Solution
Analytics & Data Platforms for Insurance
Transform actuarial, claims, and distribution data into competitive advantages that improve profitability across your book of business.
Insurance companies generate enormous volumes of data across underwriting, claims, billing, and distribution channels. Adapter builds analytics platforms that turn this data into actionable intelligence for actuaries, underwriters, claims teams, and executive leadership.
Key Challenges
- Fragmented Data Across Core Systems
- Actuarial Modeling Data Gaps
- Statutory and Regulatory Reporting
Overview
Analytics & Data Platforms for Insurance
Insurance is fundamentally a data business, yet many carriers still struggle to get a unified view of their own operations. Actuarial data lives in specialized modeling tools. Claims data sits in core platforms. Distribution data is scattered across agency management systems, broker portals, and CRM tools. Financial data flows through separate accounting systems. Without connecting these silos, leadership cannot answer basic questions about profitability by line of business, distribution channel performance, or emerging loss trends until months after the fact.
Adapter builds insurance analytics platforms that bring all of these data sources together in near real time. We design data architectures purpose-built for insurance workloads, including loss triangle computation, exposure tracking, rate adequacy analysis, and IBNR reserving support. Our platforms serve multiple user personas: actuaries who need granular policy and claims data for modeling, underwriters who need portfolio risk snapshots during the quoting process, claims managers who need severity and litigation trend visibility, and executives who need P&L views by segment.
We also build predictive analytics capabilities on top of these platforms. This includes loss propensity models that inform underwriting appetite, claims severity predictors that support reserve setting, fraud scoring models that flag suspicious claims in real time, and distribution analytics that identify the most profitable agency relationships. All of our analytics solutions include proper governance for insurance-specific requirements, including statutory reporting support, state regulatory filing data, and audit-ready data lineage documentation.
What we deliver
Solutions
- 01
Unified Insurance Data Warehouse
- 02
Actuarial-Ready Data Pipelines
- 03
Automated Regulatory Reporting
- 04
Streaming Fraud Analytics
Industry Challenges
Problems we solve
Fragmented Data Across Core Systems
Policy, claims, billing, and reinsurance data often resides in separate systems with different schemas, making cross-functional analysis extremely difficult.
Actuarial Modeling Data Gaps
Actuaries frequently spend more time preparing data than analyzing it, because the data they need is not available in a clean, consistent, and timely format.
Statutory and Regulatory Reporting
Insurance companies must produce state-level statutory filings, NAIC annual statements, and other regulatory reports that require precise data extraction and transformation.
Real-Time Fraud Detection Requirements
Batch-based analytics are too slow to catch fraud at the point of claims intake, where early detection has the highest financial impact.
What We Build
Our approach
Unified Insurance Data Warehouse
We build data platforms that consolidate policy, claims, billing, reinsurance, and distribution data into a single, governed source of truth using insurance-specific data models.
Actuarial-Ready Data Pipelines
Our pipelines deliver clean, consistent data in formats optimized for loss triangles, exposure summaries, and experience studies, saving actuaries weeks of data preparation time.
Automated Regulatory Reporting
We build automated data extraction and transformation workflows for statutory filings, annual statements, and state-level regulatory submissions.
Streaming Fraud Analytics
Real-time data pipelines and scoring models flag suspicious claims at first notice of loss, enabling SIU teams to investigate early when intervention has the greatest impact.
Results
What you can expect
3-point loss ratio improvement
Granular analytics on loss drivers, pricing adequacy, and portfolio mix enable actuarial and underwriting teams to make better risk selection and pricing decisions.
75% reduction in actuarial data preparation time
Automated pipelines that deliver clean, analysis-ready data give actuaries more time for modeling and less time wrestling with spreadsheets.
20% increase in fraud referral accuracy
Real-time scoring models and network analytics reduce false positives while catching sophisticated fraud patterns that rules-based systems miss.
FAQ
Common questions
Things clients typically ask about analytics in insurance.
Ready to get started?
Tell us about your project and we will scope an engagement that fits.