The Data Space

Input data shared by every by-policy projection.

The three input CSVs are read here, once per model, and referenced from Projection as data. Projection is parameterized by point_id, so each Projection[N] is a separate ItemSpace with its own cells cache; if the readers lived there, every model point would re-read every file. Holding them in an unparameterized Space reads each file once no matter how many policies are projected.

Inputs are external files: plain CSVs in the model folder’s parent directory, products/whole_of_life/, rather than data stored inside the model. The model folder therefore holds nothing but formulas — no _data/, no IOSpec, no embedded values — so a diff of the model shows logic changes only. This follows annuallife.TradLife_A; contrast basiclife.BasicTerm_S, which keeps its inputs inside the model through modelx’s IOSpec machinery.

The consequence worth knowing: the model is not portable on its own. Copying the WOL_UK_S folder without its parent’s CSVs produces a model that reads and then fails on first evaluation.

input_dir() resolves the directory from _model.path.parent at run time, so the model works wherever the repository is checked out. Each table has a filename Reference and a reader Cells:

Reference	Cells	File
model_point_file	model_point_table()	model_point_table.csv
mort_table_file	mort_table()	mort_table.csv
lapse_table_file	lapse_table()	lapse_table.csv

Both the mortality and the lapse table are keyed by the cell as well as by the usual rating factors, because the two cells of this product do not share a basis and must not be given each other’s. The underwritten cell restores select experience through full underwriting and takes an assured-lives shape; the guaranteed-acceptance cell cannot be better than the population and self-selects worse, so it takes a population shape with an anti-selection loading. The FCA’s price differential between the two designs — £71.73 against £8.10 per £1,000 of cover — is the scale of the error a basis mix-up produces.

Cells Descriptions

input_dir()

The directory holding the input CSVs: the model folder’s parent.

Inputs are external files, not data stored inside the model, so the model folder is pure formulas. The path is resolved at run time from where the model was read, following annuallife.TradLife_A.

model_point_table()

The model point table, read from model_point_table.csv.

mort_table()

The annual mortality rates, read from mort_table.csv.

Keyed by basis (population or assured), sex, smoker status and age last birthday, and capped at 1. Both bases are [std] proxies: the population rates are shaped like the ONS national life tables and anchored so that the O50 cell’s loaded rate is the notes’ walk-through basis exactly, and the assured rates are shaped like the “00” Series permanent assurance tables. Neither is a published table, and the file’s provenance column says which cells are anchors and which come from a sex or smoker factor. Sorted on read, because Projection.mort_rate indexes into it.

lapse_table()

The annual lapse rates by cell and policy year, from lapse_table.csv.

The two cells carry different tables: the guaranteed-acceptance one lapses faster early, on affordability attrition. Both are [std] drafting constructions - no public UK whole of life lapse study was retrieved - and on a product with no surrender value they are the single largest lever on the liability.