Developers

Import the collection, then set the base_url and api_key collection variables. Every request is pre-wired with Authorization: Bearer {{api_key}}.

Also at docs/Credit_Engine_API.postman_collection.json.

# 1. Sign up (or grab a key from the API keys page)
curl -X POST http://localhost:3000/api/signup \
  -H "Content-Type: application/json" \
  -d '{"email":"you@lender.com","org_name":"Acme Lending","password":"change-me-8+"}'

# 2. Call the Credit Engine with your key
curl -X POST http://localhost:3000/v1/evaluate \
  -H "Authorization: Bearer {{api_key}}" \
  -H "Content-Type: application/json" \
  -d '{
    "bureau": "crif",
    "report": { "crif": {
      "scoreData": { "score": 770 },
      "demographics": { "age": 34, "employmentType": "salaried" },
      "incomeAssessment": { "monthlyIncome": 60000, "foir": 28 },
      "requestedAmount": 30000
    }}
  }'

Every block below is optional and purely additive. Each one derives extra inputs — it never decides anything. Omit a block and the field it would have produced is simply absent, which the engine treats as default-deny, so the decision is byte-for-byte what it would have been without it. Whether any of these fields matters is decided by your rules: reference them from a condition_ast knockout or a scorecard factor.

# Same call, with the optional intelligence blocks attached
curl -X POST http://localhost:3000/v1/evaluate \
  -H "Authorization: Bearer {{api_key}}" \
  -H "Content-Type: application/json" \
  -d '{
    "bureau": "crif",
    "report": { "crif": { "scoreData": { "score": 770 } } },
    "features": true,
    "device":   { "is_emulator": false, "is_rooted": false,
                  "sim_age_days": 820, "loan_apps_installed_count": 2 },
    "location": { "lat": 12.977, "lng": 77.60, "ip": "203.0.113.9",
                  "declared_pincode": "560001" },
    "fraud":    { "applicant_ref": "BORROWER-9f2c", "pincode": "560001",
                  "beneficiary_account": "50100123456789" }
  }'

# -> response gains "features" { count, vector_hash, top_contributors, used_by_policy }
#    and "fraud" { fraud_score, score_breakdown, signals, device, location }