Mike Foster, President and CEO, SymphonyAI/Sensa-NetRevea

MF: Predictive and GenAI combined can create powerful tools. For criminals, it has opened opportunities for AI-powered money laundering where they create algorithms to detect and exploit vulnerabilities in transaction monitoring systems, making illicit financial activities harder to trace. They also use machine learning to mimic legitimate transaction patterns, making it more difficult for anomaly detection systems to identify fraudulent activities. 

    • The selection of datasets for the training and development of models is key, as it influences reliability, accuracy, and susceptibility to bias.
    • Intensive testing for bias and hallucinations is another key component of the development process before a GenAI solution is deployed. Developers mitigate these risks with appropriate reinforced machine learning and embeddings.
    • Human verification is also required in the testing and validation procedures, so no surprise results or human oversight eventuate. Relevant explainability tools or models should be built into solutions to deliver insights into decision trees or feature importance in relation to a model’s output.