Detecting Changes in Development Patterns

For actuaries performing a reserve analysis, change is the enemy. It’s an oft-repeated actuarial mantra: “I don’t care how Claims sets case reserves, as long as they keep doing it the same way.”

In reality, changes in development are actually more the rule than they are the exception; it’s impossible to find a book of business having perfectly stable loss development over a 10-year time span. We expect to find changes in loss development.

So, the reserving actuary is always looking out for change. But even with advance warning of changes in Claim’s process, or mix shifts on the exposure side, or a sudden jump in claim severities — it’s very difficult to quantify how much change in to expect in the loss development patterns.

Even worse, it’s hard to see direct evidence of changes in development patterns, until they’re deep in your history. And if it’s deep in your history, you’ve been using the wrong development assumptions in your predictions for the past 4-8 analysis periods.

Wait – Is Development Actually Changing?

Here’s the thought process of a reserving actuary over a hypothetical four quarters of reserve studies:

  • 1st qtr – “That’s an odd development factor, but it’s only one data point. I can safely ignore that.”
  • 2nd qtr – “There it is again… is there something actually there? Probably not, because odds are, we’re going to have two consecutive outliers every so often.”
  • 3rd qtr – “OK, it’s back to normal. I knew I shouldn’t worry about it.” (in reality, *this* is the outlier from the new pattern)
  • 4th qtr – “It’s back! there must be something here, let’s figure it out.”

How much of the triangle needs to exhibit a changing pattern before the analyst recognizes and reacts to the change?

All of this arises because the process of picking Loss Development Factors (LDFs) is one of observing the aggregate, and trying to make sense of what’s happening at the individual claim level. We may have good evidence that indicated LDFs are increasing at 12 months, but we don’t know why, or even what that should mean for or our estimates of ultimate. Our only evidence is the aggregate pattern itself.

LDFs Should Be Outputs, Not Inputs

Instead of looking at the development factors to attempt to understand what’s going on with the underlying claims, what if we look at what is happening to the underlying claims, and use that to predict what will happen to aggregate development?

This is a fundamental shift in the way the “loss development factor” is seen and used. Instead of being the most important initial assumption in the analysis, it becomes one of the last outputs from an analysis. In other words, the LDFs become a product of the analysis, rather than a key assumption and input to the analysis.

This is one of the key strategies (and benefits) of claims modeling using CLCM vs. triangle-based reserving methods. Because CLCM moves LDF indications to the end of the analysis, the Claim Life Cycle Model approach allows the analyst to recognize changes in development much earlier.

(In my last post, I gave an overview of the Claim Life Cycle Model (CLCM) approach. If CLCM is new to you, you may want to read that post for background and context.)

Triangle methods require an initial assumption as to how claims will develop in the aggregate, then apply that same assumption to every claim in the analysis. CLCM methods focus on studying the life cycle of each claim, at the claim level, to uncover what drives claim behaviors like report lag, payment pattern, and closure rates. CLCM focuses on discovering the exposure and claim characteristics that best predict individual claim behaviors.

An Answer to Why LDFs Are Changing

The end result is not just an aggregate reserve analysis, but a reserve analysis at the claim level – and at any level of detail in between. The analyst can not only produce a set of LDFs for each segment of the book, but can explain WHY the LDFs for Segment 1 differ from Segment 2, because the variables that impact development have been identified and quantified.

Additionally, the indicated LDFs for each segment will now be in balance with the aggregate LDF at the book level; it doesn’t matter how split up the book, you can get consistent reserve estimates when you add up the segments.

If you’re an actuary about to start a pricing, reserving, or claims modeling project, you should absolutely look into CLCM as one of your core strategies. Compared to more traditional approaches, the benefits and capabilities CLCM provides are transformational.

Want to accelerate your implementation of CLCM? Actuaries at Gross Consulting are now helping carriers stand up a multi-line CLCM process in three months or less using our Comprehensive Insurance Review (CIR) engagement. Please reach out to me with comments or questions at bret.shroyer@cgconsult.com

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