Financial Technology, Stability, and Inclusion

FinTech has witnessed a spectacular growth in the aftermath of the 2008 financial crisis. While the industry has taken innovative approaches to promote financial inclusion by serving traditionally under-banked businesses and people, it is also exposed to nonnegligible risk that can threaten the stability of financial market. Hence, a key challenge facing the industry is to assess and manage financial risks properly while extending financial services to a wider spectrum of firms (especially small and medium enterprises SMEs) and consumers. Since SMEs and consumers possess little "hard information" (e.g., financial statements, collaterals, credit history), it makes it a grand challenge – how to evaluate and finance them adequately. This is particularly the case as SMEs and consumers play a crucial role in economic development. According to the State Council of China and HKTID, SMEs contribute to more than 80% (46%) of employment and 90% (98%) of business units in mainland China (Hong Kong). Household consumption is also a key driver of economic growth, accounting for 60% of GDP (World Bank, 2018). Therefore, it is imperative to search for the solutions.

The project aims to develop a scientific framework on credit risk assessment and management for small businesses and consumers, lay out a formal foundation for smart contract / mechanism design, provide a platform for conducting program evaluation on the real economic and social impact of FinTech, form and test macro theories/models of financial risk featured with FinTech development, and provide policy recommendations for financial stability and inclusion. The framework is featured with a comprehensive guidance on

a) "high-frequency, high-dimensions, high-coverage" data collection, such as capturing granular digital footprints and networks of firms and consumers,

b) feature extraction based on behavioral consistency theories (Cronqvist et al., 2012), such as extracting behavioral traits (e.g., risk attitude, self-efficacy) of small business owners and consumers from investment, consumption and their behaviors through social networks and ownership chains, 

c) transformation of such "soft information" into "hard information", 

d) design, selection and training of credit models that (i) exploit the predictive power of digital footprints, networks and behavioral traits versus traditional financial metrics, and (ii) dynamically adapt to business cycles, and 

e) interpretation and application of model outcomes for financial institutions and policy makers.

The project will convene a team of experts in finance, economics, law, data science and engineering, collaborate with top financial institutions (e.g., the largest FinTech company), and form an advisory board of world leading economists (e.g., Nobel Laureates) and important policy makers (e.g., IMF Deputy MD overseeing FinTech). The extensive network of the team with global and regional institutions (e.g., IMF, World Bank, BIS, ECB, FSB, Fed, PBC, HKMA, HKFSDC, HK Competition Commission, etc.) will help disseminate the research outputs. The deliverables will help Hong Kong transit from a traditional International Financial Centre to a FinTech hub.