These jobs account for a good part of the 22,000 net jobs the financial sector has created during 2016–2019. Our FinTech start-up community has grown exponentially – Five years ago, we had about 50 FinTech firms; we now have more than 1,000. Last year, FinTech firms attracted a record $ billion of investment. For the first half of this year, despite COVID-19, the FinTech sector continued to attract equity funding and M&A amounting to $ million. The FinTech sector has been a powerful creator of jobs. We estimate there are nearly 10,000 people employed by FinTech firms, many of which are also classified as part of the financial services sector. We have seen many examples of innovative solutions that use technology to meet the daily needs of consumers of financial services. The Proof of Concept (or POC) Grant, under FSTI, provided funding support for experimentation, development, and dissemination of such solutions. One example of successful commercialisation is SoCash, who partnered with Standard Chartered Bank to pioneer micro cash distribution in Singapore, by turning any retail shop into an ATM alternative and allowing users to withdraw cash at the checkout. SoCash subsequently raised $ in Series B funding to expand its distribution network into overseas markets such as Indonesia, Malaysia and Hong Kong. The financial industry has begun to make progress in frontier technologies like AI. The AI and Data Analytics (or AIDA) Grant, under FSTI, has helped to promote the adoption and integration of AI and data analytics in financial institutions.
They review such issues as whether the model is based on reasonable assumptions, whether the firm is making appropriate use of backtesting, and how the model performs under normal and stressed market conditions. In addition, they are spending significant time on key controls related to the overall use of models, including the model validation process and the new product approval process. Likewise, as banks rely increasingly on their own assessments of credit and operational risk when determining their capital needs, our examiners will have to become well-versed in the changing technical aspects of those models. Some of the conventional, static metrics that we now use - for example, on the credit risk side, those to judge asset quality and to assess the adequacy of credit loss reserves - are likely to be supplanted by more sophisticated quantitative measures. As is the case with credit risk, we are in the process of developing a more integrated framework for assessing the adequacy of banks’ operational risk management and measurement approaches. We are focusing heavily on how banks are managing operational risk from a corporate-wide perspective. We begin by developing a feeling for the "tone at the top" - that is, the board of directors’ and senior management’s commitment to effectively manage its operational risk. Then we assess whether that commitment translates into an effective operational risk management and control structure - including the quality of management reporting, and the degree of integration of operational risk into a bank’s overall risk management approach.