Much of the AI discussion to date has been about the risks and rewards that it offers. For example, while there have been high profile stories about the risks of automated vehicle crashes many commentators are predicting long-term impact on the future of motor insurance. Warren Buffet no less believes safer vehicles will see the motor insurance industry reduce by 60% over the next 25 years. When you consider that motor insurance accounts for 40% of the industry, that is a pretty seismic change.
On a broader scale, one recent report by a Swiss think tank for the World Economic Forum predicted that 75m jobs were at risk of being replaced by 2022. On the reward side, the report also forecasts that 122m jobs will be created as a result.
It is set against this backdrop that Ventiv presented at an IRM Special Interest Group event on AI and Machine Learning; How will the Chief Risk Officer drive risk in the machine?
The session covered a review of current trends in artificial intelligence including; examples of AI technology, applications being utilised in business processes, and potential risks and steps to help mitigate them. We looked at how risk managers are using machine learning and AI and showcased the capabilities of IBM Watson Analytics.
Until recently analysing their data and information was a manual job for risk managers and their teams with more advanced analytic capabilities further restricted the insurance markets. This empowerment creates real opportunities to take control and drive decision making. Throw in the AI dynamic and things become even more interesting as there is no longer a need be a data scientist nor statistician to harvest the rewards. With Natural Language Processing (NLP) they don’t even need to know a technical language. All that is really required is the ability to gather the data set inputs.
Risk managers are familiar with collecting data on spreadsheets from multiple sources and locations. However, spreadsheets do not necessarily drive insight, learning and understanding, especially when you cannot see the wood for the trees plus everything is siloed. This is the real game changer where AI can potentially deliver in 3 areas:
From the group discussion a number of AI needs emerged which fell into five areas:
Oct 22, 2018