Another LTCI Methodological Quirk

An LTCI filing that includes original assumptions in the Master Exhibit reveals yet another methodological problem in rate adjudication with long-term consequences to policyholders.

This post describes another example of:

Risk Based Horizon Scanning

We use a 1 page Master Exhibit 2017 SERFF-ID MULF-130960272, a 666 page filing covering several books.

The exhibit contains three 3-column sets:

      • Original Pricing Assumptions (OPA) in the 1st 3-column set;
      • The experience / projection before EP(b)(b) the requested rate increase as the 2nd column set; and
      • The experience / projection after EP(a) the requested rate increase as the 3rd column set.

Each 3-column set includes incurred claims, premiums, and loss ratio (claims / premiums) for each year of the 52 year life (1998-2040). The summary includes the lifetime loss ratio (LLR).

OPA is the initial justification for pricing a policy in the beginning of a book’s life. Consider OPA random fiction.

Note the yearly loss ratio (LR) comparisons of OPA vs. either of the two last 3-column sets (EPs). OPA’s LR is always greater except for 2007 – 2008.  Despite this, OPA’s LLR (0.67) is lower than EF(b) (0.92) and EF(a) (0.87). This seems quirky. It would be natural to ask of this riddle…

How Could This Be?

Observe EP premiums & claims are well above OPA starting around 2000. Could the carrier have added books along the way, but continue to use the same OPA? It appears so!

Answer to the riddle: Since EP premiums & claims >> OPA in the weighty years when annual loss ratios exceeds 90% (e.g. years 2005 & beyond), these later years dominate the LLR calculation.

Shouldn’t the industry (carrier, regulators) have known by 2007 that OPA was far off given the wide premium & claim variance between OPA and EP?

What difference does this make?

Refer to the table below. This is the framework used by some regulators to judge how much of an increase is warranted, if any. A comparison is made between actual v. expected loss ratios, the latter from the dated and obsolete OPA!

Year Earned Premium (billions) Incurred Claims (billions) (1) Actual (LLR) (2) Expect (LLR) (1)/(2)
1991-2013 $1.572 $1.259 80.16% 66.53% 1.20
2014 $0.055 $0.109 198.80% 266.66% 0.75
2015 $0.055 $0.116 211.47% 298.71% 0.71
Total $1.682 $1.486 88.33% 71.31% 1.24

Using the invalid expected LR(2) for the stated periods (1991-2013, 2014, 2015) meant the carrier’s rate requests had to meet a secondary test in addition to the primary minimum statutory (MLLF of 0.60), thus causing a delay in rate increases. Such delays exascerbate the well-known Catch Up problem where future increases must make up for lost time. Policyholders presently own this liability though we make the case that they should not.

My guess is that the LTCI industry is not even aware of this problem or its consequences.

Other cases (e.g. AEGB-131679838) use an OPA that has the opposite problem. Here, we see OPA LR(s) consistently under EP LRs and OPA. This means the secondary test would not block rate request increases that would be otherwise blocked.

Rate grants to your policy are sensitive to whatever fictional OPA created over two decades ago.

Final Note (MULF-130960272): We used our app to review OPA and EP key metrics. The Step Down (SDN) for the OPA is 1.16>1.0 since the OPA had an LLR of 0.67 as opposed to the 0.6 MLLR. By contrast, the EP filings have an SDN of 1.73 reflecting a rise in the claims-to-premium ratio compared to OP. The Step Up (SUP) are 12.5 and 14.5, respectively for OPA v. EP. In either case, both books are Catch Up sensitive. Rate increases will continue as they have since the first in 2009, now a total of five. The EP increases were not granted in a timely fashion, due both to a dozing industry and secondary test described above. The current premium  is 2.36x the base aggregate premium (1.0), +26% above the EP SDN (1.73). Policyholders are currently paying a 26% subsidy of their current annual premium to pay for past losses.


Author: Samuel Cuscovitch

Research scientist / strategist.

%d bloggers like this: