The Capgemini World Insurance Report of 2008 describes the penetration of life insurance in India as ‘still woefully low’.  India had 16% of the world population, but only 1.68% of the world life insurance market in 2006. India is also far behind world averages in terms of insurance penetration, and insurance density. A mere 20% of the insurable population aged 20 to 60 years is currently covered by life insurance. The average number of policies (life/non-life) held by per Indian consumer is just 1.33 as against 5.2 policies per consumer in mature markets.

As we can see from the numbers, the potential for expansion of the market is huge especially with rising per capita income and a growing middle class that is expected to constitute 32% of the total population in 2010. The insurance penetration levels as a percentage of GDP is expected to grow to 6% by 2012 from the current 4.8% which would translate to a CAGR of 13% for the industry in the next five years.

Insurance companies in the developed world, where insurance has much higher penetration, realize the huge potential of insurance industry in India.  Add to it the fact that the possibility of Foreign Direct Investment(FDI) cap in the sector rising up to 49% and we have  just another factor that holds promise of leading the growth in this industry. Although currently FDI is capped at 26%, it’s soon expected to be raised. This will result in increased investment by foreign companies, especially by the foreign partners of private life insurance companies. For instance, Max group is already in talks with its partner, New York Life Insurance to chalk out a plan to increase the latter’s stake. Foreign companies who are interested in FDI have deeper pockets compared to the relatively small Indian insurance companies. They bring with themselves the ‘best practices’ distilled through years of rich experience that they have had in this industry. This augurs well for the insurance sector because the deep pockets and ‘best practices’ of foreign partners can be dovetailed with the awareness of the Indian psyche and marketing experience, of their Indian counterparts to create a synergy which can increase the reach of insurance in India making it more egalitarian.

But, as an increasing number of business houses enter the life insurance industry, even survival is going to be difficult for many companies. In the face of such stiff competition, organizations need to make sure that they put their efforts in the right places like retaining sales agents or minimizing lapsation rate. This is where data analytics comes in, as it helps making informed, analytics driven decisions, in these vital areas.

The role of Data Analytics

Insurers have an abundance of data across their organizations, but most have not leveraged the full potential of this data in customer acquisition, underwriting, claims servicing and customer management. Insurers need to improve data collection, prioritize the application of analytics across the customer life-cycle and build an analytics capability to create a sustained culture of data driven decision making.

The insurance business though rich in data, but is mired in data complexity. Even new companies less than 5 years old have a million clients. Older and  large companies e.g. LIC have over 130 million policies. Insurance policies have a large amount of data, and they are complex in structure, with variations such as benefits, face amounts, schemes, pricing, claims, multiple client relationships, medical history and family history and underwriting.

This combination of volume and complexity is unusual; this makes it difficult to manually understand the data, and its trends. Thus, the insurance business is ideally suited for the application of statistical methods.

Currently, use of statistics is largely limited to actuaries for determination of the insurance premium rates. Statistics can have wide applications in other departments of an insurance company.  For instance, the agency department can use statistical methods for combating high agent attrition rates and hiring productive agents. Also, the marketing department can use statistics to identify target customers for cross selling a new insurance policy.

There are many such business problems in different areas that can be tackled using statistical approaches.  These include:

Agency department

1. Agency force attrition
2. Insurance agent productivity and agent success factors

Renewals department

1. High lapse in the initial years of the policy

Marketing & sales department

1. Identification of customer segment for cross-selling
2. Features to be added to a new product and understanding customer needs
3. Identifying gaps in product mix
4. Customer segmentation

Operations department

1. Reducing turnaround times of new business and policy owner servicing processes
2. Fraud detection patterns
3. Enhancing product profitability

Let’s look at a few examples of how data analytics can be used in some of these cases.

Agent attrition

Since the number of agents directly corresponds to an increase in policy sales, it’s very important to retain productive agents. Statistical tools can be used to look into agents’ history and profile the productive agents and also predict which agents are likely to leave in the near future. This will enable the HR department to take steps to retain the agent or the sales manager.

Statistical tools like chi-square goodness of fit test or logistic regression can be used to determine the profile of a productive agent or an agent likely to attrite. Predictive models can be built in commercially available tools such as SAS using methods like binary logistic regression, Classification trees or neural networks.

Cross-selling

It costs five times more to acquire a new customer than to retain an existing one. Encouraging existing customers to spend more not only increases profit margins but also ensures that the relationship with the customer is strengthened and therefore the customer is less likely to stop paying premiums.

In this process, existing customers who are likely to buy another product are identified and sales campaigns are targeted to these customers thereby increasing the cost effectiveness of the campaigns. Let’s take the example, where the Insurance Company knows which one thousand customers out of their one lakh customers have teenaged children; they can target these thousand customers with products tailored to teenaged children.  This was just one out of myriad such possibilities waiting to be exploited by the sector.

Today's competitive market has made it imperative that every opportunity to gain competitive advantage be explored and used. The critical link between good decision-making and success has become more important than ever before. When it comes to the business of insurance, efforts to integrate data analytics with the decision making process would be a step in the right direction. But, as with any analysis, the quality of data analysis is only as good as the quality of data itself. So, it’s vital to set up proper MIS systems for capturing data apart from having dedicated teams for refining the quality of the data. Extensive data mining follows thereafter. Achieving all these will get their noses in front in this overly competitive environment by increasing the width and depth of its customer base.  When all this happens, we can sit back and relax, without worrying too much about the security needs. Now that’s what true development is!