Oraculi scoring

Summary

Scoring has never been simpler. With this service, you can easily score your lenders based on the settings you configured in your decision models.

Introduction

This endpoint is used for scoring based on the passed parameters/data points. By default, Lendsqr provides you with a proprietary scoring model and its sample request payload which you can tweak to your specification

However, you can pass any data point you wish to; provided that you have configured the scoring model to accept this. Below is a sample request and response body:

It is highly important to you set the specific decision model you wish to use for scoring.

Name	Type	Description
id	Integer	The decision model ID you wish to use. The Get Models API returns this value

curl --location 'https://adjutor.lendsqr.com/v2/decisioning/models/2355' \
--data-raw '{
    "gender": "Female",
    "marital_status": "Single",
    "age": "21",
    "location": "lagos",
    "no_of_dependent": "0",
    "type_of_residence": "Rented Apartment",
    "educational_attainment": "BSc, HND and Other Equivalent",
    "employment_status": "Employed",
    "sector_of_employment": "Other Financial",
    "monthly_net_income": "100,000 - 199,999",
    "employer_category": "Private Company",
    "bvn": "22536051111",
    "phone_number": "08012345678",
    "total_years_of_experience": 5,
    "time_with_current_employer": 2,
    "previous_lendsqr_loans": 3,
    "phone": "07062561111",
    "bvn_phone": "07062561111",
    "office_email": "[email protected]",
    "personal_email": "[email protected]",
    "amount": 10000
}'

{
   "status":"success",
   "message":"Successful",
   "data":{
      "credit_score_items":[
         {
            "score_name":"age",
            "score_value":"21 - 30",
            "weight":"7",
            "maximum_score":10,
            "borrower_score":0,
            "weighted_score":0
         },
         {
            "score_name":"gender",
            "score_value":"Female",
            "weight":"10",
            "maximum_score":10,
            "borrower_score":10,
            "weighted_score":0.0909
         },
         {
            "score_name":"location",
            "score_value":"lagos",
            "weight":"5",
            "maximum_score":10,
            "borrower_score":9,
            "weighted_score":0.0409
         },
         {
            "score_name":"customer_tier",
            "weight":"5",
            "maximum_score":10,
            "borrower_score":0,
            "weighted_score":0
         },
         {
            "score_name":"marital_status",
            "score_value":"Single",
            "weight":"5",
            "maximum_score":10,
            "borrower_score":6,
            "weighted_score":0.0273
         },
         {
            "score_name":"employer_category",
            "weight":"0",
            "maximum_score":10,
            "borrower_score":0,
            "weighted_score":0
         },
         {
            "score_name":"employment_status",
            "score_value":"Employed",
            "weight":"10",
            "maximum_score":10,
            "borrower_score":10,
            "weighted_score":0.0909
         },
         {
            "score_name":"type_of_residence",
            "score_value":"Rented Apartment",
            "weight":"5",
            "maximum_score":10,
            "borrower_score":10,
            "weighted_score":0.0455
         },
         {
            "score_name":"monthly_net_income",
            "score_value":"100,000 - 199,999",
            "weight":"10",
            "maximum_score":10,
            "borrower_score":6,
            "weighted_score":0.0545
         },
         {
            "score_name":"no_of_dependent",
            "score_value":"0",
            "weight":"8",
            "maximum_score":10,
            "borrower_score":0,
            "weighted_score":0
         },
         {
            "score_name":"sector_of_employment",
            "score_value":"Other Financial",
            "weight":"5",
            "maximum_score":10,
            "borrower_score":6,
            "weighted_score":0.0273
         },
         {
            "score_name":"educational_attainment",
            "weight":"5",
            "maximum_score":10,
            "borrower_score":0,
            "weighted_score":0
         },
         {
            "score_name":"total_years_of_experience",
            "weight":"5",
            "maximum_score":10,
            "borrower_score":4,
            "weighted_score":0.0182
         },
         {
            "score_name":"time_with_current_employer",
            "score_value":1,
            "weight":"5",
            "maximum_score":10,
            "borrower_score":2,
            "weighted_score":0.0091
         },
         {
            "score_name":"previous_paid_loans_on_pecunia",
            "weight":"25",
            "maximum_score":10,
            "borrower_score":0,
            "weighted_score":0
         }
      ],
      "total_weight":110,
      "score":40.46
   },
   "meta":{
      "balance":50000
   }
}

This provides you with an intuitive way of customer scoring.