Automated Claims Processing System Using Predictive Risk Scoring
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Solution Overview
Problem
The insurance industry faces inefficiencies and high costs due to the need for manual validation of claims, which burdens claimants and insurers alike, and often requires excessive documentary proof from all claimants regardless of fraud risk, leading to prolonged processing times and increased premiums.
Innovation Solution
A computer-based automated loss verification system that uses predictive modeling and third-party data sources to assess the risk of claims, reducing the need for extensive documentation from claimants by assigning a confidence level for validation, thereby streamlining the adjudication process.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If manual validation of claims is performed with extensive documentary proof requirements, then claim verification reliability is improved, but processing time and administrative costs increase
Solution Approach 1:
The system performs preliminary risk assessment and validates claims against third-party data sources before manual review is initiated. By pre-screening claims using automated validation against external databases (employment records, medical records, property records), the system identifies low-risk claims that can be approved automatically, reserving manual review only for high-risk cases. This preliminary action reduces overall processing time while maintaining verification reliability.
Solution Approach 2:
The system introduces third-party data sources as intermediaries to validate claim information. Instead of relying solely on claimant-provided documentation, the system automatically verifies claims against independent external databases (employer records for unemployment claims, medical providers for health claims, property assessors for property claims). These intermediaries provide objective verification that reduces processing time and administrative burden while maintaining or improving verification reliability.
2Object-affected harmful factors
If extensive documentary proof is required from all claimants, then fraud prevention is improved, but claimant burden and processing complexity increase
Solution Approach 1:
The system applies different validation requirements to different claims based on their risk profiles. Instead of uniformly requiring extensive documentation from all claimants, the system assesses each claim's fraud risk using predictive modeling and third-party data validation. Low-risk claims receive minimal validation requirements, while high-risk claims trigger more rigorous review processes. This localized quality approach reduces overall processing complexity and claimant burden while maintaining fraud prevention effectiveness.
Solution Approach 2:
The system enables self-validation of claims by automatically checking claimant-provided information against third-party databases. For example, the system can automatically verify employment status by querying employer records, confirm medical treatment by checking with providers, or validate property damage by accessing assessor databases. This self-service validation reduces the need for claimants to manually gather and submit extensive documentation, simplifying the process while maintaining fraud prevention capabilities.
3Productivity
If automated validation using third-party data is implemented, then processing speed is improved, but system complexity and data integration requirements increase
Solution Approach 1:
The system employs a universal validation framework that can query multiple different third-party data sources through standardized interfaces. The same validation engine and data integration architecture handles diverse claim types (unemployment, health, property, life insurance) by adapting query parameters and data source selections based on claim characteristics. This multi-functional design achieves high processing speed across varied claim types while managing system complexity through reuse of core validation components.
Solution Approach 2:
The system introduces intermediary data integration layers that standardize communication between the validation engine and diverse third-party databases. These intermediaries handle data formatting, authentication, and protocol conversion, allowing the core automated validation system to operate at high speed without being burdened by the complexity of direct integrations with numerous different data sources. The intermediaries absorb integration complexity while maintaining fast processing throughput.
Data Source
AI summary
A computer system-based automated loss verification system for evaluating the validity of claims filed under an insurance policy or debt protection contract is provided by this invention. Instead of requiring the claimant to contact the insurance company or lender to file the claim and provide exhaustive documentary proof of the validity of the claimed loss, the system pre-scores the relative risk of the claim using a risk assessment tool based upon predictive modeling and a number of potential risk factors. The associated automated loss verification tool uses this risk score and other information connected with the claim to assign a relative confidence level of proof of valid loss that must be satisfied before the claim can be approved through the adjudication process, and assigns a third-party supplied source or combination of sources of proof that can be automatically accessed by the system to validate the claim.