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.
Business Area: Accounting/Finance
Use Case Stage: Proof of Concept
Value Generated:
Credit Risk Analytics Model with high prediction accuracy; AUC ROC = 0.974.
Value Brought by Dataiku:
Built-in Analysis and AutoML tools.
Value Type:
- Reduce cost
- Reduce risk
- Save time
