Rs 18,400 / mo
Credit underwriting still takes hours of manual statement checks
A typical loan analyst spends 3 to 6 hours per file extracting PDF statements, making spreadsheets, and manually flagging anomalies. At volume, the process fails and remains unseen by the wider credit team.
The India AA framework gives lenders direct, consented financial-data access. Finarkein adds a query layer, letting analysts ask questions rather than search documents.
Based on pilot feedback from 3 NBFC lending teams in our early-access program.
From consent to answer in one session
Three steps link your credit team to answers in a borrower's data, while keeping each step visible and auditable.
The borrower approves sharing through their bank's AA-compliant app. No manual PDFs. Finarkein receives a secure, time-limited data token.
Your credit analyst asks plainly: "Is the EMI-to-income ratio within policy?" Finarkein reads data and computes the answer.
Each answer displays its calculation: the transactions used, months averaged, and policy thresholds applied. The full team can audit it.
What credit teams say
We once spent two days per SME application pulling statements and assembling the income picture. Now we ask Finarkein and see the calculations alongside their transaction sources.
Early-access participant
The audit trail convinced our credit committee. They can see precisely which transactions support the answer, rather than a score without evidence.
Pilot design partner
For SME credit, verifying income was hardest: no payslips and variable cash flows. Finarkein lets us query turnover patterns directly from bank data and inspect reasoning our risk committee can support.
Delhi NCR, early-access program
Built for every lending segment
For personal loans, BNPL, SME credit, or housing finance, the same query method applies to the data.
Personal and business loan underwriting
Query income stability, EMI history, and working-capital gaps across up to 24 months of bank data. Find salary irregularities and overdue obligations without manual review.
Short-term credit signals
For BNPL products, query spending volatility, recurring small debits, and overdraft frequency across recent 90-day data windows.
Turnover and cash flow for small businesses
Verify business turnover through credit entries, find seasonality, and assess working-capital cycles for SMEs without formal financial statements.
Income proof and EMI affordability
Confirm salary credits as income proof, calculate the proposed EMI affordability ratio, and identify co-borrower contributions from joint-account data.
Consent-first, zero-retention architecture
Finarkein does not store borrower data. Each fetch is consent-gated and processed ephemerally, retaining only the query answer and reasoning trail.
Clear tiers for lending teams of every size
Every plan includes AA framework integration, query history, and audit-trail export.
2 analyst seats, 500 queries/month, query audit log
10 analyst seats, 3,000 queries/month, API access + custom policy thresholds
Unlimited analysts, custom integrations, dedicated support SLA
See Finarkein answer a real credit question
Watch a risk analyst query borrower data and receive a structured answer with visible reasoning in under a minute.