Micro-lenders & small NBFCs
Problem: Thin files, no credit history, field agents collecting paper statements.
What you get: One upload returns an income estimate, DTI, EMI load per lender, bounce history and a fraud score. Seconds, not a procurement thread.
monthly_income_estimate + stabilitydebt_to_income_ratioemi.per_lenderbounces.by_typefraud_score
BNPL platforms
Problem: Checkout-time decisions in under 2 seconds; can't wait for manual review.
What you get: Affordability in seconds: income, fixed obligations, recent bounces. Enough to set a real-time limit or a down-payment.
expense_to_income_ratiofixed_obligations_ratiobounces.countfraud.verdict
Gig-income underwriting
Problem: Variable earnings from Uber, DoorDash, Upwork — salary slips don't exist.
What you get: Recurring-credit detection splits salary-like vs business-like income and scores stability across months, so variable earners get fair limits instead of auto-declines.
recurring_credits.business_likeincome_stability_scoremonthly_income_by_month
Landlord & tenant screening
Problem: Credit pulls are slow, expensive, and miss cash-flow reality.
What you get: Rent-to-income, cash intensity, and overdraft flags from 3 months of statements — no credit pull, applicant uploads directly, report in seconds.
estimated_monthly_rentcash_intensityoverdraft_penalty_flagsnet_surplus
Accountants & bookkeepers
Problem: Client PDFs every month-end; manual entry eats the margin.
What you get: Converter for the books, Analyser for the advice: raw Excel plus categorised spend and a top-vendor breakdown.
transactions[].categorytop_spending_categoriespayment_mode
Freelance underwriting consultants
Problem: Need bank-grade signals without an enterprise contract.
What you get: Run applicant files through the Analyser and paste the signals into your own report. The sample report shows clients what it produces.
extraction.confidencebalance_chain