Big Data is certainly gaining more and more popularity these days, especially among businesses and organisations.
Put simply, big data is a collection of data from a myriad of different information sources that, when properly interpreted, can generate invaluable business insights.
Big Data impacts and enhances organisations every day, helping them in different ways and in different tasks, from better marketing to fraud detection and crime fighting. The collection of data is only the first step; it’s what businesses do with that data that really matters.
With so many ways to use data for improvements, many industries are taking this data-driven opportunity seriously. The insurance industry is one such industry. Insurance at its core is about using data to formulate risk possibilities. If Big Data can allow insurance companies to make more informed decisions about risks, there will be benefits for the different parties involved (insurance companies, policy holders, and government compliance agencies).
The insurance model works like this: consumers or organisations take out policies based on the possibility of something risk-related occurring. Insurers then offer coverage based on their assessment of the costs to cover any possible claims.
Predictive and statistical modelling allows insurance companies to work out what will happen in the future by measuring and understanding data from the past. It’s often said that the past is the best way to interpret the future. Thus, past events can help insurance companies determine with more accuracy what will most likely occur in the future. This provides them with a valuable tool in their risk assessments.
Big Data’s Impact on Premiums
Insurance companies must take note of several pricing considerations which can be quite complicated. The price of the premium must cover insurers for risk as well as drive profit. However, they also have to be priced competitively. Looking at automobile insurance, for example, most likely premiums are higher for young drivers due to their inexperience and propensity for risk.
This is, however, a very competitive landscape because there are many different players, each trying to convince users that they have the best coverage, service, and price. Using Big Data can allow insurance companies to assess risk in the most effective way, helping them pinpoint gaps in risk and opportunities to offer better pricing.
Imagine if you will, how a driver’s premium would change should the insurer have access to data that shows the driver regularly sends txt messages whilst driving. Having access to, and properly utilising as much data as is available will paint the real picture and therefore enable the assessment of the real risk, not just the perceived risk.
User-generated Data’s Benefits
In the automotive industry, several insurance companies offer tracking devices which report back to the insurance company data about your driving behaviour. They’re referred to as telematics devices. When the device is installed, it taps into the car’s computer to capture and store data which could be anything that the insurance company believes is relevant such as speed or braking habits.
These programs are usually optional so it’s really up to the consumers if they want to get them. If the data is “good” consumers can then receive a reduction on premiums. Insurance companies can also aggregate all the data received from these devices to help them build additional models that reveal trends in how certain demographics drive and which ones may be more likely to encounter accidents.
Wearables Providing Valuable Insights
The field of health insurance is increasingly benefitting from data provided by wearables. Wearables would be defined as something like the Apple Watch or the Fitbit—devices that track a person’s physical activity and other information usually relating to fitness and overall health.
Health insurers see the benefits of this data in not only assessing the individual but also in making better assumptions on the health cycle of a person. In fact, a study found out that 63-percent of insurance executives believe wearable technology will be adopted broadly by the industry by the end of this year.
This exchange of information can also improve customer experience. When you prove to insurers that you live a healthy lifestyle and willingly provide relevant information, they can better understand health challenges you may face in the future. All this data could or may already be shared with your physicians, resulting in better services. This sharing of data improves the broader relationship between patients, insurance companies, and physicians.
Big Data’s Effect on How Consumers Buy Insurance
New players in the insurance industry are being called “insurtech” businesses. As the name suggests, they represent the merging of insurance and technology. Currently, buying insurance is still usually a cumbersome process with lots of questions. Well, what if insurance companies already knew the answers? That would improve customer experience and even reduce associated costs for the insurer because of more efficiency in the process. This could be one of the big “disruptors” for the insurance industry in the near future.
British insurance company Aviva is using Big Data to provide an easier way to price car insurance. Usually, users would be required to answer lots of questions to determine their risk. However, Aviva actually discovered a link between the purchase of life insurance and safe driving. It appears, people who are responsible enough to have life insurance also tend to be responsible drivers. As such, they offer a lower premium to life insurance policy owners.
Make Your Data Work for You
Regardless of industry, today’s businesses and organisations have ready access to more information about different things and situations than ever before. However, this accessibility and convenience is just a small part of the equation—proper analysis and interpretation is what really counts.
Through Latize’s intelligent data management platform Ulysses, companies are able to harmonise internal and external data sets with ease, accuracy, and efficiency. This allows them to derive valuable insights which can be used to reveal previously hidden opportunities, improve processes and services, and gain a competitive advantage. Not only that but with Ulysses’ ability to recommend a path forward, research, product and risk considerations are more accurately met.