The Challenge
Margin compression and rising claims complexity
Social inflation, climate volatility, and distribution costs are compressing margins across every line of business.
Underwriting Accuracy
Traditional actuarial models underprice tail risk in climate-exposed property and emerging liability lines. Alternative data integration is inconsistent across carriers, leaving systematic mispricing uncorrected.
Claims Leakage
The industry loses an estimated $30B annually to claims leakage, overpayments, duplicate claims, and coding errors that evade manual review at scale.
Fraud Networks
Organized fraud rings exploit siloed detection systems. First-party and third-party fraud is estimated at 10–15% of total claims volume, with sophisticated rings adapting faster than rules-based detection.
Customer Abandonment
72% of policyholders who experience a poor claims experience do not renew. Manual, slow claims processes are the #1 driver of NPS decline in personal and commercial lines.
Education AI Solutions
AI systems across underwriting, claims, and distribution
AI Underwriting Copilot
LLM-powered underwriting workbench that extracts risk factors from submissions, compares against portfolio experience, and recommends pricing, reducing underwriter review time by 60%.
Claims Triage & Routing
ML models that classify incoming claims by complexity, fraud risk, and required expertise, routing simple claims to straight-through processing and complex claims to senior adjusters.
Fraud Network Detection
Graph AI that maps relationships between claimants, providers, attorneys, and body shops, identifying fraud rings and organized schemes invisible to single-claim analysis.
Document Intelligence
AI extraction from police reports, medical records, repair estimates, and legal filings, eliminating manual data entry from claims workflows.
Loss Reserving AI
ML models that predict ultimate loss development more accurately than chain-ladder methods, improving reserve adequacy and reducing earnings volatility.
Distribution Analytics
Agent productivity AI, cross-sell propensity modeling, and retention risk scoring, helping carriers identify high-value relationships and reduce lapse rates.
End-to-End Implementation
End-to-end AI implementation for insurance
Solnix delivers the full lifecycle, from opportunity mapping through production deployment and continuous improvement. The same proven methodology powers every insurance engagement, tailored to your systems, data, and regulatory environment.
Discovery & AI Opportunity Mapping
We start by understanding your operations, data landscape, and goals, then map where AI delivers measurable value and where it does not. Every engagement begins with a prioritized opportunity backlog, not a technology pitch.
Data Foundation & Readiness
AI is only as good as the data behind it. We assess data quality, connect fragmented sources, and build the secure, governed pipelines that production AI depends on, with privacy and compliance designed in from the start.
Model & Agent Development
We build the models, retrieval systems, and AI agents tailored to your use cases, selecting the right approach (fine-tuning, RAG, multi-agent orchestration) for accuracy, cost, and latency, and validating against your real-world edge cases.
Integration & Workflow Embedding
AI only creates value when it lives inside the tools your teams already use. We embed models and agents into existing systems, surfaces, and workflows, so adoption is natural and human-in-the-loop controls stay in place.
Deployment, Security & Compliance
We deploy to production with the security, monitoring, and compliance controls enterprises require, including bias and fairness testing, audit logging, and the observability needed to operate AI responsibly at scale.
Optimization & Continuous Improvement
AI systems improve with use. We measure outcomes against the goals set in Phase 01, retrain and tune from live feedback, and expand to the next set of use cases, turning a single deployment into a compounding capability.
Methodology
How Solnix Builds for Insurance
01, Line of Business Assessment
01, Line of Business Assessment
We map your claims intake, underwriting, and fraud workflows, identifying the specific loss drivers and process bottlenecks with the highest ROI for AI intervention.
02, Data Architecture Review
02, Data Architecture Review
We assess your policy, claims, and third-party data, identifying quality issues, enrichment opportunities, and integration requirements for model development.
03, Core System Integration
03, Core System Integration
We integrate with Guidewire, Duck Creek, Majesco, and custom policy/claims administration systems. AI outputs surface within existing adjuster workbenches.
04, Regulatory Validation
04, Regulatory Validation
All AI models used in underwriting or claims decisions are documented with bias testing, adverse action explanation capability, and state-by-state regulatory review support.
05, Performance Monitoring
05, Performance Monitoring
We track model performance against combined ratio impact, fraud recovery rates, and adjuster adoption metrics. Quarterly model refresh cycles keep performance ahead of claim pattern drift.
FAQ
Questions from CUOs, claims VPs, and CDOs
Get Started
Better Underwriting. Faster Claims. Less Fraud.
Solnix builds the AI infrastructure that lets carriers compete on risk selection, operational efficiency, and customer experience, simultaneously.
Request an Insurance AI Assessment →