Risk & Analytics

Big Data and the Devil’s Advocate

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I had the pleasure of presenting last night to a group at the Chartered Institute of IT in London, on the topic of big data and analytics, illustrated in part by case studies from the insurance sector. Cognitive computing, Internet of Things and Cyber Security all found a part in the presentation, amongst other elements. My challenge to the assembled group was that not only was the industry changing, but so was the IT profession.
It was an interesting event for many reasons, not least the lively question and answer session which followed. Of course there was discussion about skills, tooling, implementation – but we also found ourselves talking about the ethics of big data. Of course, we know from multiple proof points that organisations which adopt analytics appear to be more successful in terms of performance, revenue, risk and customer management. But is there a price for progress?
By way of example, in the insurance environment, future healthcare models will invariably emerge which combine behaviour, location, profession, family history, perhaps our social media interactions and maybe one day our genetic build up. All this information will allow insurers to underwrite more accurately of course, but some citizens may become uninsurable, or policies may become unaffordable. Is that in the public interest? Does it matter?
Let me introduce you to the Devil’s Advocate. It’s a term used for someone who takes a deliberately contrary view, not because they necessarily believe it, but for the purpose of taking the debate further. It has its origins in the Catholic Church to challenge the validity of an individual to become a saint, by trying to uncover character flaws or misrepresentations.


Where is the Devil’s Advocate in the Big Data discussion for insurance? Don’t we invariably view the world through our own personal lens, either from an industry or technology viewpoint, and doesn’t this create a distortion or bias in our thinking in some way?
Of course, we aren’t likely to put the Big Data genie back in the bottle. We’ve reached the tipping point – and beyond. But in taking a different view, would we change the way we implement change, or explain what is happening to our stakeholders, such as the general public, and perhaps spend more time on the ethical issues which attach to our industry transformation?

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