Lending
Run the whole loan lifecycle.
Every customer conversation and every back-office task, application to payoff, on one system that validates each action before it fires.
Why lending stalls
The work is manual because the AI couldn’t be proven.
Lending runs on two workforces, the people who speak to customers and the people who keep the books, held apart by tickets, spreadsheets and hand-offs. Together they are 40–60% of what every loan costs. AI could close the gap, but a regulated action you can’t explain is a risk no lender will take. So the work stays manual.
KrimOS gates every action before it fires, so the work you couldn’t trust to software becomes work you can.
Validated, not audited after the fact
End to end
Both sides of the wall, on one system.
Kira meets the customer on every channel; Karta co-workers do the back-office work. They meet at every stage, and each action passes the validation gate before it executes.
Sourcing & onboarding
- Kira · customer
- Engages, qualifies and guides the application.
- Karta · back office
- Lead scoring, KYC and document processing.
Underwriting & decision
- Kira · customer
- Collects what is missing, sets expectations.
- Karta · back office
- Credit-analysis support, policy checks and sanction prep. The decision stays yours.
Disbursal
- Kira · customer
- Walks the borrower through the agreement and confirmation.
- Karta · back office
- Agreement generation, compliance checks and disbursal ops.
Servicing
- Kira · customer
- Payments, queries and statements, one advisor, always on.
- Karta · back office
- Account maintenance, reconciliation and monitoring.
Collections & hardship
- Kira · customer
- Reminders and plans, hardship handled with care.
- Karta · back office
- Risk segmentation, early warning and escalation.
Closure & re-engagement
- Kira · customer
- Payoff, the NOC, the next product conversation.
- Karta · back office
- Settlement, reporting and portfolio learning.
Today the line is clear: Karta segment risk, suggest the next best action and gate on your own flags. The credit decision stays yours. The safe AI underwriter we are building, the World Lending Model, is the direction, and it will clear the same validation gate as every action that runs today.
Compliance, built in
Your jurisdiction’s law, applied before each action.
The same architecture runs in every market. Only the rulebook changes. Each action is checked against the law where you lend before it executes, not after.
United States
Encoded & enforced before any action
What changes
Measured against your own baseline.
Illustrative ranges. Your real numbers come from your own operation.
Origination
More documents cleared per analyst
5–10×
throughput per FTE
Servicing
Handled without a human
40–70%
of routine requests
Collections
Lower early roll-rate
1–3 pp
reduction (1–30 DPD)
Compliance
Faster to audit-ready reporting
Minutes
down from days
It sharpens the longer it runs. The first quarter sets your baseline, gains show by Q2, and by year two it is materially ahead of go-live.
The learning curve
How it runs
Sovereign by construction, wherever you run it.
Three deployments, one architecture. Your data and your regulator decide which. Whichever you pick, everything stays inside the perimeter you draw, with no foreign model in the loop.
Deployment
Sovereign on-prem
The full stack inside your own data centre. Model, data and every action stay behind walls you already trust.
Deployment
Hybrid
Data and inference on-prem; orchestration and updates from Krim cloud. A line drawn where your regulator wants it.
Deployment
Managed
Run for you in your preferred sovereign cloud region, kept in-jurisdiction.
The loan book that pays for itself.
Every conversation handled, every action proven, every outcome compounding into the next. More borrowers reached, more loans closed, and a cost line that finally stops growing with the book.