Packets read by hand
Underwriters review 50 to 100-page mortgage packets and cross-check them against policy by hand. There is no structured audit trail behind the decision.
Use cases · Lending
Agents ingest the packet, extract and validate every field, run KYC and credit checks, spread the financials, and draft the underwriter brief, so officers review the exceptions instead of assembling the file.
under 1h approvalsup to 90% lower cost per file● in production
The work that has not moved is the work earlier automation could not reach: reading documents, cross-checking policy, and building a file a credit officer can defend.
Underwriters review 50 to 100-page mortgage packets and cross-check them against policy by hand. There is no structured audit trail behind the decision.
Unsecured loans are processed one application at a time. Approval takes days, and volume stalls because the platform to scale it is years away.
For corporate and SME credit, analysts spread the financials and write the memo manually. A single corporate memo can run two to three analyst days.
One flow from intake to disbursement. Agents ingest the packet, extract and validate every field, run KYC and credit checks, spread the financials, and draft the underwriter brief. Clean cases are approved straight through; the rest route to an officer with the exception already framed. Hover a team to see where its agents sit.
Mortgage and consumer lending leaders. The Head of Retail Lending owns the P&L, the Head of Consumer Lending owns the funnel, and the Chief Digital Officer sponsors modernization.
Corporate and SME credit teams. The Head of Corporate and SME Banking own the growth target, and the Head of Underwriting owns the operational change.
The required approvers. The Head of Credit Risk and the Chief Credit Officer sign off, and they need the evidence to do it with confidence.
Nine lending agents — what each one gathers, checks, and hands back to the credit desk.
Extracts parameters from uploaded client files and evaluates multi-bank eligibility instantly.
Validates payslips, contracts, and bank statements against the application.
Computes DSCR and validates the assumptions behind repayment capacity.
Checks LTV, encumbrances, and insurance across the collateral package.
Compares declared debts against bureau and statement data to test affordability.
Auto-builds structured, regulator-ready credit memos from the file.
Extracts financials and ratios from statements for underwriting.
Matches a client profile to the optimal products across partner banks, with fit scores.
Transforms forms into natural dialogue — recognizes existing customers, pre-fills known data, and adapts questions dynamically
“…pre-filled from your profile — just 3 questions left to submit.”
Pre-composed sets of agents, each scoped to one lending value stream — deploy the whole stack or pick the agents you need.
Income, title, appraisal, collateral, and debt checks assemble a complete, verified mortgage pack before an underwriter opens it.
Financials, collateral, use-of-funds, and repayment capacity validated and packaged for committee, pre-checked for completeness.
Balance-sheet extraction, KPI trends, market context, and auto-built credit memos turn raw statements into a defensible decision.
Broker copilots that guide client discovery, normalize income, match products across partner banks, and handle edge cases with explainable rationale.
Turns the application into a natural conversation — identity, eligibility, disclosures, and e-signature captured in-flow without breaking the dialogue.
Start from a stack or pick individual agents — they're built to work together on your value stream.
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