Hong Kong SAR - Latest HKMA Regtech Watch focuses on credit management

The use of technological solutions deployed in the area of credit management is the focus of the HKMA’s second edition of Regtech Watch. Regtech Watch was launched by the HKMA at the end of 2019 as a way to promote the adoption of regulatory technology (Regtech) by the banking industry in Hong Kong SAR. The aim is to provide information on actual or potential Regtech use cases rolled out or being explored in Hong Kong or elsewhere, but the inclusion of the different case studies and models in an issue of Regtech Watch does not mean that the HKMA supports or endorses them.

In this March 2020 edition, the HKMA looks at three different uses of technology in credit management:

  • One model looks at using income estimates through data analytics in order to assess the debt servicing ability of applicants. The HKMA does note that credit decisions made with a heavy reliance on models are vulnerable to changes in customer behaviour and market conditions. Banks using these models must retrain and revalidate the models routinely to ensure their continued robustness.
  • Another model looks at the methods such as artificial intelligence and machine learning used in the credit assessments for corporate lending. The HKMA cautions that firms should be aware of the potential issues with machine learning credit models, for example 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 have been developed only in recent years, so their performance across a complete credit cycle is yet to be seen.
  • The third model looks at the identification of adverse news relating to corporate borrowers.

As with the implementation of any technologies, the HKMA expects banks to implement programmes to recruit, train and retain employees with suitable skill sets and establish effective mechanisms to supervise the relevant staff members. Firms should have adequate in-house skills to train and test Regtech models properly and to provide adequate support for smooth operations.