What is Big Data?
Big data can be defined as extremely large sets of data that may be analyzed to reveal patterns, trends, and associations. It can be used to benefit numerous industries and sectors, but I’m going to focus on its influence on the Insurance industry at this time. Big data can provide an enormous amount of information to help insurers achieve many of their long term goals. The objective is to utilize the data collected to make the industry more efficient, lower risks and costs, and provide better access to information while creating innovation. When analyzing the insurance sector, Big Data can play a major part in Auto, Life & Health, and Property insurance. Using data properly can help companies use predictive analytics as a means to extend their product lines, reduce claim expenses, set better loss reserves, and cut operation costs. Let’s take a look at a few ways that Big Data can help change the insurance industry, analyze some of its issues, and discuss ways to implement its use to help benefit insurers.
Applying Big Data
Nearly 10% of insurance claims are fraudulent, causing over $25 billion a year to be lost due to fraud claims in just the P & C industry alone. Utilizing data from your company’s claim history, preventive analytics can assist in prioritizing claims. This is accomplished by recognizing when a submitted claim type has previously resulted in a higher payout amount. With the proper data, insurers can decrease their chances of fraud claims. They can mark their submitted claims by the estimated settlement size to determine which claims are higher priorities and which should be investigated further. By managing Big Data, predictive analysis can properly notice fraud sooner and more effectively at each step in the claim cycle. Information such as demographics and examples of the more frequent types of fraud cases reported can be used to help recognize fraud during the claim process.
Currently, most claim adjusters believe that their companies do not utilize the information that it collects from the claims department. The more insurers use more preventive analytics, the more breakthroughs that will be achieved. Using Big Data as part of the claims process can be a resource that differentiates your company from others. It can also create a cost savings to the company’s bottom line. Just a 1% improvement in loss ratio for a billion dollar company can save 10’s of millions. Insurance companies that utilize this data will mean that insurers would be combing data that they already have access to such as MVRs, clue reports, and the company’s database. They will also access new resources for data such as security cameras, tracking sensors, utility records, and even social media. In addition, adding sources such as traffic and crime reports can give a company a great assessment of a claim risk. Analytics can also shorten the claim cycle and save on payout and operation costs. Loss reserves can be calculated more appropriately by comparing the reported loss with similarly filed claims. A system can be set up to re-evaluate the reserves as the claim information is updated. Analytics can also provide a chance for certain claim submissions to be marked for closer inspection and priority handling. This would allow more senior adjusters to handle certain files from the start more efficiently. This information can also help the insureds with risk management. Analytics can predict the chances of a loss such as wind or theft, and help the insured take steps to avoid or decrease the chances of a loss.
A claim that has to go to litigation can cause a company to use a lot of their expenses. Insurers can utilize Big Data to calculate which claims are more likely to result in litigation. When recognized, these claims can then be assigned quicker to more experienced claim adjusters, who could potentially settle the claims faster and for a lower settlement amount
Utilizing data collected can assist in finding subrogation opportunities. Using processes such as text analytics can help find subrogation opportunities earlier in the claims process. This will help to minimize loss expenses and maximize subrogation collections. By recognizing these opportunities sooner, you can organize your information needed and start the subrogation process in a timelier manner.
Data used for predictive analytics can allow the underwriter to sort out the normal submissions, and have the exceptions handled manually by more senior underwriters. This would allow the underwriters to spend less time screening lower risk applicants, and focus on the more unusual cases with higher risk factors. In areas such as homeowners insurance, carriers are utilizing data to make better predictions about vandalism, theft, and flood risks. The carriers that implement these practices in their process will be the competitive companies in the near future. Underwriters will also be able to properly locate potential problem risks upfront and decline to quote, or surcharge appropriately with exclusions or special deductibles.
Analyzing data correctly can lower your marketing expenses and improve your organization’s success. Helping to define your target audience and monitoring your current marketing plan for efficiency are just 2 examples of the benefits of data to your marketing needs. Information can also assist with your social media use, website, and mobile marketing strategies.
Big Data can also improve your company’s process to create better services, lower premiums, increase your sales, lower operation costs, improve loss ratios, increase customer retention, and return higher profits.
Challenges of Using Big Data
There are currently a few challenges for implementing techniques of gathering and using Big Data. One of the main challenges is sorting out the irrelevant information to find the appropriate information that will provide the most benefits and competitive advantage. Once the information is gathered, you must then determine how to utilize it to save costs and increase revenues for your business. To properly gather and analyze Big Data, insurers will have to provide more funding to their IT Departments and make sure they have adequate cloud storage space for this data. The availability of data and the ability to collect data from various sources into a meaningful format is the biggest area where companies fail in their effort of creating predictive models. This can cause inaccurate data, which can harm a company if applied incorrectly. Also, most insurers lack the ability to collect and analyze data, which can affect their decision-making, business growth, and delivery of great customer service. Collecting and analyzing lots of information can be complex and expensive. There is also the fact that most consumers do not like their personal information being obtained and used. But research has also shown that most individuals would not mind giving up some personal information if it can give them a savings on their premiums.
With the current amount of technology available today, every industry has the potential to change the way that companies do business. Big Data is helping companies that are striving to be on the leading edge in their industry. The volume of information that is becoming available is growing exponentially, and we are now creating the tools to be able to organize and manage this data. Unlike other sectors, the insurance industry has gotten off to a late start to utilizing Big Data, but they are now using it for methods of predictive sales models, marketing, customer service, as well as claims and underwriting. In order to remain competitive in the future, insurance companies will need to take advantage of Big Data. There will be few companies that will emerge and change the industry. These trendsetters will be the companies who embrace change and adjust their processes around this abundance of information available.
You may be thinking, “Where do we start?” Currently your company may have access to large amounts of information from claims databases, company notes, and publications. Start by determining how analytics can bring value to your company. Become aware of the numerous resources available and how to integrate them to your operations, and improve the automation of your workflows and predictive models. Many insurance companies should reinvent their information management process to get the most value from the enormous amount of information they’ve been collecting for years. Companies’ constant interaction with insureds, agents, and brokers accumulate lots of information with few utilizing that data for external and internal gain. John Anderson, senior managing consultant in IBM’s North American Strategy and Analytics Practice says, “Insurers are sitting on a virtual gold mine of information. Claims activity, underwriting activity, sales and distribution activity. All of that information should be collected and compiled, and that’s beginning to happen as insurers go through transformational changes to their claim systems, underwriting platforms, and even to their distribution capabilities.” There are no limits to the ways information can be captured for analyzing. Information can be gathered from satellites, fitness wearables, social media, construction plans, weather data, energy resources, traffic cameras, drain systems, Nest home thermostats, and more. Within your organization, you can gather data from your company reports from sales, marketing, distribution, and operations. You can then develop analytic tools to improve theses areas. Once the data is obtained, there are many ways to organize and analyze it. Information can be sorted by coverage lines, geography, industry, claim type, age of insured, amount of loss payouts, or premium amounts. Look for areas of growth, opportunity, and help evaluate performance and workload of individuals. Expand your company’s ability to implement new products, new markets, and new coverages.