If the Covid-19 pandemic taught us anything, it’s that the world is changing at break-neck speed. Digitalisation is rapidly changing all industries, including the insurance industry. In 2021 McKinsey already predicted that the non-life industry by 2030 will be dictated by interconnected data from multiple sources, and user-based insurance solutions enabled by artificial intelligence (AI) and customer profiling.
Whereas replacing the traditional underwriter in their current role is highly unlikely in the medium term, most analysts make it clear that insurers who do not embrace capabilities provided by machine learning (ML) and artificial intelligence (AI) will likely lose relevance in the future.
Change is already afoot
Insurers are already using digital tools, including those with ML capabilities, across various applications. Chatbots and service-enabling bots, along with rating capabilities that utilise diverse databases, are already extensively utilised. Intelligent underwriting and invoice-settling bots are also prevalent. With the improvement of these learning capabilities, the current challenges experienced with, for example, robotic process automation (RPA), will be ironed out without much human programming or intervention. The true objective is to teach these technologies to do the tedious work like data capturing, to free up the underwriters to focus on more challenging tasks and human interaction.
Ironically, conversational AI will improve customer experience and operational efficiency through appropriate communication without the risk of human error. Once these technologies have matured and been implemented, where does that leave our human talent?
Acquisition and endorsement
Risk profiling and assessment technology, which makes use of numerous databases and customer-specific data collected through interconnected devices, combined with RPA, will enable fast, efficient, and accurate quote preparation, binding, and even queries in real time. We know, however, that what drives personal insurance are often little nuances and exceptions that require human intervention and decision-making. Underwriters must upskill themselves to become portfolio managers, who use this technology to truly engage with brokers and advisors and ensure they have an enhanced customer experience when dealing with the insurer.
Renewals
Automated renewals are certainly nothing new, and many brokers are weary of the algorithms introduced by insurers to ensure that the annual renewal and review process is smooth, and pricing is aligned to the risk introduced to the pool. Making use of wider data sources, like data from IoT devices and geolocation databases, the insurer will have deeper automated insight into the specific risk. This will free up the underwriters dealing with renewal and retention to not only engage with the broker, but also to gain better insight into specific risks and advise appropriate risk mitigation factors. This opens the door for much more meaningful and mutually satisfactory renewal negotiations. These specialist underwriters need to upskill themselves to become risk managers and learn to interpret the data correctly.
Claims
We can all agree that claims fulfilment is the shop window of any insurer. In our experience, many claims-related complaints relate to communication and delays, which are mostly caused by suppliers. Conversational AI, which provides intelligent feedback in the claims value chain will do much to improve customer experience. Similarly, automated, real-time supplier communication and engagement can ensure a much smoother and more cost-effective claims experience.
In South Africa, I’m convinced we are more than a couple of years away from the Australian insurer that manages vehicle claims by gathering crash information from the vehicle’s onboard computer, facilitating self-assessment through photographic upload, allowing driveable vehicles to drive themselves to the nearest approved supplier, and authorising repairs, all in real-time, reducing the time frame from weeks to hours.
If we can implement AI and ML throughout the claims value chain from first notification of loss to settlement, as well as fraud detection and robotic and virtual assessment, what will the claims handler of today do in the future? Like underwriters, claims handlers can move into a true portfolio management role, keeping in mind that claims often trigger a volatile and emotional experience. Once freed from the administrative burden, these handlers can become true liaison officers between the broker, client, suppliers, and underwriters.
RPA and other levels of AI primarily improve staff’s ability to conduct work that only they are capable of, thanks to a reduction in the burden of administrative tasks. These programs are expected to increase efficiency and, therefore, client satisfaction. The training, retraining, and retention of staff will be key to managing the transition.
Holding onto talent
So how do we retain staff in this digital and augmented work environment and how do we ensure that our workplaces are conducive to the new way of working?
I believe this has not and will not change. We need to continue to ensure that we value, recognise, and engage our staff through inclusive leadership. We must foster a sense of belonging and inclusion in an environment of psychological safety while continuing to ensure that our remuneration and reward programmes are fair and aligned to industry standards. Employers need to facilitate the training required for professional development and ensure that their staff remains healthy and diverse.
AI is the future of insurance. Leveraging various tools of AI technology will automate insurance processing from application to claim settlement in real-time with little to no human intervention. Leaders will therefore have the time and means to focus on what is important: staff wellness, customer satisfaction, and broker relationships.