S04 · messy data simulation

Claims fell 75% - or did the labels just not arrive yet?

People, data and outputs in this scenario are simulated. Each stage is recorded when you commit; the reveal comes after.

5stages
35 minabout
0stages committed

The brief

A motor insurer (simulated) prices policies with a claim-frequency model. Claims are reported after the accident, sometimes months later. A telematics discount was launched on 2024-05-01. On 2024-07-01, the product lead (simulated) shares this dashboard (simulated data):

Accident month (2024)	Claims per 1,000 policy-months, as of 2024-07-01
January	7.56
February	7.16
March	6.37
April	5.47
May	4.52
June	1.98

Product lead (simulated): "Claim frequency fell from about 7.6 to 2.0. The telematics discount works; let's reprice the whole book next month."

Stage 1 of 5

The dashboard groups claims by accident month (event time) and counts claims reported so far.

What do you check first?

How long claims take to be reported, and whether recent months simply have fewer claims reported yet.Seasonality; summer may have fewer accidents, so check the same months in earlier years before reading anything into the slope.Whether the telematics customers are a self-selected, safer group than the rest of the book.Nothing; the trend is clear.