From consumer behavior to the ROI of marketing campaigns, insurers want to be able to leverage the information to turn big data into actionable and revenue generating steps.
Being ahead of the curve is key when it comes to leveraging your data in a competitive industry. Here are some the latest trends to help you do even more with your information.
Today, the data primarily used in insurance analytics is known as “structured data”. This data is volunteered directly by consumers (e.g. name, address, age, gender) or anything that might be entered into standard forms and tables. This information is easily accessible but it doesn’t really form a complete image of the consumer. On the other hand, unstructured data takes into account things like social media or written reports. New technology, like the IoT, has created a way to mine unstructured data which allows insurers to create a more robust profile of customers and consumers. In fact, social media data is even being used in insurance fraud detection and communicating with current and potential customers. Big data that uses this formerly inaccessible data forms a huge part of the once-missing analytical puzzle.
With the rise of access into a whole new world of data analysis, new regulations and legislation around data have been put in place. These are fundamentally changing the ways in which insurance companies and their analytics teams can work. The General Data Protection Regulation (GDPR) was put into place last year in the European Union, setting off a global rethink on data protection. In case you missed it, the GDPR lays out exactly what kind of consumer data can be collected, and arguably more importantly, how. In the U.S., all 50 states include some kind of data protection laws with the strictest held in California and Vermont. To comply with the new standards, it is essential for insurers to works with flexible and scalable data systems to evolve with the regulations over time.
Internet of Things (IoT)
With the rise of the internet of things (IoT), we are constantly generating incomprehensible amounts of data. In fact, 2.5 trillion quintillions (that’s 15 zeros) bites of data are generated every day. For perspective, around 90% of the world’s data has been generated in the last 2 years. Let that sink in for a moment. So now, the IoT’s role in big data is unlimited. It gives insurers access to an amount of insight unimaginable before that can impact every area of their business. In 2019 alone, IoT insurance data will be used to improve risk assessment, marketing campaigns, claims processing, claims leakage and product pricing. With the leaps and bounds we’ve seen in just the past year, it’s hard to imagine the IoT’s role in InsurTech and P&S Insurance software over the coming years.
One of the hardest parts of extracting actionable insights from the data is its sheer size. There are not enough man hours in the day to effectively and efficiently channel such a large amount of information into concrete findings. That’s where machine learning comes in. With this new capability companies are now able to sift through enormous quantities of information with even better accuracy and efficiency. Not only can AI be leveraged on historical data to glean insights on past trends, it can also be used proactively to shape products and operations. Machine learning can boost efficiency and effectiveness in everything from marketing to pricing strategies to claims.