AI/ML Enabled Claims Processing for a Large-Scale Insurance Claims Management Provider
Client Overview
The client is a U.S. based insurance claims management provider handling residential, commercial, and catastrophe claims. Manual effort was delaying their claims adjudication and increasing the turnaround time across the claims process.
Over the past three decades, the company has grown from a regional daily claims operation into a nationwide full-service adjusting firm supporting insurance carriers of all sizes.
Their operations teams managed delays in claim processing, dispatch coordination, and document handling. Insured customers had limited visibility into claim progress. This added more dependency on manual follow-ups and made day-to-day coordination harder to manage.
Claims Moved Faster Than the Process Supporting Them
The claims process involved multiple handoffs, and without a connected workflow, the client spent more time following up on claim movement and processing status.
01
Inspection Delays
Dispatch teams waited on inspection updates before claims could move forward.
02
Status Follow-Ups
Claims staff spent hours following up across teams for status updates.
03
Limited Progress Visibility
Insured customers struggled to track claim progress clearly.
04
Repetitive Coordination
Operational teams handled repetitive coordination work throughout the day.
05
Approval Delays
Dispatch approvals slowed down when updates were delayed between teams.
06
Disconnected Workflows
Claims operations lacked a connected process to manage dispatch and inspections.
Customer Updates Depended on Back-and-Forth Coordination
The delays did not stay limited to one stage of the claims process. They added pressure throughout inspections, and customer communication activities.
Coordination Overload
Claims teams regularly reviewed updates and managed documentation workflows to keep cases progressing. A large portion of operational time went into coordination activities rather than actual resolution.
Inspection Delays
Inspection updates moved across multiple teams before claims could proceed to the next stage. Delays between dispatch coordination and inspection updates slowed claim processing timelines across the value chain.
Inconsistent Communication
Insured customers often depended on operational teams for claim status updates. Without a connected process, maintaining consistent communication across claim stages became increasingly difficult.
Operational Pressure
The existing claims process created inconsistencies between workflows. They found it harder to maintain processing speed between inspections and claim handling teams.
We Built a Faster Claims Process With AI-Led Automation
Using .NET, Angular, and React Native, Indium digitized key parts of the claims process through AI/ML automation solutions. It helped connect claims operations into an easier-to-manage process.
01
AI-Enabled Claims Dispatch
Automated claims dispatch workflows helped reduce dependency on manual coordination and improved how claims moved between operational teams.
02
Mobile Inspection Workflows
A mobile-friendly application enabled field inspectors to assess damage and update inspection details directly from the field.
03
Dedicated Insured Portal
A dedicated customer portal gave insured customers better visibility into claim progress and communication updates.
We Built a Faster Claims Process With AI-Led Automation
Using .NET, Angular, and React Native, Indium digitized key parts of the claims process through AI/ML automation solutions. It helped connect claims operations into an easier-to-manage process.
01
AI-Enabled Claims Dispatch
Automated claims dispatch workflows helped reduce dependency on manual coordination and improved how claims moved between operational teams.
02
Mobile Inspection Workflows
A mobile-friendly application enabled field inspectors to assess damage and update inspection details directly from the field.
03
Dedicated Insured Portal
A dedicated customer portal gave insured customers better visibility into claim progress and communication updates.
04
Digitized Claims Operations
Key parts of the claims process were digitized to reduce document-heavy workflows and improve operational coordination.
Results Achieved Through the New Claims Workflow
The implementation improved day-to-day claims operations through automated dispatch workflows and faster coordination between teams. The client could respond faster and manage claim movement with less operational effort.
01
100% Automated Claims Dispatch
Claims dispatch activities moved through an automated workflow and reduced dependency on manual coordination and repetitive operational follow-ups.
02
Automatic Claim Triggering
Claims management and inspection activities were automatically triggered based on workflow progression. This helped operational teams move claims forward faster.
03
Reduced Manual Work
Digitized workflows reduced dependency on scattered documentation and manual coordination between operational teams.
04
Faster Coordination
Operational teams could access inspection updates and claim movement information faster throughout the workflow.
Claims Teams Got Out of Coordination Mode
The client now manages claims operations through a more connected workflow across dispatch, inspections, and customer communication activities. Their teams spend less time coordinating updates manually and more time keeping claims moving through the process.
The new setup gives insured customers better visibility into claim progress and helps the client manage claims operations more consistently throughout the process.
Claims dispatch activities moved through an automated workflow and reduced dependency on manual coordination and repetitive operational follow-ups.
Indium's Data Integration Expertise: Unlocking Broker Performance Insights
Our client's need for a unified view of broker performance data called for a robust data integration solution. Here's how Indium's expertise addressed the challenges:
Mapping the data landscape
We began by meticulously understanding the existing data flows ("AS IS") from the policy issuance and agency systems into the designated data platform (data warehouse or data lake). This comprehensive mapping exercise ensured a seamless data integration process.
Mapping the data landscape
We began by meticulously understanding the existing data flows ("AS IS") from the policy issuance and agency systems into the designated data platform (data warehouse or data lake). This comprehensive mapping exercise ensured a seamless data integration process.
Mapping the data landscape
We began by meticulously understanding the existing data flows ("AS IS") from the policy issuance and agency systems into the designated data platform (data warehouse or data lake). This comprehensive mapping exercise ensured a seamless data integration process.
Mapping the data landscape
We began by meticulously understanding the existing data flows ("AS IS") from the policy issuance and agency systems into the designated data platform (data warehouse or data lake). This comprehensive mapping exercise ensured a seamless data integration process.
Mapping the data landscape
We began by meticulously understanding the existing data flows ("AS IS") from the policy issuance and agency systems into the designated data platform (data warehouse or data lake). This comprehensive mapping exercise ensured a seamless data integration process.
Defining success metrics
Next, we collaborated with the client to identify and define key performance indicators (KPIs) crucial for evaluating broker performance. This collaborative approach involved creating visuals and templates to ensure clear communication and gain business buy-in on the chosen KPIs.
Building the data pipeline
Indium's team then designed, developed, and implemented a robust data pipeline. This pipeline encompassed data extraction from both source systems, data transformation, and thorough testing and validation procedures to guarantee data accuracy and integrity.
Data modeling for enhanced analysis
We built a new data model specifically tailored for the integrated data set to facilitate efficient analysis. This data model organized the information to optimize performance and enable insightful reporting.
C-suite dashboard design with Power BI
Leveraging the power of Microsoft Power BI, we constructed a user-friendly C-suite dashboard. This interactive dashboard drew upon the data residing within the data lake, made accessible through the data models we created.
A streamlined user experience
The designed dashboard comprised a maximum of 2-3 pages, each containing a focused selection of 5-7 KPIs and visuals. Additionally, we incorporated 2-3 slicers to empower users to filter and segment the data for deeper analysis.
Test, Tweak, Triumph: How Data-Driven AB Testing Ignited Business Transformation
01
Significant Boost in Referral Rates
By identifying and resolving the friction points at the sign-in page, clients achieved a remarkable increase in referral rates. This seamless user experience enhanced customer satisfaction and accelerated hiring processes, enabling positions to be filled 30% faster, closing roles an impressive 30 days ahead of schedule compared to initial plans.
02
Data-Driven Hypothesis Validation
Clients successfully validated their business hypotheses through a cost-effective, data-backed approach that minimized risk and ensured zero disruption to ongoing operations. This strategic testing empowered them with actionable insights grounded in real user behavior.
03
Informed Decision-Making with Predictive ROI
Access to predictive analytics on the potential ROI from implementing a one-touch login solution equipped clients with the confidence to make well-informed, strategic decisions. This foresight paved the way for smarter investments and optimized digital transformation initiatives.