Event: Insurance Data & Analytics 2014
This event organised by Post Magazine was pretty well attended by Insurers and their suppliers. Although the audience was pretty quiet during Q&A sessions after each speaker, there was plenty of time for questions and a good buzz of questions & ideas during the breaks. A good mix of presentations, interviews and panel sessions as well. With apologies to those who my failing memory has overlooked, here are my recollections:
Magnus Boyd a partner at law firm Hill Dickinson shared his thoughts on privacy & trust generally during an interview with our chairwoman. The most striking thing he raised was the impact on companies from the EU’s new General Data Protection Regulation. This will significantly increase the level of fines for breaches and remove the discretion to allow firms longer to declare them. It will also require larger companies to appoint a Data Protection Officer with secure tenure. He could foresee a brisker trade in insurance against data protection breaches for specialist underwriters.
I was presenting on the emerging role of Customer Insight Directors (or CKOs in the USA). Pleasingly it seems my message as to the importance of these roles, leadership, coaching and holistic customer insight complimented other presenters. You can see a part of my message in the previous post on “Breadth of Customer Insight”. A more concerned perspective might be that the majority of presenters still focused on IT, data and analytics as if they hold the answer alone. But some positive conversations in the breaks allayed my fears, at least for a number of the attendees.
Several suppliers shared what they can offer, but two stuck out for me. Visual DNA shared their work on using visual psychographic questionnaires to generate scores which they have shown are predictive of future behaviour. For instance getting customers to unconsciously reveal their risk taking appetite or conscientiousness. It was interested to see how they are using this and the volume of scores already collected. However, I do feel use of this data to drive differential pricing or cover will prompt future questions from the FCA or ICO, given the lack of transparency for the customer as to what they are revealing and for what purpose. What was encouraging was to see at least one of the suppliers engaging with the predictive power of attitudinal as well as behavioural data (i.e. research + analytics).
The other interesting company was Esri. Ostensibly a GIS and mapping data provider, I was unaware of their scale, private ownership and amount reinvested in R&D (very much like the SAS model). What was even more pleasing was to hear of their work with the UN and what a key role Esri plays in helping early on during natural disasters around the world. Providing the UN and NGOs with up to date maps for their work is a key need that does not get much media attention. So it seems that Jack Dangermond has not only built a very successful global privately owned data & analytics business, but one with CSR in its DNA. Good to see.
I was also encouraged by the final presentation from Ian Hood of RSA. He is responsible for RSA’s digital capability, keeping that up-to-date, meeting customer expectations and implementing into an omni-channel world. My encouragement came, once again, from how Ian is using attitudinal as well as behavioural data. Research was used and valued (including the valuable technique of eye tracking studies) to compliment the behavioural data on digital usage and robust “AB testing”, i.e. properly constructed database marketing to test the hypotheses reached from converging research & analysis. Right on my wavelength. It is interesting that I quite often find that this thinking and approach is more prevalent amongst digital teams in corporates, but sadly often because they are run as more independent silos from the main organisation.
So, overall a good event (and like all such events you get out what you put in). I would just like to see the brief for future such events deliberately extended to cover all of customer insight so more sharing and learning can happen across the boundaries that too often exist between data scientists and researchers.