Explainable AI in Production: A Neuro-Symbolic Model for Real-Time Fraud Detection

This article presents a neuro-symbolic model for real-time fraud detection that provides deterministic and human-readable explanations in 0.9 ms, outperforming traditional explainable AI methods like SHAP, which requires 30 ms and stochastic explanations. The significance of this model lies in its ability to provide fast and reliable explanations, making it suitable for production environments where real-time decision-making is critical.

⚡ Key Takeaways

• The neuro-symbolic model produces explanations 33 times faster than SHAP, with a response time of 0.9 ms.
• The model provides deterministic explanations, unlike SHAP's stochastic approach, which enhances reliability and trust in the decision-making process.
• The neuro-symbolic model eliminates the need for a background dataset at inference time, simplifying maintenance and deployment.

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