Signals-Based Data Syndication for Secure Multi-Carrier Fraud Detection

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Solution Overview

Problem

Insurance carriers face challenges in data sharing due to security concerns, resource intensity, and the inefficiency of adapting analytics across non-standardized data sets, which can lead to anti-competitive collusion.

Innovation Solution

A system for signals-based data syndication and collaboration that aggregates data from multiple carriers into a unified operational data store, performs analytics across the multi-carrier data set, and facilitates controlled data sharing and collaboration among carriers to identify patterns indicative of activities like fraud, while protecting proprietary information.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Reliability

If data is shared between insurance carriers, then fraud detection capabilities are improved, but security concerns and proprietary information protection are worsened

Engineering Contradiction:

Improvefraud detection capabilitiesVSAvoidsecurity concerns and proprietary information exposure

Core Design Contradiction:

ReliabilityVSObject-affected harmful factors

Solution Approach 1:

A centralized analytics platform serves as an intermediary that receives data from multiple carriers, performs unified analytics, and returns results without exposing individual carrier data structures. This mediator enables fraud detection across carriers while protecting each carrier's proprietary information format and data architecture.

Inventive Principle:

Principle #24Intermediary (Mediator)

Solution Approach 2:

The system segments data sharing by allowing carriers to contribute only the necessary data elements for fraud detection while retaining control over their full data structures. The platform processes segmented data portions and returns only relevant findings, preventing complete data exposure and maintaining security boundaries.

Inventive Principle:

Principle #1Segmentation

2Adaptability or versatility

If carriers perform analytics on their own non-standardized data, then analytics customization is improved, but resource efficiency and collaboration consistency are worsened

Engineering Contradiction:

Improveanalytics customization per carrierVSAvoidresource efficiency and collaboration effectiveness

Core Design Contradiction:

Adaptability or versatilityVSProductivity

Solution Approach 1:

The system establishes a universal data standard and unified analytics platform that can process data from multiple carriers with different original formats. The platform transforms each carrier's non-standardized data into a common format for consistent analysis, enabling resource sharing and collaborative fraud detection across the entire industry.

Inventive Principle:

Principle #6Universality (Multi-functionality)

Solution Approach 2:

The system changes the data representation parameters by transforming each carrier's proprietary data formats into a standardized unified format. This parameter transformation allows the same analytics to be applied consistently across all carriers while preserving the ability to handle different data types and structures through the standardization layer.

Inventive Principle:

Principle #35Parameter changes

3Reliability

If data sharing is tightly controlled to avoid anti-competitive collusion, then competition fairness is improved, but data sharing effectiveness and collaboration depth are worsened

Engineering Contradiction:

Improveanti-competitive complianceVSAvoiddata sharing effectiveness

Core Design Contradiction:

ReliabilityVSProductivity

Solution Approach 1:

The system extracts only the specific data elements and analytics results necessary for fraud detection from the full carrier datasets. By taking out only the minimal required information for collaborative fraud analysis, the system enables effective collaboration while avoiding the disclosure of broader proprietary information that could raise anti-competitive concerns.

Inventive Principle:

Principle #2Taking out (Extraction)

Solution Approach 2:

The platform creates a controlled copy of data for analysis purposes, where data is replicated in a standardized format for collaborative analytics but the original proprietary data structures and full datasets remain isolated with each carrier. This copying enables collaboration while maintaining clear separation and control over proprietary information.

Inventive Principle:

Principle #26Copying

Data Source

PatentUS20260004362A1Signals-based data syndication and collaboration

Publication Date: 2026.01.01 GUIDEWIRE SOFTWARE INC

AI summary

Signals-based data syndication and collaboration is disclosed. A data store of insurance related data collected from a plurality of carriers is accessed. A pattern is identified based at least in part on data stored in the data store. The pattern is associated with a first set of insurance related data belonging to a first carrier and with a second set of insurance related data belonging to a second carrier. First and second users associated with the first and second carriers are notified, respectively, of the identified pattern. Consent from the first user to share at least a portion of the first set of insurance related data and consent from the second user to share at least a portion of the second set of insurance related data are obtained. At least a portion of the second set of insurance related data that the second user has consented to share is caused to be presented to the first user. At least a portion of the first set of insurance related data that the first user has consented to share is caused to be presented to the second user.