Cited by 152Insurance and Financial Risk ManagementCustomer churn and segmentationProbability and Risk Models

The value of vehicle telematics data in insurance risk selection processes

Baecke, Philippe, Bocca, Lorenzo·2017·Decision Support Systems

Integrity signals

Registry

Crossref · 10.1016/j.dss.2017.04.009

Cites

Statistics

Recomputing p-values needs the paper’s full text.

Claims the paper makes

We couldn’t retrieve this paper’s full text, so its claims and self-check weren’t run. The registry and citation checks still apply.

Claims other papers make about this one

Each is checked against this paper’s own text: does it say what the citing paper says it does?

  • Including standard telematics variables significantly improves risk assessment of insureds.

    “Recently, it has been proven that including standard telematics variables significantly improves risk assessment of insureds”

    From The Use of Telematics Devices to Improve Automobile Insurance Rates (2019) · cites this paper as Baecke & Bocca, 2017

The citation lists haven’t been fetched yet

References 48 · Cited by 152

Authors
Baecke, P., & Bocca, L.
Affiliations
Vlerick Business School (BE)
Corresponding author
Baecke, Philippe
Venue
Decision Support Systems
Publisher
Elsevier BV
Published
2017-06
Volume
98
Pages
69-79
ISSN
0167-9236 (ISSN-L)
OpenAlex
W2608634440
Cited by
152
References
48
Citations by year
2026: 9 · 2025: 22 · 2024: 19 · 2023: 19 · 2022: 20 · 2021: 23 · 2020: 12 · 2019: 11 · 2018: 14 · 2017: 3
FWCI
19.69
Type
journal article
Language
en
Open access
closed
Locations
Decision Support Systems (publishedVersion)
Topics
  • Social Sciences › Economics, Econometrics and Finance › Economics and Econometrics › Insurance and Financial Risk Management
  • Social Sciences › Business, Management and Accounting › Marketing › Customer churn and segmentation
  • Social Sciences › Decision Sciences › Management Science and Operations Research › Probability and Risk Models
Keywords
vehicle telematics, usage-based insurance, pay-as-you-drive, insurance risk assessment, Internet of Things, data mining

About these checks

Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.

Statistics and arithmetic are recomputed, not judged.

Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.

What counts as a claim ›How we measure confidence ›How we check this ›

Are you an author, or do you see a problem with this page? Request a review