Author: Karim Derrick
Contact: Joe Cunningham

Part 3 of the Kennedys IQ SmartRisk Series

As AI continues to transform professional services, the challenge of ensuring accuracy, consistency, and explainability in automated decision-making remains a significant hurdle. In this third instalment of our Kennedys IQ SmartRisk Series, leading up to the March 19th launch, we explore how Evidential Reasoning and the Belief Rule Base (BRB) methodology provide the structured, logic-driven framework necessary for trustworthy AI-assisted professional judgment.

Why traditional AI models fall short in decision-making

While Large Language Models (LLMs) excel at text analysis and data extraction, they struggle with decision consistency and explainability.

Traditional AI systems encounter three major problems when applied to professional judgment:

1. Lack of structured logic – LLMs operate probabilistically, making them unsuitable for precise legal and insurance assessments.
2. Difficulty handling uncertainty – AI models cannot easily integrate incomplete or conflicting information, a frequent reality in professional decision-making.
3. Opaque reasoning – AI’s “black box” nature makes it difficult to justify decisions, a critical requirement in claims handling and underwriting.

The power of Evidential Reasoning and Belief Rule Base (BRB)

Kennedys IQ SmartRisk employs Evidential Reasoning and BRB to overcome these issues.

This hybrid approach combines expert knowledge and AI-driven learning, enabling:

• Structured, explainable decision-making
• Integration of qualitative and quantitative factors
• Handling of incomplete or evolving evidence

How it works

1. Evidential Reasoning:This approach refines probability-based decision-making by incorporating different categories of evidence, weighting them appropriately based on reliability and confidence.
2. Belief Rule Base (BRB):Unlike traditional rule-based systems, BRB can model uncertainty and evolving knowledge, ensuring that AI recommendations align with human expert judgment.

This combination enhances professional decision-making by providing clear, justifiable AI-driven insights that insurance professionals can trust.

The future of AI in professional judgment

By integrating Evidential Reasoning and BRB, SmartRisk offers an innovative way to augment—not replace—human expertise. The result? Improved accuracy, efficiency, and trust in AI-assisted claims handling and underwriting.

Looking ahead: tackling Algorithmic Aversion

In our next article, we’ll address Algorithmic Aversion—the reluctance of professionals to trust AI-driven decision-making. We’ll explore how SmartRisk builds confidence by ensuring AI is a transparent, explainable, and accountable tool rather than a “black box.”

Join us at the SmartRisk launch event

In March 19, SmartRisk will be unveiled—the world’s first hybrid AI system designed specifically for professional services. Join us to see how we are redefining risk assessment and claims decisioning.