Machine learning forecasts for future claim trends, high-cost member identification, and intervention ROI modeling to proactively manage healthcare spend.
LSTM neural networks analyze 5+ years of claims history to predict future cost trajectories. Separate models for medical, pharmacy, dental, and vision trends with confidence intervals.
Identify members likely to exceed $100K in annual costs 6–12 months before it happens. Gradient boosting models analyze 200+ features including diagnosis codes, utilization patterns, and demographics.
Calculate expected savings from care management programs, specialty pharmacy switches, or high-performance network steering. Models account for member compliance rates and natural regression.
Retrain models weekly as new claims data arrives. Adaptive learning algorithms adjust predictions based on actual outcomes, continuously improving forecast accuracy.
Replace broker estimates with statistical forecasts. Board gets 95% confidence intervals for next year's costs, not single-point guesses from vendors with incentive to lowball.
Predict which members will breach specific deductible 6 months early. Proactive care management reduces laser placements that permanently increase premiums.
Acquiring company? Predict target's benefit costs under your plan design before deal closes. Model integration scenarios, identify hidden liabilities, validate seller's actuarial assumptions.
Comprehensive governance framework for board members and plan fiduciaries — defense-ready documentation and continuous oversight infrastructure.
Timestamped audit trail with complete chain of custody
EBITDA quantification and board-ready financial models
Cross-system verification and data integrity validation
Automated clause extraction and guarantee enforcement
Monte Carlo simulations and credibility-weighted forecasts
Transaction-level anomaly detection and forensic alerts
ERISA compliance monitoring and DOL audit readiness
AI-powered trend forecasting and intervention modeling