Taking data analysis to the next level with AI
The Internet of Things (IOT) and artificial intelligence (AI) are just some of the technology phrases that are becoming part of business discussions at insurance companies across South Africa. Kelly Preston, data analytics manager at SilverBridge, discusses how they contribute to next-level data analytics.
Even though insurance companies are incredibly data rich, very few of them harness the potential of data for more customised solutions tailored for an increasingly knowledgeable customer base. It is no longer good enough to provide generic products and services. The connected citizen expects more nuanced offerings that consider their specific wants and needs.
With the growth of IOT (the telemetry systems of old), insurance companies have an incredibly powerful ally to create such bespoke solutions. Already, some are using these devices to track driver behaviour for reduced (or loaded) premiums. Up until recently, much of this analysis was driven by employees with specialist data skill sets. And while it helped to differentiate these insurers from their competitors, there is still opportunity for even more growth.
Thanks to AI, analysis can go to the next level.
Using advanced machine-learning algorithms, companies can start implementing AI as a real-time analysis tool that provides product developers with insights previously hidden away. Even the best (human) data scientist is no match for a computer when it comes to data analysis.
AI is not just about chat bots. It is about taking data sets, interpreting them against specific requirements, and providing the insights needed for solutions catering for a specific customer segment. Pairing this AI analysis with data provided by IOT devices, an insurance company can more accurately understand customer behaviour and potentially identify how additional solutions can be bundled into existing offerings.
Because how much of what IOT does is hidden to the end-user, there is a seamless integration with other insurance value propositions. Once a connected device is installed on a vehicle, the end-user can carry on as normal.
Beyond driving, there are already examples of how IOT can help medical professionals identify heart attack symptoms in people who wear pacemakers and act (and respond) accordingly. Granted, people are concerned about potential privacy and security issues. However, legislation and compliancy drive much of the developments in insurance. Companies therefore need to make sure that how they gather information and analyse it adheres to the law. The financial penalties (and impact on brand reputation) are significant if they fail to do so.
With AI and IOT combining to offer competitive value, insurance companies need to embrace the next-level data analytics it provides for. The alternative will have a negative impact on growth potential and attracting an expanding, more connected, customer pool.