There are different ways to aggregate loss data. You can discover lots of interesting information about your dataset just by looking at it differently. Every claim should have information on:
- Accident date – The date of loss, when the accident occurs. For chronic illnesses or other losses that occur over time, the discovery date is typically used
- Report date – The date the claim gets reported to the claims administrator.
- Paid date – The date of the transaction. This probably won’t be shown to you as there could be many transactions, or it may show the latest transaction date. Only needed for grouping by calendar year.
- Policy Year dates – The beginning and end dates of the policy year associated with the claim. This may not always be in the loss data but you should know it.
You can now group claims together by calendar years, report years, accident years, or policy years. Each have special purposes and characteristics. An example will be shown below.
Calendar Year – This is for accounting purposes. You group the claims’ transaction dates by actual calendar year or their fiscal year. No development, because transactions are logged into the system as they’re created. In other words, you can’t make a transaction in the past or the future, so what’s known is known. This can contain info from all previous policy years.
Report Year – This only helps estimate IBNER (Incurred But Not Enough Reported), but not pure IBNR. Group claims by the date they are reported. Little development, because of reporting lag and internal back up processing claims. Most medical claims are usually reported within a few months, so their reserving practices focus on report lags within 24 months.
Accident Year – This is used to create loss development factors. Group claims by their date of loss. More development here as opposed to report year, because now you can have claims that get reported very late and are associated with that very old accident year. Using report year, that claim will just be added to the current reporting year, not a previous one.
Policy Year – This is used to make actuarial projections to assist in projecting liabilities for the upcoming policy year. If you’re going on a “per occurrence” basis, you use the loss date. If you go by a “claims made” basis, you use the report date. Then you group the losses by the policy years’ start and end dates. This has the most opportunity for development, especially for policies with long tails.
Development refers to changes over time to the loss amounts, either because of new transactions, changes to reserves, and/or new claims. The way you group the claims will have different development rates due to the way claims come in. When the claims are fully developed and closed out, those years are at ultimate.
Let’s look at an example with 4 claims and policy years starting on 6/1. Note that Claim 1 has an additional payment on 4/1/2017. See if you can calculate and get the same results!
| Claim Number | Loss Date | Report Date | Paid Date | Paid Amount |
| 1 | 7/1/2014 | 10/1/2014 | 11/1/2014 | 100 |
| 2 | 4/1/2015 | 7/1/2015 | 8/1/2015 | 200 |
| 3 | 7/1/2015 | 12/1/2015 | 1/1/2016 | 300 |
| 4 | 10/1/2016 | 1/1/2017 | 2/1/2017 | 400 |
| 1 | 7/1/2014 | 10/1/2014 | 4/1/2017 | 500 |
Grouped by Calendar Year, valued as of 12/31/15, 12/31/16, and 12/31/17.
| Calendar Year | 12/31/2015 | 12/31/2016 | 12/31/2017 |
| 1/1/2014 | 100 | 100 | 100 |
| 1/1/2015 | 200 | 200 | 200 |
| 1/1/2016 | 300 | 300 | |
| 1/1/2017 | 900 |
Grouped by Report Year, valued as of 12/31/15, 12/31/16, and 12/31/17. Note the development is a result of IBNER.
| Report Year | 12/31/2015 | 12/31/2016 | 12/31/2017 |
| 1/1/2014 | 100 | 100 | 600 |
| 1/1/2015 | 200 | 500 | 500 |
| 1/1/2016 | |||
| 1/1/2017 | 400 |
Grouped by Accident Year, valued as of 12/31/15, 12/31/16, and 12/31/17.
| Accident Year | 12/31/2015 | 12/31/2016 | 12/31/2017 |
| 1/1/2014 | 100 | 100 | 600 |
| 1/1/2015 | 200 | 500 | 500 |
| 1/1/2016 | 400 | ||
| 1/1/2017 |
Grouped by Policy Year, valued as of 12/31/15, 12/31/16, and 12/31/17.
| Policy Year | 12/31/2015 | 12/31/2016 | 12/31/2017 |
| 6/1/2014 | 300 | 300 | 800 |
| 6/1/2015 | 300 | 300 | |
| 6/1/2016 | 400 | ||
| 6/1/2017 |
Were you able to get the same answers? In another article we will look at how to observe trends, and the appropriate methods used to address them.
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