Underwriting policy decides clear applications, refers the rest
Applications sit in a checklist or rules buried in your origination system. Decisimo automates clear credit decisions in one call and refers the rest to an underwriter.
From application to the underwriter’s decision
Send application
Run the policy
Return decision
Send referral
Prepare the case
Underwriter decides
Post the decision
Clear applications decided in one call
- Knock-outA match ends the call before later rules and data calls run
- Data sourcesThey run together. A failed source leaves an error flag for the rules
- Decision and reasonEach table row can write both into the response
A referral reaches the underwriter with the work done
- Case referenceThe lender’s system sends it to a case type, which opens the case
- Payslip readingA document task makes text. A model task reads figures from it
- Underwriter decisionThe underwriter completes the role inbox form. Decisimo posts the decision back
The credit team changes the policy
- Policy editsEach save creates a revision across rule sets, tables, scorecards and functions
- Compare decisionsRun the same applications through both policies. Decisimo lists changed decisions
- New releaseAn endpoint can carry role sign-off before deployment
What stays in the lender’s systems
- Applicant portalThe lender collects applicant documents through its own systems
- Applicant servicesE-signature, identity verification and disbursement stay with the lender
- Applicant messagesThe lender’s systems send messages to the applicant
Questions we get asked
What is automated underwriting?
Automated underwriting is a credit policy expressed as decision logic that approves or declines applications it can decide and refers the rest for underwriter review. Decisimo runs that policy in one call, and the lender's system sends referrals to a case for an underwriter.
Can automated underwriting replace my loan origination system?
The lender’s system sends applications and referrals, and keeps applicant services such as document collection, e-signature and disbursement. Read about moving from a manual checklist
Can I use my own underwriting model?
A model trained in Python, R or Julia can be uploaded and called in a decision flow. A model task can also read figures from payslip text on a case.