Technology is already shaping the future of insurance from autonomous vehicles and advanced driver assistance systems (ADAS), to inter-connected homes, artificial intelligence (AI) and machine learning.
One of the biggest challenges the insurance industry faces is adapting to this brave new world and maximising the opportunities that the new technology creates. Established insurers face a huge threat from agile start-ups able to better harness the new technologies. Some of the new ‘tech’ may or may not live up to the billing and some will be certain to drive rapid change. Data and analytics, what we collect and how we extract value from the data, is one area already in motion.
The big data challenge
Big data technologies and analytics are making it easier for organisations to capture large datasets but many still struggle to generate meaningful insights from the vast amount of data. The challenge is to convert the data into meaningful information and then connect it with and across datasets in a way that enables enrichment and deep insight.
Deep risk insights
In terms of risk management, where insurers are seeing the real value is using data and analytics to gain a deeper insight which allows for better, more profitable decision making. Using artificial intelligence and machine learning, patterns and trends can be identified that would otherwise have stayed hidden. Technologies around data have emerged to handle the exponentially growing volumes, improve velocity to support real-time analytics, and integrate a greater variety of internal and external data. Twenty years ago, many insurers couldn’t even rate a risk by postcode, particularly those distributing through brokers, due to legacy systems and IT restrictions. Now, pricing can be based on data relating to the specific individual in real time. Personalised pricing has allowed insurers to be more targeted in the selection of customers, to proactively cross and up-sell and to target opportunities in new segments or markets with confidence.
Why the hype surrounding AI?
Machine learning techniques such as neural networks have been around for a long time and were in use in the industry during the 1990’s for predictive analytics, so what’s changed? There are three main factors; firstly, computing power has significantly improved. According to Moore’s law, computing power effectively doubles every couple of years. This means that algorithms are now able to crunch much more data within timescales that were previously out of reach. Secondly, the volume, availability, and granularity of data has also radically improved. Thirdly, the efficiency and capability of the algorithms embedded deep within neural networks have also markedly improved. These three factors combined have resulted in these types of techniques coming more into focus recently for applications within insurance.
Insurers have been using AI technologies to improve their efficiency and speed up internal operations in terms of automating processes for claims and underwriting. AI and neural networks can also be employed to help gain a deeper insight and to differentiate risk in a much more granular way.
Business Insight has developed its own AI platform called ‘Perspective’. It is a neural network that can take large volumes of records across many variables as data feeds before iteratively learning from the data, uncovering hidden patterns and forming an optimal solution. The software can take a vast number of input data points and hundreds of corresponding risk factors per case before constructing a more accurate estimate of risk and offering significant improvements in predictive accuracy compared to statistical data models.
Changing customer needs
Behavioural analytics and advanced data analysis can also help insurance companies gain a deeper understanding of their customer base for the development of personalised products and solutions.
Millennials, having grown up with smartphones and being used to digital interactions, want the ability to compare products quickly and easily and find value for money at the click of a button. They want the product best suited to them and their lifestyle and these are the things they are looking for from an insurer. This is where data and technology will need to be harnessed effectively by insurers to create products for the next generation of customers. It is this need to adapt and evolve to match customer requirements and buying preferences that has led Aviva to recently launch their ‘Ask it Never’ initiative. Aimed at Millennials, the idea is to eliminate the need for applicants to have to spend time answering lengthy questionnaires by pre-populating the fields using big data to streamline the application process, saving the customer time and making the service more efficient.
Agility and change need to be embraced by traditional insurers otherwise some may end up going the same way as Kodak, a market leading company that resisted change and saw its market share fall off a cliff when digital photography came along.