Featured Product

    BIS Paper Examines How Non-Traditional Data Affect Credit Scoring

    December 19, 2019

    BIS published a working paper that examines how machine learning and non-traditional data affect credit scoring. The paper compares the predictive power of credit scoring models based on machine learning techniques, as used by fintech companies, with that of traditional loss and default models typically used by banks. The results show that the model based on machine learning and non-traditional data used by the fintech company is better able to predict losses and defaults than traditional models in the presence of a negative shock to the aggregate credit supply.

    Using proprietary transaction-level data from a leading fintech company in China for the period between May and September 2017, the authors tested the performance of different models to predict losses and defaults, both in normal times and when the economy is subject to a shock. They analyzed the case of an (exogenous) change in regulation policy on shadow banking in China that caused lending to decline and credit conditions to deteriorate. The main conclusions of the paper can be summarized as follows:

    • The machine learning-based credit scoring models outperform traditional empirical models (using both traditional and non-traditional information) in predicting borrowers’ losses and defaults.
    • Non-traditional information improves the predictive power of the model.
    • While the models perform similarly well in normal times, the model based on machine learning is better able to predict losses and defaults following a negative shock to the aggregate credit supply. One possible reason for this is that machine learning can better mine the non-linear relationship between variables in the event of a shock.
    • The predictive power of all the models improves when the length of the relationship between bank and customer increases. However, the comparative advantage of the model that uses the fintech credit scoring technique based on machine learning tends to decline when the length of the relationship increases.

     

    Related Links

    Keywords: International, China, Banking, Machine Learning, Credit Scoring, Fintech, Credit Risk, Big Data, BIS

    Related Articles
    News

    PRA and FPC Finalize Changes to Leverage Ratio Framework in UK

    The Prudential Regulation Authority (PRA) published the final policy statement PS21/21 on the leverage ratio framework in the UK. PS21/21, which sets out the final policy of both the Financial Policy Committee (FPC) and PRA

    October 08, 2021 WebPage Regulatory News
    News

    CFPB Proposes Rule on Small Business Lending Data Collection

    The Consumer Financial Protection Bureau (CFPB) proposed to amend Regulation B to implement changes to the Equal Credit Opportunity Act (ECOA) under Section 1071 of the Dodd-Frank Act.

    October 08, 2021 WebPage Regulatory News
    News

    PRA Decides to Maintain O-SII Buffers for Another Year

    The Prudential Regulation Authority (PRA) decided to maintain, at the 2019 levels, the buffer rates for the Other Systemically Important Institutions (O-SII) for another year, with no new rates to be set until December 2023.

    October 08, 2021 WebPage Regulatory News
    News

    FSB Report Assesses Implementation of Recommendations on Stablecoins

    The Financial Stability Board (FSB) published a progress report on implementation of its high-level recommendations for the regulation, supervision, and oversight of global stablecoin arrangements.

    October 07, 2021 WebPage Regulatory News
    News

    APRA Updates Loan Serviceability Expectations for Home Lending

    In a letter to the authorized deposit taking institutions, the Australian Prudential Regulation Authority (APRA) announced an increase in the minimum interest rate buffer it expects banks to use when assessing the serviceability of home loan applications.

    October 06, 2021 WebPage Regulatory News
    News

    CPMI and IOSCO Consult on Guidance on Stablecoin Arrangements

    The Committee on Payments and Market Infrastructures (CPMI) and the International Organization of Securities Commissions (IOSCO) are consulting on the preliminary guidance that clarifies that stablecoin arrangements should observe international standards for payment, clearing, and settlement systems.

    October 06, 2021 WebPage Regulatory News
    News

    EBA and EIOPA Set Out Work Priorities for 2022

    The European Banking Authority (EBA) and the European Insurance and Occupational Pensions Authority (EIOPA) have set out their respective work priorities for 2022.

    October 05, 2021 WebPage Regulatory News
    News

    MFSA Issues Reporting Updates and Guidance for Banks

    The Malta Financial Services Authority (MFSA) updated the guidelines on supervisory reporting requirements under the reporting framework 3.0, in addition to the reporting module on leverage under the common reporting (COREP) framework.

    October 05, 2021 WebPage Regulatory News
    News

    EC Publishes Decision on List of Equivalent Third Countries Under CRR

    The European Commission (EC) published the Implementing Decision 2021/1753 on the equivalence of supervisory and regulatory requirements of certain third countries and territories for the purposes of the treatment of exposures, in accordance with the Capital Requirements Regulation or CRR (575/2013).

    October 04, 2021 WebPage Regulatory News
    News

    EC Rule on Contractual Recognition of Write-Down and Conversion Powers

    EC published the Implementing Regulation 2021/1751, which lays down implementing technical standards on uniform formats and templates for notification of determination of the impracticability of including contractual recognition of write-down and conversion powers.

    October 04, 2021 WebPage Regulatory News
    RESULTS 1 - 10 OF 7552