- Advanced fraud analytics for a leading US P&C insurer resulting in identification of 21,000 (Fraudulent) referrals amounting to 14 Mn USD in a span on 5 years.
- Streamlined operations across multiple countries with significant cost savings through ADMS for One of the largest US global life insurer
- Lapsation modelling for a global insurance major for its India operations. Predictive models developed for agent retention analytics, agent LTV analytics, CLV analytics, lapsation and collection analytics and a business intelligence framework to enable collections intelligence to be used by 600 offices across India
- End to end BI delivery through agile to a leading provider of general insurance, banking, life insurance and superannuation in Australia and New Zealand, resulting in reduced spend on application maintenance by over AUD 4 million/year and also achieving 98% on time availability of all critical applications
Enabling Custom Data Strategies
Insurers face significant challenges due to legacy systems, inconsistent data, and inadequate analytics. Rising customer expectations and risk management costs necessitate effective data strategies and governance. Key priorities for insurers include understanding customers, providing hyper-personalized services, and addressing operational inefficiencies like fraud, lengthy documentation processes, policy risk, and manual data validation.
Solution Overview
Insurers must deploy advanced analytics and AI/ML to streamline business operations and improve profitability. We help Insurers build data and analytics capabilities in the following four areas to address their business challenges:
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Insurance Use Cases
Proof Points
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