Executive summary
A U.S.–based underwriting services provider for Workers’ Compensation, engaged Bridgeport to address inefficiencies in loss run report handling.
Bridgeport implemented a Document Intelligence solution — powered by Bridgeport DocuRead capabilities — to automate extraction, normalization, and query-based retrieval of loss run data.
The solution enabled faster, more accurate underwriting decisions while significantly reducing manual effort and operational cost.
Client overview
The client is a U.S.–focused underwriting services provider specializing in Workers’ Compensation for the SMB segment. The company supports insurance carriers, brokerages, MGAs, PEOs and other intermediaries across the United States.
Business challenges
The client’s underwriting workflows were constrained by the manual nature and complexity of
loss run report analysis
No standard format across carriers — large variability in tables, terms, symbols, and structure High processing time and human dependency for reading, interpreting, and transcribing loss data Slow underwriting turnaround and delayed pricing decisions due to data unavailability
Inconsistent interpretation of key loss metrics across underwriters
High operational cost and compliance exposure from manual handling
Solutions
Bridgeport’s Document Intelligence Platform
Intelligent loss run data extraction
Auto-detects variations in layout and template
Extracts claims, dates, amounts, reserves, narrative text
Normalizes output into a structured repository
Generates Excel outputs and API-returned results
Question answering layer for underwriting
Accepts underwriting questions (e.g., Total incurred by year?”)
Returns precise structured answers in real time
Reduces dependency on manual reading and interpretation
Secure integration and deployment
API-based upload and query endpoints
Encryption, RBAC, audit logging and controls for compliance
Results and measured impact
Processing efficiency
Up to 70% faster loss run processing turnaround
50–60% reduction in manual effort and review cycles
30–40% drop in rework due to standardized outputs
Underwriting decision improvement
40–50% faster underwriting decision cycles
Higher pricing confidence via normalized, comparable loss data
Reduced subjective interpretation and analyst variance
Operational & compliance outcomes
Centralized, auditable loss run repository
Lower operational risk and compliance exposure
Scalable without linear staffing increase
Conclusion
By implementing Bridgeport’s Document Intelligence platform , the client was able to transform a highfriction bottleneck into a fast, accurate, and scalable workflow. The solution accelerated underwriting, enhanced pricing confidence, reduced cost of operations, and created a reusable intelligent data layer over unstructured loss runs — establishing a foundation for broader automation across the underwriting lifecycle.