Leveraging Data — Both structured & unstructured, internal & external — forms a key building block to script & realize a successful digital transformation journey for enterprises.
Looking closely at the insurance sector — Proliferation of data is on a rise presenting unprecedented opportunities for insurers to develop actionable insights on– potential markets, customers, competitors, risk and natural disasters.
Key questions in the minds of leading insurers today are:
What more can our data tell us?
If we add external data to our models — what additional insights will we receive?
How can analytics boost day-to-day decision making across the insurance value chain?
It’s pertinent for incumbent insurers to infuse advanced analytics capability into its DNA to operate more efficiently, reduce time to market for new products, gain more insight into customer needs and prepare a sustainable competitive advantage against Insur-Techs.
Understanding Advanced Analytics
To begin with, let us understand the building blocks & power of Advanced Analytics
Data Mining: This involves providing the raw data which is in turn used as an input for the various analytics solution stages — Descriptive, Predictive and Prescriptive Analytics
Descriptive Analytics: It entails uncovering existing insights and creating connections between data points and sets, as well as cleaning data
Predictive Analytics: Clean data sets and existing insights are used for extrapolation and making predictions about future business outcomes, trends and customer behavior
Prescriptive Analytics: Referred to as the ‘Final Frontier of Analytic Capabilities’ — it goes beyond predicting the future, suggesting actions to benefit from the prediction and showcasing the implications of each decision option.
Further, Advanced analytics also includes the trending new-age technologies like artificial intelligence, machine learning, visualizations, neural networks and also semantic analysis! Combining these together, we create a powerful solution suite to make reliable predictions and generate actionable insights at a large enterprise level.
The Indian Lens: Present
The Indian Insurance Industry is characterized by under-penetration due to the macro-economic factors of the country. To boost insurance adoption among consumers, advanced analytics has proven to be a valuable asset by helping insurers calculate the right insurance amount for individuals and digitize the underwriting & claims management process.
Both life & general insurance companies in India are increasingly riding on the advanced analytics bandwagon, discovering opportunities across:
Cross-sell propensity models to target the right customers with the right products
Customer retention analytics
Customer management using customer lifetime value models.
Business Process Improvement to track & enhance sales productivity
Improved revenue visibility by forecasting sales & renewals
Forecasting demand at call centers to improve operational efficiency
Enhancing risk management by embedding analytics in internal audit and estimating the risk of early claims etc.
The Indian Lens: Near Future
Considering the current information infrastructure, high regulatory challenges, threat from Asian Insur-Techs and the exponential technology curve, we predict immense potential and adoption of:
AI-powered single-click based policy issuance and claims management solutions
Recommendation engines suggesting what insurance products one should be buying when — boosting customer loyalty
Customized pricing for — life insurance based on health status and lifestyle; motor insurance linked to driving style and locations
Advanced analytics tools of AI-enabled virtual assistants, audio/ image/video-enabled claims processing will be driving the upcoming digital insurance wave.
Deep Dive Into Successes
Digital Transformation in Insurance is synonymous with — Reinventing the Core Business. Let’s take a look at some of the successful advanced analytics applications across the Insurance industry
1.Innovating traditional distribution channels: A leading insurer built an advanced analytics platform to match customers and agents based on demographics and behavioral data which drove up sales substantially
2.Innovating Underwriting: High variability in decision processes and long wait times — result in application drop-outs. To overcome this, a leading insurer built an AI-enabled learning model and initiated testing using historical claims experience & underwriting decisions. This enabled a significant reduction in underwriting cost per application along with faster turnaround time and increased sales through better pricing.
3.Modernizing the Policy Administration System: A leading insurer optimized the required information on customer applications by leveraging third-party data to pre-fill information and standardized the data capture across the product portfolio to better support sophisticated analytic solutions. Further, it went about building analytics on to the PAS by- creating actuarial tools to monitor risk levels and provide early warning signs to the business, developing performance dashboards to make profitable decisions on target markets and pricing, establishing underwriting portfolio performance targets and link submission routing based on actual performance.
The scope for advanced analytics to yield business benefits is extensive spanning across the insurance value chain — Sales, Product & Pricing , Commercial Underwriting, Claims Management, Regulatory Compliance, Customer Data Protection and Customer Experience. To decide on the priority of use cases, incumbents must consider existing technology landscape, capability, capital availability and competitive positioning.
NSEIT is the trusted technology partner for 6 of the Top 10 leading insurers in India. We have expertise across underwriting, distribution, cross-sell, customer management, claims and risk functions where we have leveraged ML-based predictive algorithms and interactive visualizations to drive business growth.
To know more, visit — https://nseit.com/dataanalytic