Unlock deep learning to power precision pricing, smarter underwriting, and proactive claims analytics
Benefits for pricing accuracy and actuarial strategy.
Enhancing underwriting and risk selection.
Preemptive risk management and loss prevention.
Importance of cause code analysis
- Explains cause codes as standardised loss classifications (e.g., fire, flood, cyber breach).
- Highlights current market limitations in capturing detailed cause codes.
- Demonstrates how granular cause analysis improves underwriting precision, risk selection, and profitability.
Actuarial & pricing benefits
- Improved actuarial accuracy with enhanced risk segmentation by loss cause frequency and severity.
- Demonstrated loss ratio improvements.
- Advanced cognitive analytics predicting complex claims scenarios.
Underwriting & risk selection advantages
- More precise risk profiling, identifying high-risk attributes associated with certain loss causes.
- Data-driven underwriting guidelines adapting dynamically based on predictive insights.
Proactive loss prevention
- Identifies recurring loss causes (e.g., frequent fire incidents or equipment breakdowns).
- Enables proactive client engagement to mitigate identified risks, reducing future claims.
Cause code insights
Turning claims history into competitive advantage
Speciality line analytics
Detailed insights by line (Marine, Property, Energy, Construction, Aviation, Cyber, etc.), identifying leading causes of loss.
Actionable data enabling tailored underwriting and risk management decisions.
Real-life success stories
Leading Lloyd’s MGA demonstrates how detailed cause-of-loss analytics enabled them to proactively manage client risks and mitigate underwriting losses.
Quantifiable performance gains (loss ratio improvement, claims savings).
Strategic benefits
Enhanced regulatory compliance through transparent, data-driven reporting.
Improved reserving accuracy and capital planning.
Better management of emerging risks and systemic exposures.