Digital transformation carried out in the last decade has paved the path for new business models that necessitates leveraging “data science” as a tool in the entire insurance business cycle. The insurance carriers are utilizing data, computation power, and technology breakthroughs to modernize their traditional actuarial pricing and reserving methodologies.
Data science helps insurance carriers in optimizing the operational decision-making process through the integration of analytical and technological expertise. The insurance industry is leveraging new data sources such as text, audio, images, and video into both analysis and decision making at all levels. The data science tools and techniques help in discovering answers to key pain points for people contributing to various roles and capacities in an insurance company.
Data Science brings innovative solutions for every stage of the insurance life cycle like product designing, customer segmentation, risk management, underwriting, etc. It offers insurers, ways for more granular risk analysis for all lines of business. Be it related to vehicles, people, or property.
Some of the use cases that help our customers use Data and Data Science to solve business problems are
- Customer Analytics for Insurance
- Insurers can take advantage of new sources of data to better target intended customers to specific, and potentially more suitable, products. Analysis of trends in preferences and behaviors improves an insurer’s understanding of changes in consumer needs, and this insight can be useful in the development of innovative new products and the design of associated features. At Coforge we help insurance companies in building Customer 360-degree views, Campaign Analytics, Customer Segmentation, Cross-Sell & Upsell, Recommendation Engine, Clickstream Analytics, Social Media Analytics, Sales Forecast, Customer Experience Analytics, and Sales Analytics.
- Risk assessment, underwriting, and pricing
- Data Science allows insurers to do a more granular risk assessment and help their underwriters to set premiums more accurately. Detailed risk assessment can also ensure an increase in insurance coverage making it more cost-effective for end customers. Our Price optimization solution helps carriers in gathering Portfolio Insights, Claims prediction, Retention Analysis, Conversion Analysis, Quote Analysis, What-if Simulation.
- Brand Influencer
- Our solutions like Brand Awareness, Competitor Analysis, Sentiment Analytics, Topic Models, Brand Influencers help insurance companies in making strategic decisions.
- Claims management and Fraud Analytics
- Data Science has a significant role to play in making insurance claim management and associated complaints process more efficient, benefiting insurers and policyholders alike. Analysis of social media activity and connections can be used effectively to spot fraudulent claims activity by groups of people working together to make a series of false or exaggerated claims.
- Portfolio Optimization
- Our Machine learning-based solutions like Investment Portfolio Analysis, Investment Portfolio Optimization, Investment Portfolio Sentiment Analytics provide portfolio managers is a practical and efficient way of developing an effective portfolio segmentation.
- Premium Forecaster
- Our solution Portfolio Analyzer, Quote to Cash, Premium Renewal prediction helps insurance companies in strategic decision making.
- Agent Performance
- Machine learning techniques can help in uncovering various factors or influencers related to agent performance. Business Insights based on the combined ratio, the growth rate for each agent, and forecast helps in defining agent retention policies.