Feature Selection to Optimize Credit Banking Risk Evaluation Decisions for the Example of Home Equity Loans

2021 ◽  
Author(s):  
Agustin Pérez-Martín ◽  
Agustin Pérez-Torregrosa ◽  
Alejandro Rabasa ◽  
Marta Vaca
Keyword(s):  
Feature Selection ◽  
Risk Evaluation ◽  
Home Equity ◽  
Home Equity Loans ◽  
Banking Risk

scholarly journals Feature Selection to Optimize Credit Banking Risk Evaluation Decisions for the Example of Home Equity Loans

Mathematics ◽  
2020 ◽  
Vol 8 (11) ◽  
pp. 1971
Author(s):  
Agustin Pérez-Martín ◽  
Agustin Pérez-Torregrosa ◽  
Alejandro Rabasa ◽  
Marta Vaca
Keyword(s):  
Feature Selection ◽  
Financial Institutions ◽  
Credit Scoring ◽  
Feature Selection Method ◽  
Capital Allocation ◽  
Risk Level ◽  
Home Equity ◽  
Home Equity Loans ◽  
The Mean ◽  
Basel Agreement

Measuring credit risk is essential for financial institutions because there is a high risk level associated with incorrect credit decisions. The Basel II agreement recommended the use of advanced credit scoring methods in order to improve the efficiency of capital allocation. The latest Basel agreement (Basel III) states that the requirements for reserves based on risk have increased. Financial institutions currently have exhaustive datasets regarding their operations; this is a problem that can be addressed by applying a good feature selection method combined with big data techniques for data management. A comparative study of selection techniques is conducted in this work to find the selector that reduces the mean square error and requires the least execution time.

Big Data techniques to measure credit banking risk in home equity loans

2018 ◽  
Vol 89 ◽  
pp. 448-454 ◽  
Author(s):  
A. Pérez-Martín ◽  
A. Pérez-Torregrosa ◽  
M. Vaca
Keyword(s):  
Big Data ◽  
Home Equity ◽  
Home Equity Loans ◽  
Banking Risk

Home Equity Lending and Retail Spending: Evidence from a Natural Experiment in Texas

2012 ◽  
Vol 4 (4) ◽  
pp. 94-125 ◽  
Author(s):  
Chadi S Abdallah ◽  
William D Lastrapes
Keyword(s):  
Natural Experiment ◽  
Credit Constraints ◽  
Constitutional Amendment ◽  
Aggregate Level ◽  
Home Equity ◽  
Credit Constraint ◽  
Household Level ◽  
Credit Availability ◽  
Level Data ◽  
Home Equity Loans

We estimate how spending in Texas responded to a 1997 constitutional amendment that relaxed severe restrictions on home equity lending. We use this event as a natural experiment to estimate the importance of credit constraints. If households are credit-constrained, such an increase in credit availability will increase their spending. We find that Texas retail sales at the county and state levels increased significantly after the amendment, lending support to the credit-constraint hypothesis. We confirm these findings and refine our interpretation of the estimated aggregate-level responses using household-level data on home equity loans. (JEL D14, E21, G21, G28)

A feature selection enabled hybrid-bagging algorithm for credit risk evaluation

2017 ◽  
Vol 34 (6) ◽  
pp. e12217 ◽  
Author(s):  
Shashi Dahiya ◽  
S.S. Handa ◽  
N.P. Singh
Keyword(s):  
Feature Selection ◽  
Credit Risk ◽  
Risk Evaluation
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