Transforming Indian Insurance Sector with Data Analytics Edge

Insurance Industry – A Late Adopter to Analytics

With India’s insurable population projected to reach 750 mn1 in 2020, the insurance penetration still hovers below the world average (3.9% against global average of 6.3% in 20132). However, the woes of the industry are far more than just that. Lurking behind steep growth are burgeoning customer acquisition costs, high customer churn that leads to lower retention, and cut-throat competition among players vying for a larger pie of the customer’s wallet.

Customer Acquisition

To begin with, most Indian insurers employ a salesforce consisting of agents who sell directly to customers and in return get paid fat commissions that shoot up the costs of acquiring new customers. Customer acquisition by a company refers to the process of converting prospects and inquiries to new customers by persuading them to buy the company’s products and services. As of 2011, operating expenditures and customer acquisition costs of Indian insurance companies accounted for 25% to 50%3 of the total annual premiums.

Customer Retention

The challenges to customer retention are multi-faceted. High rate of attrition among customers translates into too many policies being returned or lapsed way before they enable adequate premium income for the insurer to become profitable. Customer retention envisages the activities undertaken to retain the maximum number of customers by securing customer loyalty towards the company / brand. The key to customer retention is knowing your customer well enough to facilitate meaningful engagement. To put things into perspective, most Indian insurers collect a large amount of customer data during the initial stages of customer onboarding, i.e. the application process. As policy lifecycle changes from filing a new application to its actual usage and recurring premium payments, the data generation practically ceases. In the absence of targeted customer loyalty programmes, and given that insurance is still not exactly a favourite of the Indian household, customer relationships often wane leading to high churn rates.

Share of Customer’s Wallet

The fresh scramble among insurance players to secure a higher share of the customer’s wallet is in the light of the fact that increasing a company’s pie in the customer’s wallet is often a cheaper way of bolstering revenue than increasing the company’s share in the market. Share of wallet (SOW) refers to the proportion of the customer’s total spending that a business attains through its products and services. However, in the absence of actionable customer analytics and insights into their wallet spend, this remains a wishful proposition.

Even as Indian insurers struggled to make both ends meet, it took them five years (from 2005 to 2010) to finally start selling policies online. The price for late adoption to data analytics have been paid both by insurers and customers – Indian insurance sector lost a mind-boggling INR 30,401 Cr4 (~ 9% of the industry worth in that year) to frauds and scams in 2011.

Data Analytics in Indian Insurance Sector

Data analytics in Indian insurance sector can be perceived as a three-pronged tool – Marketing Analytics, Loyalty Analytics and Risk Analytics.

Marketing Analytics include analytics that drive efforts to maximize fresh influx of customers and attain a higher share of the customer’s wallet, such as promotion campaign analytics, segmentation and targeting analytics, price & premium optimization and marketing mix modelling. Loyalty Analytics are targeted towards optimizing customer retention rates by establishing touch-points for customer engagement on one hand and alleviating customer grievances and doubts on the other. These include analytics on customer satisfaction assessments, customer churn analytics, reduction of claims settlement periods, personalization of customer experience, claims settlement optimization, and customer life-time-value analysis.

Risk Analytics are more for the insurer than for the customer, but also with substantial spill-over effects on the latter. These include risk optimization through analytics such as analytics for fraud detection & management, operationalizing claims approval & risk scorecards, actionable analytics on policy renewal & revival, predictive loss forecasting & modeling.

Customer Analytics for Future Revolution

According to a report by BCG-Google, 75% of insurance policies in India are anticipated to be influenced by digital channels by 20205. This essentially translates into a vast online ecosystem to catalyse growth and profitability for insurers. Using multi-modal data analysis, they can zoom into both structured data (application and policy data, for example) and text-based data (such as reports and experiential data on social media) to design more powerful products, formulate correct pricing and fuel better acquisition followed by improved customer stickiness.

Data analytics has been identified as one of the most pressing issues of insurance company by a PwC report on ’Top Insurance Industry Issues 2014’. Even though the industry virtually sits on a data tank, it lacks the tools and corporate will-power to gain business advantage from that data. According to global risk solutions provider LexisNexis, presently the expenditure on data analytics by insurance companies in India is far too low.6

How far the Indian insurers are ready to walk the extra mile to enter into the analytics fold is yet to be seen – however, the fact remains that analytics will be the key to growth and profitability in the years to come. In our forthcoming blog, we will bring to you the various solutions that FORMCEPT can offer to insurers to enable higher customer acquisition, better retention and larger share of the customer’s wallet.

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