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Case Study: Collect data to meet needs

The problem:

A meeting with a new client has identified a number of protection requirements that need addressing. He has been disillusioned in the past after applying online direct to a life company without advice because the ultimate premium offered was significantly higher than the initial premium quoted. As a result of this , he is sceptical about the accuracy of any recommended solutions.

Issues to look out for:

  • The importance of managing the client’s expectations from outset to avoid them being put off by terms they were not expecting. Likely loaded premiums or imposed terms need to be discussed and understood as part of the recommendation.
  • Avoid the temptation to complete multiple applications with a view to selecting the best offer.
  • Adopt an efficient process to identify potential counter offers before advice being given.

The solution

Very rarely should there be a need to submit multiple applications, or multi-app. This process creates more work for the adviser, the IFA firm and the client due to the need for additional form-filling, illustrations, application submissions and chasing medical reports and other such joys of the protection pipeline.

Even at the end of this process, the outcomes may be identical. Furthermore, the client will still not have had their expectations managed.

Instead, broad health and occupational data should be gathered at the same time as protection needs are being identified and agreed with the client.

During the research process, once a short list of, say, three potential providers have been selected, their underwriting departments can be emailed with the (anonymous) summary of the client’s health situation along with a request for potential outcomes.

As a result of this process, the recommended protection solutions are going to be as accurate as possible in terms of expected premiums and counter terms, subject to full underwriting.

The process also lends itself very well to a frank discussion with the client about the importance of full medical disclosure. In fact, it is prudent to adopt this process for all protection cases.

Consequently, there are fewer surprises for the adviser, the client’s expectations have been well managed, there will be greater sales conversions and there is no need to multi-app.

Additionally, the adviser and the firm can build a valuable library which identifies which companies are more sympathetic to certain health conditions and those which are seemingly cherry-picking the cleaner lives.

It is also a good gauge of the provider’s service levels.

The broad data worth collecting would include:

  • Date of birth, gender and tobacco usage in last 12 months.
  • Height, weight and waist measurement.
  • Occupation: short description of duties, percentage of manual work (lifting, carrying, working with machinery and tools), heights worked and frequency, annual business mileage.
  • Medical condition(s): date of initial occurrence, date of last symptom, current medication/treatment, past medication/treatment, ongoing symptoms, historic and future tests/investigations/referrals / hospitalisation/operations, work absence, whether fully recovered.
  • Family history: whether any parents, brothers or sisters (before age 65) died or suffered from: heart disease, stroke, kidney disease, cancer (including site and type), MS, diabetes, Huntington’s disease, motor neurone disease, Alzheimer’s, Parkinson’s or any other hereditary disorder.

Many insurance companies are happy to accommodate this approach. Aegon, for example, has a template to help advisers available on its website.

Peter Chadborn is director and adviser at Plan Money

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