[Hong Kong, 2 November 2020] Commissioned by the Hong Kong Monetary Authority (HKMA), the Hong Kong Applied Science and Technology Research Institute (ASTRI) today publishes a white paper titled “Alternative Credit Scoring of Micro-, Small and Medium-sized Enterprises (MSMEs)”, which outlines how FinTech can be adopted to collect and utilise alternative data to evaluate borrowers’ creditworthiness and thus improve banks’ business scale of their existing MSMEs financing services and the access to finance for MSMEs.
MSMEs account for more than 98% of the business establishments in Hong Kong and employ about 46% of the workforce in the private sector. Yet many face significant challenges in securing a bank loan due to their lack of financial information and the significant burden faced by banks in conducting credit assessments and monitoring related processes. Mr Hugh Chow, CEO of ASTRI, said: “The traditional methods of measuring a company’s creditworthiness, calculating the probability of default, mean the odds are stacked against MSMEs who may rely on offline or cash transactions and who may not have the most orderly and neatest of accounting books. They may also need the funding urgently and the weeks it takes for an application to be processed could prove fatal if the difference between survival and bankruptcy is counted in days.
Eddie Yue, Chief Executive of HKMA, said that it is a global phenomenon that smaller businesses often find it challenging to access finance. “MSMEs play an important role in the economy. Fintech is believed to be an essential tool to help expand MSMEs’ access to credit by lowering costs and better managing the credit risks. Hong Kong is well positioned to drive fintech development given the support from the industry and society as a whole,” he noted. This white paper sets out how Hong Kong can take advantage of artificial intelligence and machine learning to explore a wide variety of data from many sources to assess the creditworthiness of MSMEs, including cash flow, point-of-sale transaction records, utility bill payments and even information from online accounting software programs. The paper lays out the technological components needed to handle and process the alternative data used in alternative credit scoring. Further, it proposes building an effective alternative credit scoring ecosystem for banks and providers of alternative data in Hong Kong that can handle data management, credit assessment automation, and monitoring. It also suggests steps that need to be taken by the players in the ecosystem to support this proposal. The white paper offers a roadmap for the adoption of alternative credit scoring in Hong Kong and suggests three areas for future development. Firstly, continuous support by the government and infrastructure facilitation for data sharing are critical to maintain the availability of alternative data. Secondly, the continuous development of innovative machine learning models is required to enhance the handling of model validation, performance, data privacy, fairness, and interpretability. Finally, a centralised data-sharing platform could facilitate an ecosystem that will expedite the adoption of alternative credit scoring by banks in Hong Kong. “The release of this white paper aims to promote the adoption of alternative credit scoring by banks in Hong Kong with a view to improving access to finance for MSMEs and helping banks to improve the business scale of their existing MSME financing services. It can be used as a basic blueprint for banks looking to kickstart the adoption process,” added Mr Chow.
Please click here for the full white paper.