Building an enterprise-level AI module for travel insurance claims is complex. Claims processing requires handling diverse data formats, interpreting detailed information, and applying judgment beyond simple automation.
When developing Lea’s AI claims module, we faced challenges like outdated legacy systems, inconsistent data formats, and evolving fraud tactics. These hurdles demanded not only technical skill but also adaptability and problem-solving.
In this article series, we’ll share the in-depth journey of building Lea’s AI eligibility assessment module: the challenges, key insights, and technical solutions we applied to create an enterprise-ready system for travel insurance claims processing.
Our Real-Time Data Synchronization solution focuses on replicating claim history data in a live environment to ensure accurate claims processing, policy verification, and real – time customer service. This data is frequently updated, requiring a reliable solution for real-time synchronization.
Here are the key technical challenges involved in real-time synchronization of this data:
Challenge : Claims processing relies on frequent updates, such as claim statuses, amendments, and policy changes—that need to be tracked and synchronized in real time. Delays or errors in these updates can lead to inefficient operations, dissatisfied customers, and missed opportunities to resolve claims quickly. These challenges also introduce the risk of compliance issues and incorrect data handling, which can have legal or regulatory consequences.
Solution : A CDC (Change Data Capture) solution replicates data continuously and in real time, ensuring that all systems operate with the most up-to-date information. By leveraging event-driven change streams, each transactional update is captured quickly and efficiently, maintaining data consistency across platforms without disrupting system performance. This enables high-frequency, low-latency replication, providing businesses with accurate, timely data without compromising on speed or consistency.
Example: In travel insurance, as a claim progresses through stages like initial filing, verification of the cause (e.g., flight delay details), and final settlement. Each step generates updates, such as a change in claim status, new document submissions, or updated policy adjustments.
CDC captures these updates are captured and synchronized in near real time, ensuring that all systems (e.g., customer service, claims processing, and payment systems) are immediately updated with the latest information.
Examples:
Example: A traveler files a claim for a medical emergency while abroad. Initially, the claim is submitted with basic details, but soon after, additional documents like medical bills and a physician’s report are uploaded to support the claim.
If the document upload reaches the primary database before the claim status update (e.g., “approved” or “pending review”), a conflict arises because the status and supporting documentation are out of sync across systems.
Conflict resolution protocols ensure that all updates (claim status and document uploads) are synchronized in the correct order across all platforms, allowing the insurance representative to see the most recent data and make an informed decision.
CDC continuously monitors the client’s database, capturing and synchronizing changes as they happen. This approach creates a real-time replica of the client’s data on our side, ensuring critical information—such as claim history and policy updates—is always up to date. By capturing updates directly from the client database, CDC reduces the need for frequent API calls, which may be restricted or unavailable.
For travel insurance providers, CDC enables immediate access to essential data, including new claims, policy changes, and status updates, without additional load on the client’s database. This reduces processing delays, improves service quality, and allows insurers to respond quickly to customer needs.
Example: When a customer files a claim for a delayed flight, our synchronized replica instantly reflects the new claim details, allowing us to process the claim without repeatedly querying the client’s system. This setup accelerates response times, allowing our teams to provide faster, more accurate service.
Using Change Data Capture (CDC), we can automate customer engagement workflows by continuously monitoring and replicating client data in real time. CDC captures critical customer data points—such as travel dates, policy updates, and claims status changes—without needing constant access to the client’s live database. This enables us to activate personalized communication campaigns based on real-time data, independently and efficiently.
Example: If we launch a WhatsApp campaign for customers with upcoming trips, our system uses replicated data to identify departure dates and send personalized messages such as coverage confirmations, safety reminders, or document checklists. CDC ensures that these messages are sent at the right time without needing frequent database queries, allowing real-time relevance with minimal load on the client’s system.
APIs are typically the main access point to client data, controlling who can access information and how often. However, frequent API calls can lead to performance issues and potential security risks. CDC minimizes these dependencies by creating a real-time replica of the client’s data on our side, enabling independent data analysis and engagement without constant API access.
Why This Matters: This approach ensures reliable, secure data access that reduces the load on client systems. With less reliance on APIs, we achieve both data accessibility and operational efficiency without impacting the client’s live infrastructure.
Benefits:
Example: During events such as severe weather disruptions or unexpected travel advisories, travel insurance providers often face a surge in claims and policy updates. With a synchronized replica using CDC, we avoid hundreds of daily API calls that would typically be needed to track each new claim or status change.
Instead, CDC continuously updates our system in real time, enabling rapid analytics on claims volumes, proactive customer notifications, and efficient claims processing workflows—all without placing additional load on the client’s live system.
With CDC, a real-time replica continuously feeds updated data into machine learning models, allowing us to generate insights and automate processes without accessing the client’s primary database. This setup supports predictive analytics in claims processing and risk assessment, using the latest data to enhance forecasting and decision-making.
Example: For a travel insurance provider, our predictive models analyze claims data to identify trends, such as an increase in claims related to specific routes, seasons, or areas affected by adverse events (e.g., hurricanes or political unrest). With real-time data replication, these models are constantly refined, helping anticipate high-risk scenarios, streamline claims processing, and improve response times. This leads to faster, more accurate claims assessments, enhancing risk management and customer service.
CDC not only enables real-time data synchronization but also supports a scalable architecture that adapts to evolving needs in travel insurance. By establishing a synchronized data replica, CDC provides a secure, flexible system that can manage growing data volumes and increasing complexity.
Why This Matters: Travel insurance data is dynamic, with constantly changing formats and high data volumes. CDC’s architecture is designed to meet current operational demands while seamlessly scaling for future growth.
At Ancileo, our CDC-based approach to data synchronization provides efficient, secure, and flexible solutions for managing travel insurance claims. By supporting real-time updates and preserving client infrastructure, CDC enables scalable, data-driven operations tailored to the needs of the travel insurance industry.