---
title: Credit Scoring with ML
description: Credit Scoring with ML
image: https://joonsolutions.com/wp-content/uploads/2021/06/credit-1024x969.png
---

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# Credit Scoring with ML

[Casper](https://blog.joonsolutions.com/refined-and-refactored/author/casper)

 Dec 3, 2021 11:00:43 PM

 

 

 

![](https://joonsolutions.com/wp-content/uploads/2021/06/credit-1024x969.png)

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Ameriprise Financial, Inc. is a diversified financial services company and bank holding company incorporated in Delaware and headquartered in Minneapolis, Minnesota. It provides financial planning products and services, including wealth management, asset management, insurance, annuities, and estate planning.

## Use case: Beating traditional credit score methods with Machine Learning

 

Ameriprise  wanted to see the impact of using Machine Learning vs traditional credit score methods to predict if a customer would go into credit default

Joon’s platform was used to ingest the data, automatically transform it, create features and build ML models

The results were a ML model that was able to predict credit default better to the point it caught 83% of bad debt not caught by credit score while refusing loans to the same number of customers

The model could be reversed and 77% more people could be offered loans if the bank wanted to keep their current default rate

This AI model was ready for production in 4 weeks

![](https://joonsolutions.com/wp-content/uploads/2021/06/credit-1024x969.png)

 

## Use Case Results

![](https://joonsolutions.com/wp-content/uploads/2021/06/Credit-scoring-from-tree-based-model-1024x435.jpg)

**The results were much better than anyone anticipated, catching 83% of bad debt not caught by credit score. Which drastically reduces exposure to credit risk. Should they want to keep the same rate of default, they could lend to 77% more people.**

 

 

 

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