Financial institutions have historically relied on historical data to assess risk. However, this approach often falls short in capturing the dynamic nature of the financial ecosystem. Rapid shifts and emerging trends can leave traditional risk models vulnerable. This paper explores a transformative solution: the integration of Artificial Intelligence (AI) and synthetic data in financial risk management.
By leveraging AI algorithms to generate synthetic data that mimics real-world scenarios, institutions can overcome data limitations and build more robust risk models. This empowers them to navigate the ever-changing regulatory landscape with greater agility. This paper delves into the specific ways AI and synthetic data are transforming financial risk management, exploring the benefits and potential challenges associated with this innovative approach.
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