Claims Management

Augment claims handling and processing with a better understanding of your claims life cycle.

Our Claims Management analytics services help insurers optimize their claims workflows, assess claims severity and litigation propensity, and estimate losses by identifying trends and uncovering hidden insights in historical data.

How we help

Claims Injury and Damage Severity

Better understand how severe claims might be and what the associated losses will total to more accurately price policies and forecast potential losses.

FNOL Outlier Detection

Identify anomalies in FNOL submission by comparing cases with historical claims data and routing them for investigation.

Fraud Detection

Leverage analytics to identify anomalies that could indicate fraudulent claims.

Claims Segmentation and Assignment

Analyze FNOL information for severity of claims, claims type, loss cause, and more to segment claims for straight-through processing or assign them to the right adjuster.

Report Summary

Shorten lead times through process automation for reports involved in the claims life cycle, from police reports to medical records to more.

Subrogation Opportunity

Reduce losses by detecting subrogation opportunities at time of FNOL.

Litigation Propensity

Reduce expenses and cut down on losses by proactively assessing a policy’s propensity for litigation.

Loss Estimation

Estimate loss amounts based on FNOL submission information and historical claims to manage loss reserves.

Together with our platform partners

TESTIMONIALS

Customer Communications
Insurance core systems|webinar speakers|Webinar Clip Deborah Zawisza Onboarding Clip|Tim Hays Webinar clip making the company grow|
AI Automation||AI model based on NLP predicts unique test cases vs duplicates|AI model uses data to learn and predict root cause of new defects|AI uses historical information to identify patterns and recommend sets of test cases|AI model uses data to learn and predict root cause of new defects|AI uses historical information to identify patterns and recommend sets of test cases|AI model uses data to learn and predict root cause of new defects|AI uses historical information to identify patterns and recommend sets of test cases|AI in Software Testing|Identifying Defect Root Cause|Identifying Duplicate Test Cases|Predicting Test Cases That Will Find A Bug

Insights to improve your UW process

Our solutions help clients create seamless customer experiences, leading to better CX

Accelerating product design

Our expert insurance technology teams have the expertise to implement the right migration process

Multi-state product expansion

React faster to customer requirements, and regulatory changes
INSIGHTS

Stay ahead with P&C-focused thought leadership