“Big Data” two small words when combined together can have different meanings to different audiences. However, irrespective of the meaning, for the Insurance sector, with no physical products to sell, Big Data has now become a business imperative.
Historically, the usage of math coupled with financial theory to analyse and understand the costs of risks have been the backbone of the insurance sector. While the analytics undertaken by actuaries are critically important to an insurance company, the advent of modern technology as well and the data explosion that is currently taking place have expanded and reinvented the core disciplines of analysts. Today’s advanced analytics in insurance have redefined the role, scope and boundaries of actuarial science.
Like most companies in the financial services industry, life insurers collect a substantial amount of customer data during the application process but as with many other industries data collection post underwriting is marginal.
But this is slowly changing due to new customer channels and touch points. Instead of relying only on internal data sources such as loss histories, which was the norm, Insurers have now begun to analyse the individual. For example if a customer has had a policy with an insurance company for close to 6 years, paid his premium on time, has a good credit score, married with a 6 month old child and falls in the high income category insurance companies through analytics and understanding customer behaviour offer the customer a higher cover for his insurance premium besides also talking to him about the insurance and education plans for his child as well as a family health plan.
The insurance sector in India has been engaged in identifying and understanding the application of Big Data initiatives within its businesses. India has a low penetration of 0.7% and 4% in the general and life insurance sectors respectively. With the influx of FDI in India, there is an increased pressure on domestic players to up their game and expand their geographical reach. As internet access through the mobile technology continues to evolve, consumers are carrying out banking and retail transactions online and via mobile devices. This emphasizes the need gap for well-managed data services that reduce turnaround time and enhance business efficiencies. The room for growth is tremendous and the scope for Big Data in insurance has never been more pronounced.
According to Nasscom, India’s Big Data outsourcing opportunity is projected to reach around USD 1.2 billion by the end of the year 2015. Having said that, Big Data initiatives are at their infancy in India and organizations are yet to explore the full potential of Big Data and the value it brings to them.
Most Indian organizations are still grappling with the amount of data they generate. The early adopters of Big Data are expected to emerge from sectors such as BFSI, retail, hospitality and media. The challenge faced by most sectors is to analyze the data collected and identify new opportunities to store them securely and affordably.
In the financial services sector and more specifically in Insurance, the benefits of the Big data initiatives are likely to translate into a better customer experience, operational efficiency while reducing fraud and thus losses. Economic customer acquisition and persistency are the big challenges and Big Data initiatives will definitely help in managing these problems in a data driven manner. Leveraging developing data sources like the Credit Information Companies in conjunction with internal data initiatives will help the insurers’ structure data better to make it actionable.
Thanks to the Reserve Bank of India, the regulatory structure in India on data sharing in the banking industry is fairly evolved. Specialized organizations called “Credit Information Companies” are licensed by the Reserve bank of India to collect and disseminate banking information. While the Insurance companies can access the CICs, they are currently not required to contribute data to them. However, the insurance sector is also on the path to build a similar data repository that can help the industry. As in other countries, we expect that over a period of time these data repositories will also converge and begin to talk to each other.
An insurer can make the right decision wherever it is needed, including underwriting, application and claim fraud, retention, cross-selling, claims assessment and collections using the appropriate products and services and thus take their first step into the big data domain.
India Inc. can leverage Big Data Analytics to innovate and transform internally as well as through products and experiences. Moving towards data-driven and evidence-based business models allows an enterprise to understand its customer and empower its workforce.
Organizations are now realizing the value of Big Data Analytics in mining customer preferences and propensity as well as in devising technologies that deliver actionable strategies to the front end. As far as pricing goes, Big data will help in optimizing the risk segmentation leading to better pricing structure. Better insights into customer segments and preferences can also help in developing innovative and customized products and services while also helping insurers channelize their resources in a more effective and organized structure.
Large capital spends is not a requirement to derive benefits from organizational data resources. Often simple data marts focused on specific use cases can drive value in the organizations and may be the appropriate starting points to get the business teams in readiness to accept increasing levels of complexity of analytics solutions.
The effective use of data analytics can aid in enhanced customer lifecycle management in terms of heightened customer intelligence, new sourcing mechanisms, better customer monitoring techniques and of course can help prevent fraudulent claims. Data analytics can be used to understand consumer behavior, for segmentation and to develop the right offer for the right customer.
We live in an increasingly connected world that would see the Internet of Things have a huge impact on the way insurers would engage with their customers be it wearables that could produce data on the health of the wearer or a telematics connected car that communicates the, maintenance and vehicle usage that ultimately determines the premium an automobile owner pays. The days of one size fits all is nearing an end, data analytics is forcing insurers to go the “Made to Measure” way.
Try deep learning using MATLAB