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How Royal London has rewritten the protection rulebook

A new offering from Royal London re-writes the rule book and sets a new benchmark for the industry.

The term “underwriting” is thought to have originated when Lloyd’s of London introduced the process of name signing under the description of the event or possession being insured.

But while it is one of the most important functions in the financial world, underwriting has for decades remained an archaic and cumbersome process, certainly not in line with today’s consumer expectations.

It had to evolve.

Enter stage left: Royal London’s streamlined mortgage protection offering, which we are proudly piloting.

Using predictive analytic techniques, it replaces the traditional lengthy question set with just three medical and three lifestyle questions. Data collected from the mortgage fact-find is used by the scoring engine to make an instant decision on life cover eligibility, with no medical tests or additional evidence required.

This game-changing approach should not be underestimated. It rewrites the rule book and sets a new benchmark for the industry.

Ian McKenna: Royal London’s protection and mortgage advice ‘game changer’

The differences between the existing underwriting process and this new proposition are profound: a guaranteed price with terms versus a quoted price invariably subject to change, six simple questions instead of 30-plus, and no further evidence required versus a laborious paper chase. The two experiences could not be further apart.

The adviser benefits from an increased confidence in price and process; the consumer likewise, along with a far superior journey. The result? More consumers being protected. Not only will more engage at the front end but less will drop out.

Looking further afield, we see the types and sources of data feeding the analytics engines continuing to evolve. From Alibaba offering loans based on its consumer’s online shopping experience, to Lenddo pioneering the use of social media.

This data (whether that be on social media or gleaned via a wearable device) is generally “unstructured” and difficult to analyse on any scale. As such, it requires machine learning/artificial intelligence to interpret and spot patterns, freeing up underwriters to work on the more complex cases.

Exciting times lay ahead. Indeed, considering some of the leading insuretech start-ups like Lemonade, it appears the world of protection is heading in the right direction at last. Who knows where it will ultimately lead? It is just exciting to be part of the journey.

Mike Aldridge is sales director at London & Country



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