AI-Driven Creditworthiness Scoring — Validated with SPSS Discriminant Analysis
Enhance credit assessments with AI-driven precision, backed by SPSS-validated analytics for reliable and informed decisions every time.
The Challenge : Credit Decisions without Clarity
- Manual and time consuming evaluation - decisions based on gut feel
- Static scoring - unable to reflect realtime changes in partner behaviour
- Subjectivity - inconsistent criteria between decision makers
- High exposure risk - leading to overdue receivables and write offs
The AI/ML Model Working
Input Data
Dynamic input data
Train & Test Data
Data Set is divided into train and test data sets for model training and evaluation
Classification Model
Classification model to study the pattern
Model Evaluation
Model is evaluated with the accuracy level and predictability
Selecting the Model
Decision
Decision taken based on the model
AI/ML Model
- Credit decisions and now powered by trained classification model
- Model learns from past data and its dynamic
- With new data set the model predicts the desired O/P
- Model accuracy is used to choose the best model
SPSS Discriminant Analysis: Double-Checking Every Decision
To ensure our AI model’s predictions were not just fast but also trustworthy, we ran every output through SPSS Discriminant Analysis. This statistical technique tested how well our model separated high, medium and low and low-risk groups
The analysis confirmed:
Strong group separation (low Wilks’ Lambda values)
High classification accuracy — matching AI results in over 86% of cases
Clear predictor significance — identifying which variables drove the risk classification
This dual-layer approach gave the client speed from AI and confidence from statistics.
Results & Business Impact
Decision Time
Decision timr reduced by 55%
Risk Minimization
Protection against high risk exposure
Consistent & Dynamic
Model automatically rescore, consistent and objective decision making
Ready to Apply AI & Analytics to Your Credit Decisions?
Empower your business with a dynamic credit risk model that updates in real time — and is validated statistically for full confidence. Let’s explore how you can implement this for your suppliers, distributors, or customer credit evaluation.