INSURANCE
INSURANCE
The insurance sector has always relied on data and analysis, to mitigate risks and gain insights about customer behavior. Insurance companies often face roadblocks in terms of speed, scale, and efficiency, while trying to collate, process, and manage huge volumes of data. This has become an even bigger challenge with diverse sources like telematics, customer interactions, government data, and social media. That’s where Sigmoid’s robust data engineering and data science practices come to the picture. Our services in ML, AI, and big data analytics have opened up promising possibilities in the areas of:
The insurance sector has always relied on data and analysis, to mitigate risks and gain insights about customer behavior. Insurance companies often face roadblocks in terms of speed, scale, and efficiency, while trying to collate, process, and manage huge volumes of data. This has become an even bigger challenge with diverse sources like telematics, customer interactions, government data, and social media. That’s where Sigmoid’s robust data engineering and data science practices come to the picture. Our services in ML, AI, and big data analytics have opened up promising possibilities in the areas of:
Use Cases
Use Cases
Success Stories
Client
Leading Healthcare Insurance Company
Challenges
Existing system was based on manual rules and lacked predictive model
Sigmoid Solution
Built an ML-backed underwriting system to assign overall group risk score using lab/diagnostic, prescription, and claims data at multiple levels and data bridges
Impact
Increase in the margins on deals by 8%
Download Case Study
Group-Risk-Assessment-Scoring
Client
Leading Fortune 500 Firm
Challenges
Limited personalization and manual testing process with nascent ML capability
Sigmoid Solution
Built personalized customer and offer affinity model using customer (monetary, demographics, past behaviour etc), offer (discount, product, type etc), and other parameters
Impact
12% improvement in average conversion rates
Download Case Study
Personalized Marketing Effectiveness
Client
Insurance Tech Startup
Challenges
Manually identifying replacement cost of items in an insurance claim was labor intensive and time-consuming
Sigmoid Solution
Improved accuracy by creating ontologies for the development of rules and finding similarities among products
Impact
Faster and more accurate settlements
Download Case Study
Property-Claim-Estimation
Technology Stack

Tech-Stack-for-Data-Analytics

Success Stories
Group Risk Assessment Scoring
Client
Leading Healthcare Insurance Company
Challenges
Existing system was based on manual rules and lacked predictive model
Sigmoid Solution
Built an ML-backed underwriting system to assign overall group risk score using lab/diagnostic, prescription, and claims data at multiple levels and data bridges
Impact
Increase in the margins on deals by 8%
Personalized Marketing Effectiveness
Client
Leading Fortune 500 Firm
Challenges
Limited personalization and manual testing process with nascent ML capability
Sigmoid Solution
Built personalized customer and offer affinity model using customer (monetary, demographics, past behaviour etc), offer (discount, product, type etc), and other parameters
Impact
12% average conversion rate
Property Claim Estimation
Client
Insurance Tech Startup
Challenges
Manually identifying replacement cost of items in an insurance claim was labor intensive and time-consuming
Sigmoid Solution
Improved accuracy by creating ontologies for the development of rules and finding similarities among products
Impact
Faster and more accurate settlements
Technology Stack