Enhancing Insurance Analytics: Smarter Data Ingestion for a Leading Transportation Company
Client Overview
The client is a globally recognized ride-hailing and transportation network leader, seamlessly connecting millions of users through its mobile app. Operating in over 900 metropolitan areas worldwide, the company has transformed urban mobility by offering convenient, cost-effective, and tech-driven alternatives to traditional taxis. Beyond ride-hailing, the client is rapidly expanding into logistics and last-mile delivery, redefining the future of transportation and mobility solutions.
Struggling with Fragmented Claims Data from Multiple Insurance Providers
Key Business Requirements:
Standardizing and Transforming Claims Data
Harmonize diverse insurance provider data by aligning inconsistent formats, structures, and languages into a unified, coherent dataset.
Linking Claims with Incident Records
Utilize advanced fuzzy matching techniques to accurately associate claims with incident data, creating a comprehensive view of each case.
Consolidating Claims Data for Financial Insights
Integrate regional claims data to enable in-depth financial performance analysis, including key metrics such as losses and recoveries.
Ensuring Data Accuracy and Integrity
Implement rigorous validation processes to enhance data reliability, ensuring trustworthy insights for informed decision-making.
Optimizing Insurance Analytics with a Scalable Data Ingestion Framework
Indium helped a leading transportation company enhance its insurance analytics by implementing a scalable data ingestion framework. This solution streamlined the onboarding of new insurance carriers and efficiently ingested data into the Hadoop ecosystem. <br /> <b>Key Components of the Framework</b><br />
Seamless Data Sourcing
- Claims Data: Collected from insurance providers via Google Drive and Box.
- Actuarial Data: Claims-to-incident mapping files sourced from the actuarial team on Google Drive.
- Legal Data: Extracted from Salesforce for further processing.
- Smart Integration: Using containerized microservices and API-driven architecture, Indium streamlined provider onboarding, minimizing system reconfiguration efforts and ensuring cost-effective scalability
Automated ETL & Data Validation
Indium developed automated ETL pipelines with data standardization algorithms, significantly reducing manual intervention and improving resource allocation.
- Data Accuracy Checks: A Python-based validation framework ensures financial accuracy and data integrity.
- Real-time Anomaly Detection: Advanced models expedite data quality assessments, accelerating insurance claim processing and enhancing operational efficiency.
Structured Data Layers
- Data Lake Creation: Files are extracted, quality-checked using a Python-based framework, and valid files are moved to the HDFS Data Lake.
- Raw Layer: Standardizes data formats to create a unified source of truth.
- Processed Layer: Data is transformed based on predefined rules and stored in processed tables.
- Consolidation Layer: Python-driven consolidation links provider data with legal and incident information using fuzzy name matching.
Exploratory Analysis & Insights
- Query Processing: Hive/Presto enables complex data queries
- Visual Analytics: Tableau dashboards provide real-time insights into claim patterns and incident trends.
- Predictive Modeling: Enables dynamic pricing strategies and risk assessment optimization for premium negotiations.
.
Impact & Business Benefits
Faster Carrier Onboarding:
Reduced data ingestion time with API-driven integration.
Enhanced Data Quality
Automated validation minimized errors, improving decision-making
Actionable Insights
Predictive analytics empowered strategic planning and cost optimization.
By leveraging advanced data engineering and analytics, Indium transformed the client’s insurance data management, enabling smarter decision-making and operational agility
Indium Driving Smarter Insurance Decisions
Our solution streamlined insurance data processes, empowering a transportation leader with faster insights and cost-saving opportunities. Discover the impact:
190+ Man-Hours Saved Monthly
Automated data standardization and consolidation eliminated manual efforts, freeing up the team to focus on high-value strategic tasks and boosting operational efficiency.
Faster Onboarding, Quicker Insights
Reduced manual data quality checks by 2-3 weeks per claim onboarding, accelerating time-to-market for new insurance providers and enabling faster data-driven decisions.
Scalable Cost Savings
A highly scalable architecture streamlined provider integrations, cutting both effort and costs for adding new insurance partners.
Optimized Premiums with Data-Backed Negotiations
Enhanced claims analytics empowered the client to negotiate better terms, reducing total insurance premiums by **5-10%**—delivering significant cost savings.
About Indium
Indium is an Al-driven digital engineering company that helps enterprises build, scale, and innovate with cutting-edge technology. We specialize in custom solutions, ensuring every engagement is tailored to business needs with a relentless customer-first approach. Our expertise spans Generative Al, Product Engineering, Intelligent Automation, Data & Al, Quality Engineering, and Gaming, delivering high-impact solutions that drive real business impact.
With 5,000+ associates globally, we partner with Fortune 500, Global 2000, and leading technology firms across Financial Services, Healthcare, Manufacturing, Retail, and Technology-driving impact in North America, India, the UK, Singapore, Australia, and Japan to keep businesses ahead in an Al-first world.
