AI and machine learning bring benefits to financial services, but also risks
Source: Asia Insurance Review | Dec 2017
Financial institutions are increasingly using AI and machine learning in a range of applications across the financial system and while this brings benefits, there are also risks, said a report published by the Financial Stability Board (FSB).
Specifically for insurance, the report noted that the industry is using machine learning to analyse complex data to lower costs and improve profitability. Adoption of AI and machine learning applications in InsurTech is particularly high in the United States, UK, Germany and China.
The FSB’s analysis reveals a number of potential benefits and risks for financial stability that should be monitored as the technology is adopted in the coming years and as more data becomes available, such as:
- Applications of AI and machine learning could result in new and unexpected forms of interconnectedness between financial markets and institutions, for instance based on the use by various institutions of previously unrelated data sources.
- Network effects and scalability of new technologies may, in the future, give rise to third-party dependencies. This could in turn lead to the emergence of new systemically important players that could fall outside the regulatory perimeter.
- The lack of interpretability or auditability of AI and machine learning methods could become a macro-level risk. Similarly, a widespread use of opaque models may result in unintended consequences.
- As with any new product or service, it will be important to assess uses of AI and machine learning in view of their risks, including adherence to relevant protocols on data privacy, conduct risks, and cybersecurity. Adequate testing and ‘training’ of tools with unbiased data and feedback mechanisms is important to ensure applications do what they are intended to do. A