IME - Building a Credit Risk Analytics Model with High Prediction Accuracy

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mohamed-khamis
mohamed-khamis Partner, L2 Admin, L2 Designer, Dataiku DSS Core Designer, Dataiku DSS & SQL, Dataiku DSS ML Practitioner, Dataiku DSS Core Concepts, Snowflake Advanced, Dataiku DSS Adv Designer, Registered, Dataiku DSS Developer, Dataiku Frontrunner Awards 2021 Participant, Frontrunner 2022 Participant Posts: 13 Partner

Name: Mohamed AbdElAziz Khamis Omar

Title: Head of Data Science

Country: Egypt

Organization: IME

IME is a key market player in Data Management solutions. To learn more: www.infme.com

Awards Categories:

  • Data Science for Good
  • Moonshot Pioneer(s)

Business Challenge:

  • Credit Risk Analytics Module; Home Equity Mortgage loan fault perdition.
  • Due to data privacy of the bank, we trained the model on a generic dataset.

The data set HMEQ reports characteristics and delinquency information for 5,960 home equity loans. A home equity loan is a loan where the obligor uses the equity of his or her home as the underlying collateral. The data set has the following characteristics:

  • BAD: 1 = applicant defaulted on loan or seriously delinquent; 0 = applicant paid loan
  • LOAN: Amount of the loan request
  • MORTDUE: Amount due on existing mortgage
  • VALUE: Value of current property
  • REASON: DebtCon = debt consolidation; HomeImp = home improvement
  • JOB: Occupational categories
  • YOJ: Years at present job
  • DEROG: Number of major derogatory reports
  • DELINQ: Number of delinquent credit lines
  • CLAGE: Age of oldest credit line in months
  • NINQ: Number of recent credit inquiries
  • CLNO: Number of credit lines
  • DEBTINC: Debt-to-income ratio The goal of this use case is to build a model that borrowers can use to help make the best financial decisions.

Business Solution:

Using Dataiku AutoML.

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Business Area: Accounting/Finance

Use Case Stage: Proof of Concept

Value Generated:

Credit Risk Analytics Model with high prediction accuracy; AUC ROC = 0.974.

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Value Brought by Dataiku:

Built-in Analysis and AutoML tools.

Value Type:

  • Reduce cost
  • Reduce risk
  • Save time
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