A recent report by the Financial Stability Board (FSB), an international organization made up of national and regional banking supervisors, sets forth the need for financial stability regulations to expand their scope of action into areas such as Artificial Intelligence and machine learning.
Like any other new technology, Artificial Intelligence (AI) presents an opportunity, but also poses new risks. AI can help the financial sector to cut costs, improve profitability and expand the range of customer options.
However, the report warns that widespread use of these technologies in sectors such as banking and insurance could also compromise financial stability due to the increased interconnectedness of companies using this technology and the industry’s dependence on technology companies that are not subject to regulatory oversight.
The FSB’s analysis reveals a series 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.” These are the FSB’s conclusions:
- The more efficient processing of information may contribute to a more efficient financial system. The Regtech and SupTech applications of AI and machine learning can help improve regulatory compliance and increase supervisory effectiveness.
- Applications of AI and machine learning could result in new and unexpected forms of interconnectedness between financial markets and institutions; for instance, ones 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.
- It will be important to assess the implementation of relevant data privacy, conduct risk and cybersecurity protocols.
AI, a challenge and an ally for regulators
In fact, as Reuters reports, the FSB warns that the expected rapid growth in AI also raises the prospect of outside technology players expanding their influence over the finance sector. Also, the pace of technological progress adds an additional level of complexity when defining a long-lasting set of rules to regulate AI activity, which is expected to revolutionize the financial sector, according to some academics.
On the other hand, Artificial Intelligence presents great opportunities in the field of regtech, i.e. the use of technology to facilitate regulatory compliance, or the detection of fraud and money laundering. But it is not limited to banks and insurance companies. Regulatory bodies are also resorting to AI systems to improve financial supervision. Also, central banks trust that AI will help them elaborate real-time predictions, using ‘big data’ technologies to define their monetary policies.
What is AI used for in banking?
The financial industry expects AI to help with everything, from the definition of products and customer segmentation, to risk management and fraud detection, allowing institutions to capitalize on ‘big data,’ better anticipate change, and evolve when needed.
Machine learning – automated learning – allows machines to learn without being expressly programmed. This learning ability allows them to identify otherwise undetectable patterns and to make data-based predictions.