Consumer Loans (/api/v1/loans)

Endpoints for creating, managing, extracting, and predicting risk for Consumer Loan Applications.

1. Predict Risk (Consumer Loan)

Execute the risk prediction algorithm on a consumer loan based on JSON input.

• Method: POST
• Endpoint: /api/v1/loans/predict
• Authentication: Required (API Key)
• Headers:
  • X-API-Key: <your_api_key>
  • Content-Type: application/json

Request Body

{
  "loan_amnt": 15000,
  "int_rate": 10.5,
  "annual_inc": 85000,
  "dti": 12.5,
  "open_acc": 10,
  "total_acc": 25,
  ...
}

cURL

curl -X POST https://api.riskinmind.ai/api/v1/loans/predict \
  -H "X-API-Key: YOUR_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "loan_amnt": 15000,
    "int_rate": 10.5,
    "annual_inc": 85000,
    "dti": 12.5,
    "open_acc": 10,
    "total_acc": 25
  }'

Python

import requests

url = "https://api.riskinmind.ai/api/v1/loans/predict"
headers = {
    "X-API-Key": "YOUR_API_KEY",
    "Content-Type": "application/json"
}
data = {
    "loan_amnt": 15000,
    "int_rate": 10.5,
    "annual_inc": 85000,
    "dti": 12.5,
    "open_acc": 10,
    "total_acc": 25
}

response = requests.post(url, headers=headers, json=data)
print(response.json())

JavaScript

const response = await fetch('https://api.riskinmind.ai/api/v1/loans/predict', {
  method: 'POST',
  headers: {
    'X-API-Key': 'YOUR_API_KEY',
    'Content-Type': 'application/json'
  },
  body: JSON.stringify({
    loan_amnt: 15000,
    int_rate: 10.5,
    annual_inc: 85000,
    dti: 12.5,
    open_acc: 10,
    total_acc: 25
  })
});

const data = await response.json();
console.log(data);

Response

• Content-Type: application/json

{
  "probability": 0.85,
  "rejection_probability": 0.15
}

2. Generate Reports (Consumer & Commercial)

These endpoints trigger report generation based on the loan's extracted data and return a PDF binary stream.

Consumer Report

• Method: POST
• Endpoint: /api/v1/loans/report/consumer
• Authentication: Required (API Key)
• Headers:
  • X-API-Key: <your_api_key>
  • Content-Type: application/json
• Body: Contains the same parameters used for /predict.
• Response Format: application/pdf binary stream.

Commercial Report

• Method: POST
• Endpoint: /api/v1/loans/report/commercial
• Authentication: Required (API Key)
• Headers:
  • X-API-Key: <your_api_key>
  • Content-Type: application/json
• Body: Contains the same parameters used for /predict.
• Response Format: application/pdf binary stream.

cURL

curl -X POST https://api.riskinmind.ai/api/v1/loans/report/consumer \
  -H "X-API-Key: YOUR_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "loan_amnt": 15000,
    "int_rate": 10.5,
    "annual_inc": 85000
  }' --output consumer_report.pdf

Python

import requests

url = "https://api.riskinmind.ai/api/v1/loans/report/consumer"
headers = {
    "X-API-Key": "YOUR_API_KEY",
    "Content-Type": "application/json"
}
data = {
    "loan_amnt": 15000,
    "int_rate": 10.5,
    "annual_inc": 85000
}

response = requests.post(url, headers=headers, json=data)
with open("consumer_report.pdf", "wb") as f:
    f.write(response.content)

JavaScript

const response = await fetch('https://api.riskinmind.ai/api/v1/loans/report/consumer', {
  method: 'POST',
  headers: {
    'X-API-Key': 'YOUR_API_KEY',
    'Content-Type': 'application/json'
  },
  body: JSON.stringify({
    loan_amnt: 15000,
    int_rate: 10.5,
    annual_inc: 85000
  })
});

const blob = await response.blob();
const url = window.URL.createObjectURL(blob);
const link = document.createElement("a");
link.href = url;
link.download = 'consumer_report.pdf';
document.body.appendChild(link);
link.click();

3. CECL Prediction Engine

Calculate Current Expected Credit Losses (CECL) using the RiskInMind financial math engine.

• Method: POST
• Endpoint: /api/v1/loans/cecl
• Authentication: Required (API Key)
• Headers:
  • X-API-Key: <your_api_key>
  • Content-Type: application/json

Request Body

[
  {
    "loanId": "loan_123",
    "exposureAtDefault": 50000,
    "probabilityOfDefault": 0.02,
    "lossGivenDefault": 0.45
  }
]

cURL

curl -X POST https://api.riskinmind.ai/api/v1/loans/cecl \
  -H "X-API-Key: YOUR_API_KEY" \
  -H "Content-Type: application/json" \
  -d '[
    {
      "loanId": "loan_123",
      "exposureAtDefault": 50000,
      "probabilityOfDefault": 0.02,
      "lossGivenDefault": 0.45
    }
  ]'

Python

import requests

url = "https://api.riskinmind.ai/api/v1/loans/cecl"
headers = {
    "X-API-Key": "YOUR_API_KEY",
    "Content-Type": "application/json"
}
data = [
    {
        "loanId": "loan_123",
        "exposureAtDefault": 50000,
        "probabilityOfDefault": 0.02,
        "lossGivenDefault": 0.45
    }
]

response = requests.post(url, headers=headers, json=data)
print(response.json())

JavaScript

const response = await fetch('https://api.riskinmind.ai/api/v1/loans/cecl', {
  method: 'POST',
  headers: {
    'X-API-Key': 'YOUR_API_KEY',
    'Content-Type': 'application/json'
  },
  body: JSON.stringify([
    {
      loanId: "loan_123",
      exposureAtDefault: 50000,
      probabilityOfDefault: 0.02,
      lossGivenDefault: 0.45
    }
  ])
});

const data = await response.json();
console.log(data);

Response

• Content-Type: application/json

{
  "totalExpectedLoss": 450.00,
  "breakdown": [ ]
}

4. 1003 Loan Application Generation

Generate a standardized Uniform Residential Loan Application (Form 1003) PDF. This endpoint synthesizes data from the borrower's profile, extracted documents, and the current loan application.

• Method: POST
• Endpoint: /api/v1/loans/1003
• Authentication: Required (API Key)
• Headers:
  • X-API-Key: <your_api_key>
  • Content-Type: application/json

cURL

curl -X POST https://api.riskinmind.ai/api/v1/loans/1003 \
  -H "X-API-Key: YOUR_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "userId": "user_456",
    "orgId": "org_789",
    "borrower": {
      "ssn": "XXX-XX-XXXX",
      "marital_status": "Married"
    }
  }' --output form_1003.pdf

Python

import requests

url = "https://api.riskinmind.ai/api/v1/loans/1003"
headers = {
    "X-API-Key": "YOUR_API_KEY",
    "Content-Type": "application/json"
}
data = {
    "userId": "user_456",
    "orgId": "org_789",
    "borrower": {
        "ssn": "XXX-XX-XXXX",
        "marital_status": "Married"
    }
}

response = requests.post(url, headers=headers, json=data)
with open("form_1003.pdf", "wb") as f:
    f.write(response.content)

JavaScript

const response = await fetch('https://api.riskinmind.ai/api/v1/loans/1003', {
  method: 'POST',
  headers: {
    'X-API-Key': 'YOUR_API_KEY',
    'Content-Type': 'application/json'
  },
  body: JSON.stringify({
    userId: "user_456",
    orgId: "org_789",
    borrower: {
      ssn: "XXX-XX-XXXX",
      marital_status: "Married"
    }
  })
});

const blob = await response.blob();
const url = window.URL.createObjectURL(blob);
const link = document.createElement("a");
link.href = url;
link.download = 'form_1003.pdf';
document.body.appendChild(link);
link.click();

Response

• Content-Type: application/pdf
• Returns: A binary PDF stream representing the completed 1003 form.