Featured Product

    HKMA Publishes Second Issue of Regtech Watch Newsletter

    March 16, 2020

    HKMA published the second issue of the Regtech Watch newsletter. This issue focuses on applications of technology in credit risk management. It highlights the key challenges in credit underwriting and risk management processes and shares use cases of banks that apply machine learning models and other technologies to overcome these challenges. Three use cases are summarized covering the use of data-driven income estimation to approve personal loans, machine learning-based methods to streamline corporate loan underwriting, and linguistic and sentiment analysis to identify adverse news about the borrower.

    In the course of understanding and examining credit underwriting and risk management processes of banks, HKMA has observed that some banks have adopted new technologies to overcome certain longstanding challenges. The application of technology in credit risk management is gaining popularity across banks in Hong Kong. The newsletter showcase the following use cases:

    • Data-driven income estimation to approve personal loans. To enable banks to offer a smoother customer experience, HKMA introduced new guidelines in May 2018 to allow banks to adopt innovative technology to manage credit risks related to personal lending business. Several banks have since adopted data-driven income estimation models to inform credit underwriting and lending decisions. By applying these models to readily available information, banks can take income input into account in their credit underwriting decisions very quickly, resulting in a significantly faster application process. Banks using these models are cognizant of the need to re-train and re-validate the models routinely to ensure their continued robustness.
    • Machine learning-based methods to streamline corporate loan underwriting. To improve efficiency of corporate lending decisions, some banks are exploring the use of artificial intelligence and machine learning in credit assessment. One bank in Hong Kong recently launched a pilot roll-out of artificial intelligence engines for financial spreading, including the use of Optical Character Recognition to digitize physical copies of financial statements. Another Hong Kong lender supplemented traditional financial ratios with analyses of more advanced indicators about corporate borrowers, for example, by examining the transaction and cash-flow patterns reflected in bank statements. The indicators will then be used to estimate the probability of default, which ultimately informs loan decisions.
    • Linguistic and sentiment analysis to identify adverse news about the borrower. To identify adverse news to ensure that any major adverse developments related to corporate borrowers are identified in a timely manner, banks need to review a large volume of news from different sources on an ongoing basis. To this end, some banks have started to use tools such as Natural Language Processing (NLP) and supervised machine learning to automate news screening. This involves the use of linguistic analysis tools to extract relevant information from the news sources, classify the information into different subjects, and digitize it in a machine-readable format. The technology helps banks achieve more timely and accurate identification of adverse news on borrowers, which in turn improves their ongoing assessment of the borrowers’ creditworthiness.

    These use cases also demonstrate the potential limitations of new technology. In machine learning credit models, the probability-of-default predictions obtained via different approaches may vary significantly and are not easy to interpret. In addition, the models currently in use were developed only in recent years, so their performance across a complete credit cycle is yet to be seen. Additionally, banks often depend on third-party developers for expertise in designing and developing technology applications, giving rise to potential risks in governance and accountability. To overcome these limitations, HKMA expects banks to implement programs to recruit, train, and retain employees with suitable skill sets and establish effective mechanisms to supervise the relevant staff members. 

    Apart from these use cases, HKMA noticed that banks overseas are now applying emerging technology solutions to credit risk management, particularly with regard to small-business loans. Given the limited credit history of small businesses, the industry has developed credit-scoring models based on alternative data—"firmographic information" such as borrowers’ firm size and location and social media presence—to facilitate loan approval. Such alternative data have helped banks to arrive at more accurate assessments of the creditworthiness of small businesses,which might otherwise be opaque. The benefits of credit scoring with alternative data are being increasingly acknowledged internationally, for example, by BIS and FSB.

    Keywords: Asia Pacific, Hong Kong, Banking, Regtech, Newsletter, Machine Learning, Credit Risk, Artificial Intelligence, Regtech Watch, Natural Language Processing, Fintech, HKMA

    Related Articles
    News

    EC Consults on PSD2 and Open Finance; EU Reaches Agreement on DORA

    The European Commission (EC) published a public consultation on the review of revised payment services directive (PSD2) and open finance.

    May 11, 2022 WebPage Regulatory News
    News

    EC Mandates ESAs to Propose Amendments to SFDR Technical Standards

    The European Commission (EC) has issued two letters mandating the European Supervisory Authorities (ESAs) to jointly propose amendments to the regulatory technical standards under Sustainable Finance Disclosure Regulation or SFDR.

    May 11, 2022 WebPage Regulatory News
    News

    EBA Examines Supervisory Practices, Issues Deposits Reporting Template

    The European Banking Authority (EBA) published its annual report on convergence of supervisory practices for 2021. Additionally, following a request from the European Commission (EC),

    May 11, 2022 WebPage Regulatory News
    News

    US Agency Publications Address Basel, Reporting, and CECL Developments

    The Farm Credit Administration published, in the Federal Register, the final rule on implementation of the Current Expected Credit Losses (CECL) methodology for allowances

    May 09, 2022 WebPage Regulatory News
    News

    SEC Extends Comment Period on Climate Risk Disclosures

    The U.S. Securities and Exchange Commission (SEC) looks set to intensify focus on crypto-assets and cyber risk and extended the comment period on the proposed rules to enhance and standardize climate-related disclosures for investors.

    May 09, 2022 WebPage Regulatory News
    News

    APRA Reduces Committed Liquidity Facility, Issues Other Updates

    The Australian Prudential Regulation Authority (APRA) announced reduction in the aggregate Committed Liquidity Facility and issued an update on the operational preparedness for zero and negative market interest rates.

    May 09, 2022 WebPage Regulatory News
    News

    CMF Consults on Basel Rules, Presents Roadmap to Address Climate Risks

    The Commission for the Financial Market (CMF) in Chile published capital adequacy ratios (as of February 2022, January 2022, and December 2021) for 17 banks and for the banking system.

    May 06, 2022 WebPage Regulatory News
    News

    PRA Issues Statement on NPEs and Policy on Trading Activity Wind-Down

    The Prudential Regulation Authority (PRA) issued a statement on the European Banking Authority (EBA) guidelines on management of non-performing exposures (NPEs) and forborne exposures.

    May 06, 2022 WebPage Regulatory News
    News

    EBA Updates Standards for 2023 Benchmarking of Internal Approaches

    The European Banking Authority (EBA) updated the implementing technical standards that specify the data collection for the 2023 supervisory benchmarking exercise in relation to the internal approaches used in market risk, credit risk, and IFRS 9 accounting.

    May 06, 2022 WebPage Regulatory News
    News

    EIOPA Responds to Stakeholder Views on Blockchain in Insurance

    The European Insurance and Occupational Pensions Authority (EIOPA) published a feedback statement on the responses received to the consultation on blockchain and smart contracts in insurance.

    May 06, 2022 WebPage Regulatory News
    RESULTS 1 - 10 OF 8179