> ## Documentation Index
> Fetch the complete documentation index at: https://docs.fincept.in/llms.txt
> Use this file to discover all available pages before exploring further.

# Discrimination Metrics for Credit Models

> Calculates comprehensive discrimination metrics including Gini coefficient, KS statistic, AUC-ROC, and accuracy ratio. Essential for validating credit risk models and assessing their ability to distinguish between defaulters and non-defaulters. [Tier: ENTERPRISE, Credits: 10]



## OpenAPI

````yaml api-specs/ml.json post /quantlib/ml/credit/discrimination
openapi: 3.1.0
info:
  title: FinceptQuantLib API - ML
  description: >-
    Machine Learning and Credit Risk module endpoints for FinceptQuantLib API.
    Pro Tier access required (5 credits per request). Covers credit scoring,
    model validation, regression models, clustering, anomaly detection, feature
    engineering, and preprocessing.
  version: 3.0.0
  contact:
    name: Fincept API Support
    url: https://fincept.in
servers:
  - url: https://api.fincept.in
    description: Fincept API Production Server
security:
  - APIKeyHeader: []
tags:
  - name: quantlib-ml
    description: Machine Learning and Credit Risk Analytics
    x-displayName: ML
paths:
  /quantlib/ml/credit/discrimination:
    post:
      tags:
        - quantlib-ml
      summary: Discrimination Metrics for Credit Models
      description: >-
        Calculates comprehensive discrimination metrics including Gini
        coefficient, KS statistic, AUC-ROC, and accuracy ratio. Essential for
        validating credit risk models and assessing their ability to distinguish
        between defaulters and non-defaulters. [Tier: ENTERPRISE, Credits: 10]
      operationId: discrimination_metrics
      requestBody:
        required: true
        content:
          application/json:
            schema:
              type: object
              required:
                - y_true
                - y_score
              properties:
                y_true:
                  type: array
                  description: True binary labels (0 = non-default, 1 = default)
                  items:
                    type: integer
                    enum:
                      - 0
                      - 1
                  example:
                    - 0
                    - 0
                    - 1
                    - 1
                    - 0
                    - 1
                    - 0
                    - 1
                y_score:
                  type: array
                  description: Predicted probabilities or risk scores
                  items:
                    type: number
                  example:
                    - 0.12
                    - 0.23
                    - 0.87
                    - 0.92
                    - 0.15
                    - 0.78
                    - 0.09
                    - 0.85
      responses:
        '200':
          description: Discrimination metrics
          content:
            application/json:
              schema:
                type: object
                properties:
                  success:
                    type: boolean
                    example: true
                  data:
                    type: object
                    properties:
                      gini:
                        type: number
                        description: Gini coefficient (0-1, higher is better)
                        example: 0.756
                      ks_statistic:
                        type: number
                        description: Kolmogorov-Smirnov statistic
                        example: 0.623
                      auc_roc:
                        type: number
                        description: Area Under ROC Curve
                        example: 0.878
                      accuracy_ratio:
                        type: number
                        description: Accuracy Ratio (Gini/Perfect Gini)
                        example: 0.756
        '401':
          $ref: '#/components/responses/UnauthorizedError'
        '402':
          $ref: '#/components/responses/InsufficientCreditsError'
        '422':
          $ref: '#/components/responses/ValidationError'
components:
  responses:
    UnauthorizedError:
      description: Authentication information is missing or invalid
      content:
        application/json:
          schema:
            type: object
            properties:
              detail:
                type: string
                example: Invalid API key
    InsufficientCreditsError:
      description: Insufficient credits for this operation
      content:
        application/json:
          schema:
            type: object
            properties:
              detail:
                type: string
                example: Insufficient credits. This endpoint requires 5 credits.
    ValidationError:
      description: Request validation error
      content:
        application/json:
          schema:
            type: object
            properties:
              detail:
                type: array
                items:
                  type: object
                  properties:
                    loc:
                      type: array
                      items:
                        type: string
                    msg:
                      type: string
                    type:
                      type: string
  securitySchemes:
    APIKeyHeader:
      type: apiKey
      in: header
      name: X-API-Key
      description: >-
        API key for authentication. Get your key at
        https://api.fincept.in/auth/register

````