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

Author

Listed:
  • Agustin Pérez-Martín

    (Economic and Financial Studies Department, Miguel Hernández University of Elche, 03202 Elche, Spain
    These authors contributed equally to this work.)

  • Agustin Pérez-Torregrosa

    (Economic and Financial Studies Department, Miguel Hernández University of Elche, 03202 Elche, Spain
    These authors contributed equally to this work.)

  • Alejandro Rabasa

    (Operations Research Center, Miguel Hernández University of Elche, 03202 Elche, Spain
    These authors contributed equally to this work.)

  • Marta Vaca

    (Economic and Financial Studies Department, Miguel Hernández University of Elche, 03202 Elche, Spain
    These authors contributed equally to this work.)

Abstract

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.

Suggested Citation

  • Agustin Pérez-Martín & Agustin Pérez-Torregrosa & Alejandro Rabasa & Marta Vaca, 2020. "Feature Selection to Optimize Credit Banking Risk Evaluation Decisions for the Example of Home Equity Loans," Mathematics, MDPI, vol. 8(11), pages 1-16, November.
    • Handle: RePEc:gam:jmathe:v:8:y:2020:i:11:p:1971-:d:440863
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    References listed on IDEAS

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    1. Wangwang Yan & Jing Ba & Taihua Xu & Hualong Yu & Jinlong Shi & Bin Han, 2022. "Beam-Influenced Attribute Selector for Producing Stable Reduct," Mathematics, MDPI, vol. 10(4), pages 1-20, February.
    2. Maria Patricia Durango‐Gutiérrez & Juan Lara‐Rubio & Andrés Navarro‐Galera, 2023. "Analysis of default risk in microfinance institutions under the Basel III framework," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 28(2), pages 1261-1278, April.

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