Ahead of Alfi’s annual Private Markets Conference getting underway in Luxembourg next week, Thomas Chevalier, executive director of Temenos Multifonds, sets out how the reluctance of private markets to embrace AI finally appears to be dissipating.
We certainly see more asset managers and fund administrators in private markets being more open to AI tools for their core business (ie. decision-making and investment operations) when first adoption was more around less business critical functions (such as marketing and communication).
AI now helps firms to work smarter, stay competitive, and minimize risks incurred by human errors. However, there are challenges that need to be addressed before AI can be widely adopted across the industry.
First is the concern of data privacy and security risks. Regulators are still assessing their approaches to compliance requirements. Firms using AI need to ensure they have full explainability and an audit trail for both the data inputs and the models. The second is the availability of data.
It’s difficult to feed client information into AI models due to the various restrictions around data protection in the financial space.
It’s important for firms to communicate clearly with clients about how their data is being used. Proper governance and control mechanisms have to be implemented regarding how AI handles those data securely.
At Temenos Multifonds, we are using Explainable AI(XAI) on top of an exception-driven process that can help fund administrators easily identify false positives and provide transparent, human explanations about exception decisions.
