The Value of Actual Versus Technical Pricing


When monitoring the price adequacy of a portfolio over time we tend to focus on renewal rate change; how much more or less we charge for accounts staying on the books. It makes sense and is readily calculable. We adjust for any underlying changes in exposure, coverage, limits, or deductibles at the policy level and calculate a risk-adjusted rate change for each policy renewed that year. Risk-adjusted rate change gives us a sense of whether pricing changes are improving or deteriorating the expected ultimate loss ratio (ULR). If the risk-adjusted rate change is greater than the loss cost trend, we expect improvement in the ultimate loss ratio. If the risk-adjusted rate change is less, we expect deterioration in the ultimate loss ratio.

Getting long-term portfolio pricing right

Unfortunately, this misses the whole picture in understanding the price adequacy of a portfolio over time. Each year, some policies are renewed, some policies are churned (no longer written) and new business is written. Using only renewal rate change critically misses the rate level impact of policies dropping off the book, as well as new business written. If a portfolio is growing significantly, or changing its composition, the impact of churned and new business can be just as important to the overall rate adequacy of the portfolio as renewal rate change.

Managing the monitoring and measures

How do we monitor the rate adequacy of new and non-renewed or lost business? This is where Actual versus Technical (AvT) pricing comes in, sometimes called “Bound to Benchmark” or “Bound to Manual” pricing. This is a measure of what was actually charged for a policy versus the mechanical price that comes out of a rating algorithm prior to any judgmental credits or Debits. Comparing the AvT of the churned or new policies to the AvT of the renewal business, we get a sense for whether the business lost and added is priced stronger or weaker than the renewal policies.

The limits of AvT

Technical pricing is never perfect. There are often risk factors that impact expected loss not accounted for or situations where the technical pricing across various segments is more or less adequate. AvT relies on the law of averages: these true deviations average out and comparing AvT across groups of policies gives us a good indication of relative price strength. If that assumption does not hold, the relative price strength of two portfolios indicated by comparing AvT could be misleading. This generally happens when there are materially different distributions of risks in the portfolios across which AvT is being compared. Such a shift could result from product expansions, changes in underwriting appetite, changes in distribution and more.

The winning formula

There are several ways in which data can be reported so that AvT based metrics can be calculated. These include:

  1. Technical price in dollars is reported. We can then divide the bound premium by the technical price to get AvT.
  2. Rating factors needed to produce technical pricing are provided. With all the rating factors, we can calculate the technical price and then divide the bound premium by the calculated technical price to get AvT.
  3. Individual risk premium modification (IRPM) factors, also referred to as underwriting and schedule modification factors, are reported. If the judgmental modifications that take the technical pricing and produce the bound price are provided, we can back into the technical pricing. AvT equals the modification factors plus one. E.g. an IRPM of 20% translates to an AvT of 1.20.

In summary, the AvT metric allows us to get a more holistic view of price adequacy over time by incorporating the impacts of new and churned business. Without AvT, it is difficult to get a complete view on how changes in portfolio composition are impacting the overall profitability of a book of business over time.

Now it’s over to you to share your experience of AvT pricing.

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The Accelerant team can also work with you to capture the data needed for AvT based analytics.