Credit decisioning
A recommendation your officer can defend
Khepee scores an application and recommends an outcome. A person makes the decision. That boundary is deliberate — an automated rejection nobody can explain is a regulatory and reputational liability.
The scorecard
Rules you set, applied identically every time
The default engine is a transparent rule-based scorecard. You configure the factors and weights; it applies them consistently to every application, which is precisely what a manual process cannot promise.
- Income multiple against the requested instalment
- Existing obligations, where the borrower declares or your data shows them
- KYC quality and document consistency
- Repayment history with your institution on the platform
Explainability
The score arrives with its reasons
A number on its own tells an officer nothing they can act on or explain. Khepee surfaces the factors that moved the score and how far each one moved it.
- Factor-level contributions, not an opaque total
- Thresholds visible, so a borderline case is recognisable as one
- The recommendation is advisory and labelled as such
- What the audit trail records is the human decision and its stated reason
Extensibility
Room for bureau data and models, when you want them
The scoring engine sits behind an interface. Adding a credit bureau feed or your own model means implementing that interface — the origination workflow, the audit trail and the officer console do not change.
- A single `ScoringEngine` seam, versioned so old decisions stay interpretable
- Bureau integration behind the same vendor-interface discipline as KYC and payments
- A model can run in shadow mode against live applications before it influences anything
- The score version is recorded with the decision, so history remains explainable
Guardrails
What the engine is not permitted to do
Approve on its own
The engine recommends. Approval requires an officer with the permission to give it.
Exceed a regulatory limit
A recommendation above the NRB ceiling or the 36-month cap is rejected before it reaches an officer.
Use data outside its purpose
Scoring reads borrower data under the credit_assessment purpose, and that read is logged.
Why it matters
Consistency is the point
Indicative of what a codified credit policy changes. Actual outcomes depend on the policy you configure.
1
Credit policy
Applied identically regardless of branch, officer or day of the week.100%
Decisions with a reason
Adverse outcomes cannot be saved without one.0
Automated rejections
A human is accountable for every decline.Full
Reconstructability
Score, factors, officer and ruleset version, retained together.
Fair treatment
Designed so a borrower can be told why
A declined borrower who receives no explanation escalates — to your grievance channel, then sometimes to the regulator. The platform is built so a clear, accurate reason is always available.
- A declined application always carries a written reason
- The reason is retained for the full retention period
- Your grievance process can retrieve the full decision record
- Protected characteristics are not collected, so they cannot enter a score
Khepee provides the technology; your institution provides the credit
Khepee is a technology service provider operated by Lacspace Corporation Pvt. Ltd. It is not a bank or financial institution, does not lend, does not accept deposits and does not hold customer funds. All credit decisions, pricing and lending terms are set by the partner institution licensed by Nepal Rastra Bank. Khepee makes no claim of NRB licensing, approval or endorsement.
Coming soon
Model your credit policy with us
Bring your current underwriting rules and we will show you how they configure — and where the platform would stop you.