Even though insurance has been one of the industries most reliant on data since its advent, big data is busy reinventing how this is analysed and used to create competitive advantage in a digital world. Jaco Swanepoel, CEO of SilverBridge Holdings, looks at how things have evolved in recent years.
Traditionally, insurers use actuarial models to calculate premiums for products and liabilities in respect of policies and profits. These models use assumptions for the expected experience of claims and cancelations of contracts. Insurance companies will regularly use their actual data to test the validity of these assumptions.
For example, they would compare expected death claims for a past period with the actual claims for the same period. In turn, this is analysed to adjust assumptions for future calculations. Fundamentally, this is a risk management approach. The data using this methodology is used to ensure that insurers price their products and asses their liabilities correctly. Of course, the idea of using large amounts of data is not foreign to insurance companies.
“The arrival of big data has expanded the scope of storage, manipulation, and the analysis capacity beyond the scale of the traditional approaches required by insurance companies. It allows for the collection of large and varied data sets that can be analysed in ways was previously not possible,” says Swanepoel.
However, the complex analysis of large datasets can help insurers discover information that was previously invisible. In turn, this can be used to improve customer experience and reduce inefficiencies.
Examples of this includes:
- Hidden patterns – high claims ratios in certain geographical areas;
- Unknown correlations – link between exercise and back pain;
- Market trends – changing product attractiveness in different market segments; and
- Customer preferences – younger people preferring a certain product.
“This kind of information can help insurance companies make informed decisions in all areas of the business including sales and customer service. After all, an insurer is in the business of helping customers with financial assistance if certain risks materialise. These risks are normally directly influenced by the behaviour of the customer, for example back pain as a result of sitting too much. By using big data combined with the Internet of Things (IoT), insurance companies can now help customers to adjust their behaviour and reward them with better pricing.”
Because insurers already have big datasets and the skills to analyse these, it should be a logical next step for them to extract value out of the data at their disposal today.
“However, the most likely challenges they will have to overcome will be cognitive biases such as the Ikea effect that comes down to the insurer thinking its traditional analysis tools are better or already provide it with the information required. Furthermore, information bias can also be a problem. Given the amount of information at their disposal, it is easy to go into paralyses and not make any changes.”
Fortunately, there is an extensive uptake of big data for practical solutions especially around short-term insurance and medical aids.
“These providers use IoT devices and the collected data to monitor customer behaviour and reward them in some way. The most common examples are movement sensors in vehicles and fitness trackers. But eventually big data will enable insurers to deliver personalised premiums to customers based on the information and analysis generated.”
SilverBridge has over 23 years’ experience as a leading provider of insurance software solutions in the African financial services industry. Our footprint extends to 14 African countries. SilverBridge’s digital insurance suite allows financial services companies the opportunity to respond quickly to changing markets. With customers throughout Africa, SilverBridge has the knowledge, experience, and technology capabilities to help its clients do better business.