Why is MAT able to
predict mortality more accurately than conventional underwriters? Simply
put, the human brain isn't engineered to envision extreme possibilities.
Recent studies of the human mind have demonstrated that people –
including experts – consistently underestimate the likely range of
outcomes, particularly when very large numbers of variables and
permutations must be taken into account. Predictions tend to fall within
a tall, narrow bell curve that misses the possible, even if highly
unlikely, outliers.
In the life insurance world, this natural tendency to define risk too
narrowly is exacerbated by the fact that underwriting has not kept pace
with the progress medical advances and lifestyle changes have made in
increasing average life expectancy. People today are living longer,
healthier lives than ever before. And this trend can only be expected to
accelerate.
The implication is that traditional underwriting will not only tend to
underestimate the full width of the actual risk distribution curve
reflected in a portfolio of policies, but also predict an overly
pessimistic mean value.
By removing the human element from the equation, and basing assessments
on up-to-the-minute research, MAT's mathematical algorithm projects a
risk distribution curve that more closely matches actual mortality. The
diagram below (for illustrative purposes only) highlights the zone of
strategic opportunity inherent in MAT's predictive accuracy.
