The financial services sector, especially insurance, has always been known for its conservative approach. However, to maintain the competitive edge, it has become very important for even the most conservative of insurers to adopt new technologies like Big Data, which helps companies to process very large amounts of information, increase the efficiency of workflow, design products that customers actually need, and reduce the costs of operation.
The Impact of Big Data on Business
All businesses generate huge amounts of data on their customers and the competitive environment. Earlier, when their ability to process this mammoth amount of data was limited, the businesses could not take advantage of the data to improve their products and services or get an insight into customer behavior that allowed them to gain a competitive edge. However, with the relatively easy access to massive computational power at cheap costs and the ability to apply artificial technology to analyze the data, it has become easy to convert it to meaningful information that can be applied on several fronts. Commonly, Big Data is used to develop new models of distribution and customer interaction like chat boxes, robo-advisors, virtual assistants, etc. to enhance the quality of the customer experience and make the marketing efforts more finely targeted. Big Data also lies at the core of process automation as it allows the improvement of the efficiency of the internal workflows by replacing manual intervention with automation. Important fallout of the impact of Big Data implementation is that it enables businesses to create new business model concepts that can provide them with a sharp competitive edge.
The Implications of Big Data for Competition and Innovation
The bedrock of insurance has traditionally been the analysis of various kinds of data like the personal information on policyholders, accident statistics, mortality figures, and trends, as well as multiple third-party sources of information that are used to classify people into different risk categories, prevent losses from fraud, and optimize expenses. The rapid movement towards the adoption of digital information collection and processing has opened up several new sources to the insurance industry that can be used to build a complex pattern of behavior for each customer and assign a specific risk class. The most popular new sources of data are online behavior that includes online shopping patterns, internet browsing behavior, and social media presence and activity and data drawn anonymously by sensors that are embedded in the many smart devices that we use like cars, drones, smart homes, Internet of Things, etc. Data from these new sources can be combined with that drawn from the traditional sources to generate insights into the lifestyle and behavior of a person in real-time that can be used to establish an enduring competitive advantage.
Applications of Big Data in the Insurance Sector
It is the opinion of experts in the insurance business that the ability to stay competitive in the insurance sector by companies will increasingly depend on how they can access data and derive fresh risk-related perspectives from it. The use of Big Data can make it possible to discover new approaches for encouraging prudent behavior thus permitting the new technologies to allow the role played by insurance to progress from just protection from perceived risk to the actual prediction and prevention of risk. A peek into what Big Data can do for the insurance industry:
Acquisition of Customers
Rather than relying on the answers provided by the customer in a structured format of an application form, it is possible to get more accurate insights into a person’s preferences and behavior by analyzing the huge amounts of data that he generates during the usage of channels like email, social media, and other methods of electronic feedback such as web browsing behavior. The diversity of the sources and the sheer amount of unstructured data makes it possible for insurance companies to increase their efficiency of the acquisition of new customers belong to a targeted profile.
Customer Retention
With customer acquisition being very difficult and expensive, insurance companies need to focus on retaining their existing customers. Since no customer leaves all of a sudden, analysis of Big Data can reveal early signs of any dissatisfaction so that the insurance companies can react quickly and address the specific complaint and generally improve their services to remove common pain points. Customer loyalty can be increased with improved insights into what the principal reasons of dissatisfaction are and addressing the issues in multiple ways like changing the pricing, offering discounts, etc.
Assessment of Risk
The profitability of insurance companies is traditionally liked to how efficiently and accurately they can assess their customers’ risk and offer them products that address the risk concerns at prices that are competitive. The application of Big Data technologies can substantially elevate the efficiency and accuracy of risk assessment making it possible to offer insurance products that are structured better and priced better. Big data-enabled predictive modeling methods also make it possible for the insurance companies to make an assessment of the specific issues and concerns that can arise from individual customers and very accurately determine their risk profile.
Fraud Prevention and Detection
According to http://www.insurancefraud.org, the website of Coalition Against Insurance Fraud, American insurance companies lose more than $80 billion due to incidents of fraud. The effect of this is the reduced profitability of the insurance companies and increased premiums for each and every customer. Using Big Data modeling techniques, insurers can figure out customers who are more likely to have been involved in fraudulent practices and investigate their application in more detail.
Personalization of Services and Pricing
Among the biggest advantages of Big Data is that the analysis of massive amounts of unstructured data helps insurers to understand better what the customer really needs. The insurance companies can then utilize the information to structure offers that are more customized by taking into account his behavioral patterns and medical history. The result is a product that is more suited to the needs of the customer, fits his budget better, and yet delivers the insurer the profitability and safety required for stakeholder satisfaction.
Conclusion
Big Data has multiple benefits for the insurance sector; it not only can automate numerous manual processes making them more accurate and efficient, reduce costs of operation, help in developing new policies that suit customers’ better, but also deliver a competitive edge or improved client acquisition and retention.