Movement of Policy (5): Termination / Alteration

Note: Please note that the following discussion is only for movement of policy (MOP) of individual life/family takaful products only.

Among the three statistical reporting forms (L6, L7 & L8 for life insurers; FT5, FT6, FT7 for takaful operators), the termination / alteration statistics are considered as the most complicated. As all three forms need to be reconciled (please refer to the above diagram), many people have no choice to put the differences that cannot be reconciled as "Others" (another popular word to be used is "balancing item").

In fact, it is not complicated if you follow the correct approach to do these termination / alteration statistics. If you re-arrange the formulas in the above diagram, you can easily see that actually these statistics intend to explain the changes/movements occur previous month in force policies and new business incepted in current month, by comparing to the current month in force policies.

So, what is the best way to do termination / alteration statistics? I guess you already get the correct answer by now, i.e. comparing current month in force data (DATA 1) to previous month in force data plus current month new business data (DATA 2 + DATA 3) and the differences between DATA 1 and DAT 2 & DATA 3 are the statistics you need:

• Termination: The base plan / riders available in DATA 2 & DATA 3, but NOT available in DATA 1.
• Reinstatement / Addition of new riders: The base plan / riders NOT available in DATA 2 & DATA 3, but available in DATA 1.
• Alteration: The base plan / riders available in both DATA 1 and DATA 2 & DATA 3, but the sum assured, premiums or product code are different in DATA 1 and DATA 2 & DATA 3.

If we would like to split reinstatement and addition of new riders, we may need to have an additional step to check whether the attaching base plan are available in DATA 2 - if yes, we can consider those riders are newly added riders to an existing base plan.

In order to do the above-mentioned comparison, we need to first understand the base plan / rider's unique identification used in our policy admin system - i.e. unique field or combination of fields that differentiate one base plan / rider from others:

• Base Plan: Normally, policy number is the main identification (like "primary key" in MS Access table) that we can use to differentiate one base plan from others. If we have yearly renewable products, we may need to find out whether the system will use the existing policy number upon renewal (Hopefully your system will use the existing policy number, otherwise you will run out of policy number very soon...).
   
• Rider: We may need to use combination of multiple fields to form the unique identification. In one of the system I use previously, each rider has a unique "sequence code" - all riders under attached to a base plan have different sequence code. I used combination of policy number and rider code (e.g. "1234567A" (policy number) + "01" (rider code) for the 1st rider under base plan with policy number 1234567A)

How frequent we should prepare the statistics?
Similar to the in force statistics, termination / alteration statistics are rarely used for production performance or decision making. Hence, if our process is properly automated and it only take little resources & time to prepare the statistics, it will be nice to have the termination / alteration statistics on monthly basis. You may not need to submit the report to the Management if they don't really want to look at the statistics (they already have plenty of reports to go through).

So what's the point we spend so much efforts preparing the termination / alteration statistics? Well, let's think how we can make use of the statistics (the reports will remain as papers if we do not use them). Actually we can use these statistics as "early warning" system in order to trace any unusual trends promptly - we can use these statistics to do some quick calculation to get rough estimates on surrender / lapse rates or claim rates.

It will only be useful to the Management if we derive meaningful conclusions from the statistics.

How should the termination / alteration statistics to be reported?
Internally, I would recommend to list out all types of termination / alteration - please do NOT have a category called "Others" (Only for external reporting like L7 or FT6). Different from the new business statistics and in force statistics, we may not need to report the statistics by product (Otherwise our tables will be very big and difficult to study).

However, it will be useful if we can breakdown by base plan / riders and major product class (as investment-linked products may have different experience from the traditional products). The statistics may not be meaningful if we combine all products together (which we normally call "rojak").

What are the source data?
Apart from the new business data and in force data mentioned above, we need another set of data from our Data Warehouse / MIS for the policy statuses of the policies terminated during current month - so that we are able to identify why a policy is terminated (such as death / TPD / Critical illness, surrender, lapse, maturity / expiry, … - please refer to "Back to Basic - Movement of Policy (MOP)" for detailed discussion).

What is the tool?
Similarly, the first choice I would recommend is FoxPro. So far I have no idea how to use Data Conversion System (DCS) to easily compare 2 different sets of data (i.e. "LEFT OUTER JOIN" in FoxPro).