The use of AI and ML in finance is revolutionizing the industry, but there are potential risks associated with the deployment of AI-driven techniques. To ensure that these vulnerabilities and risks are minimized, some level of human supervision of AI-techniques is still necessary. Firms need to invest in developing human capital with the necessary skills to exploit the value of AI and ML technologies, while regulatory and supervisory authorities need to be technically capable of operating, inspecting and intervening in the AI-based systems.
The use of artificial intelligence (AI), machine learning (ML) and big data in finance is revolutionizing the industry. As with any innovation, there are potential risks associated with the adoption of AI and ML technologies in finance, including employment risks and the need for skilled professionals. In this article, we will discuss the risks of employment and the need for specialized skills in the financial sector as AI and ML become more prominent.
AI and ML in Financial Services:
AI and ML have the potential to bring about major changes in the financial services sector, including improved customer service, increased efficiency, and better decision-making. AI and ML can also be used to uncover new opportunities, such as detecting fraud or identifying new sources of revenue.
However, the use of AI and ML requires different skillsets than those traditionally held by financial practitioners. To make the most of AI and ML, financial services providers need to be technically capable of operating, inspecting and intervening in the AI-based systems. This means that professionals who combine scientific expertise in the area of AI, computer science, and financial sector expertise need to be employed.
Employment Risks:
The widespread adoption of AI and ML in finance may give rise to some employment risks. As AI and ML become more mainstream, financial firms will need to invest in developing human capital with the necessary skills to exploit the value of these technologies and vast amounts of unstructured data.
At the same time, executives of financial services firms expect that the application of such technologies may result in potentially significant job losses across the industry. Therefore, it is important for firms to ensure that they have the appropriate understanding of the workings of the AI techniques and models and are capable of substituting the automated AI systems with well-trained humans when necessary.
Skills Requirements:
The widespread use of AI and ML by the financial industry will increasingly rely on and drive the demand for experts who successfully combine finance knowledge with expertise in computer science. Compliance professionals and risk managers need to have an appropriate understanding of the workings of the AI techniques and models in order to audit, oversee, challenge and approve their use.
Additionally, senior managers need to have the ability to understand and follow the development and implementation of AI and ML technologies. Regulatory and supervisory authorities need to have the technical capabilities to inspect AI-based systems and intervene when needed.