As financial institutions accelerate their use of artificial intelligence to combat financial crime, explainability has moved from a technical consideration to a strategic priority.
The new ‘Guide to Explainable AI in Financial Services‘ by SymphonyAI sets out why transparency, accountability, and defensible decision-making are now essential for firms deploying AI across AML and sanctions screening.
The report explores how explainable AI supports confidence across key stakeholders. For instance, providing regulators with clearer accountability and defensible decisioning, improves the reassurance customers have in decisions and the confidence investigations teams have to act faster and with clear reasoning.
It also explores why explainability is becoming a requirement, including the need for meaningful explanations in automated decisioning and how AI-specific regulation is rapidly growing.
On top of this, the report covers how explainability works in AML and sanctions screening. In relation to AML, AI tools combined with human-readable, natural-language explanations allow investigators to understand why alerts are true or false positive. While for sanctions screening, generative AI extracts context from unstructured text, predictive AI evaluates match likelihood and provides explanations and probability to lower false positive rates.
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