UK Financial Institutions are Increasing Use of Machine Learning Posted by AVCU on 9:39 AM

Machine learning (ML) is being used with increasing frequency by financial institutions in the U.K., according to a joint report from the Bank of England (BoE) and Financial Conduct Authority (FCA).

The report summarizes the results of a survey conducted by the Bank of England and Financial Conduct Authority involving 106 respondents from a group of almost 300 banks, credit brokers, e-money institutions, financial market infrastructure firms, investment managers, insurers, non-bank lenders and principal trading firms. It reflects the BoE and FCA’s intention to better understand the interaction between an increasingly data-driven economy and dramatic changes to the structure and nature of the financial system supporting it.

In particular, the report emphasizes the need to strike a balance between supporting development of innovative and transformative technology while also addressing the risks posed by such developments to consumers and the U.K. financial system as a whole, according to Ropes & Gray.

Key findings of the report include:

• Firms in the financial services sector are using machine learning (ML) with increasing frequency. Two-thirds of respondents reported using ML in some form, with most firms expecting usage to increase significantly in the coming years. 
• The insurance and banking sectors use ML most extensively. Overall, ML is deployed most often in relation to anti-money laundering and fraud detection, as well as in customer-facing applications such as customer services and marketing, according to the report. 
• Firms consider improvements in AML, fraud detection and overall efficiency as the biggest benefits of using ML. They identified risks, including a lack of explainability, inadequate controls or governance, data quality issues and poor model performance. To mitigate those risks, firms implement alert systems and so-called “human-in-the-loop” mechanisms to flag when the ML model is not working as intended. 
• The report found firms do not consider regulation to be an unjustified barrier to ML deployment, but some believe there should be additional guidance to clarify existing regulations. Respondents noted that, because ML is a relatively new technology, it may not always be obvious how the existing regulatory framework applies to it. 
• Firms do not believe that ML necessarily creates new risks, but it could amplify existing ones. Respondents recognized that governance and controls processes will need to keep pace with technological development to appropriately manage those risks, the report states. 
• Although most firms reported using their existing risk management frameworks to address risks posed by ML, they noted that these frameworks might have to evolve as ML becomes increasingly mature and sophisticated.