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Efficient claims processing has become a top challenge for insurance companies as the cost and complexity of healthcare continues to rise. Redis Enterprise provides the building blocks for modern digital claims processing platforms with in-memory database performance, real-time event processing, and AI/ML model serving.
Insurance companies receive millions of claims each day from healthcare professionals through a vast array of software platforms. Errors in the claims process lead to countless phone calls and resubmittals that waste time and raise the cost of care.
While electronic claims submission is growing in popularity, many claims-processing entities use multiple internal and external systems that require days between processing steps. Payers and providers are now looking for ways to integrate different claims platforms, or build their own end-to-end systems.
Traditional claims processing systems that run on legacy hardware and rely on inflexible approval rules can’t process claims quickly, and are significantly harder to update over time. Modernizing these systems with cloud infrastructures, event-driven architectures, and AI inferencing means insurance claims can be efficiently handled in real time.
Inefficient claims processing forces healthcare professionals to waste time chasing payments instead of spending time on patient care, leading to worse health outcomes for patients and higher insurance costs. Redis Enterprise provides the real-time performance and modern data models needed to power real-time claims inquiries, instant member lookups, auto claims adjudication, and more.
Events can represent the steps of the claims process without requiring tightly coupled application logic. Use Redis Enterprise to trigger data processing in response to updates in your claims processing workflow, and as a store for real-time events and streams.
A claims status inquiry often involves expensive queries across dozens of different systems. Redis Enterprise can be used as an event store and search engine for more efficient claims status inquiries, or as an in-memory database for best performance.
While AI and machine learning models typically need to query reference data stored in a separate database, Redis Enterprise lets you serve deep-learning models directly where data is stored to enable faster claims auditing and fraud detection.
Caching decreases application response times by serving frequently needed data from an in-memory cache instead of making calls to a database with network-attached persistent storage. Redis Enterprise provides enterprise-grade caching with expiration and eviction policies to efficiently manage cache objects, global distribution with Active-Active replication, and virtually unlimited scale.
Redis Enterprise can act as an event store with Redis Streams supporting claims processing platforms designed to ingest and analyze large amounts of transactions in real time, or process data in response to real-time events.
AI and machine-learning models are increasingly being used to improve the speed and accuracy of fraud-detection platforms, but the need to query reference data stored in a separate database creates network overhead that makes processing times much slower. Redis Enterprise lets you serve deep-learning models directly where your data lives for dramatically increased performance, enabling faster and more accurate fraud analysis.
RedisGears is a serverless engine for transaction, batch, and event-driven data processing in Redis. It enables you to execute data flows in Redis in almost any deployment environment with infinite programmability. RedisGears enables use cases like write-behind caching, event processing, and the use of multiple models together in Redis to power more sophisticated fraud analysis.
By combining Redis modules and data structures, Redis Enterprise can power multiple components of a digital claims processing platform. The result is a simpler architecture that can process data across multiple models without needing to run multiple database clients and connectors.
Redis Enterprise uses a shared-nothing cluster architecture and is fault tolerant at all levels—with automated failover at the process level, for individual nodes, and even across infrastructure availability zones, as well as tunable persistence and disaster recovery.
Redis Enterprise comes with role-based access control (RBAC), administrative auditing, built-in encryption, and integrations with external identity providers to meet the security and compliance needs of your organization.