The question of which would come first in the triad of 'vision, data and strategy' was decisively answered by Mr Vincent Shi, Managing Director of ScorGlobal Distribution Solutions Asia. "Data should never come first, that's a given," he said, explaining that otherwise, businesses run the risk of letting a specific few data points determine their strategy, while ignoring or missing out on other relevant data points.
“Always ask the business question first. What is my plan, or what is preventing me from achieving my plan? The answer to that is probably where your data project comes in,” he said, while speaking at the 3rd Asia Conference on Big Data and Analytics for Insurance.
Mr Bill Lee, Managing Director of Azendian Solutions, describes the issue as the difference between strategy and tactics. “At the strategic level, we can never let data tell us what to do. But on a tactical level, data can point us in the right direction. Data can tell us how to focus and understand our customer better.”
A straw poll by Dr Ladina Caviezel, Analytics Consultant, Group Digital & Information Services at Swiss Re also showed the majority of the 100-odd delegates at the conference saw modern technologies as enablers and partners of their business. “Combining the risk knowledge in the insurance industry and state-of-the-art data science, we can generate new insights, enable productivity and create digital business,” she said. Data science, in this case, includes text analytics, machine learning, visual analytics and predictive modelling.
Speaking on the possible moral hazard of determining whether a potential customer is a smoker or not (as an example of a factor that would affect premium prices), she added that even the best data science model or medical test cannot be 100% accurate, as they are a simplification of reality. "So the threshold decision between the sensitivity(true positive) or specificity (true negative) of the model is not purely a scientific decision but also a business one," she said.
Mr Shi also described the ways big data analytics could be an enabler for developing new insurance products and strategies, utilising computing power and AI to create usage-based and parametric products to deal with oft-ignored customer pain points. He used China as an example, where ride-hailing and travel apps have parametric and usage-based insurance available as riders, paying out claims in the event of a traffic jam or flight delay. These apps use vast amounts of historic and real-time weather data, combined with travel distance and the start and end points of the journey to determine premium and payout instantaneously.
The two-day conference, sponsored by ReMark, is organised by Asia Insurance Review and ends today.