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Record W4403913950 · doi:10.55016/ojs/sppp.v17i1.79828

The Captive Insurance Opportunity in Alberta: Drivers of Success in Captive Domiciles

2024· article· en· W4403913950 on OpenAlexaboutno aff
E. A. Johnson, Anne Kleffner

Bibliographic record

VenueThe School of Public Policy Publications · 2024
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicAgriculture and Farm Safety
Canadian institutionsnot available
Fundersnot available
KeywordsBusinessActuarial science

Abstract

fetched live from OpenAlex

The annual economic impact from captive insurance companies in Alberta could range as high as C$139 million, but changes to the province’s current policies are necessary for the industry ideally to grow to 210 captives by 2033, up from the 20 licensed captives as of July 2024. Alberta’s Captive Insurance Companies Act came into force in July 2022, making it the second province after British Columbia to permit captive insurance companies. Diversifying Alberta’s economy and building the province’s financial sector are important parts of the rationale behind Alberta’s captive insurance legislation, but much remains to be done. To determine how Alberta can build on its early success, this paper extracts lessons from studies on captive insurance in Bermuda, Delaware, North and South Carolina, Vermont and Hawaii that measured captives’ economic benefits. Economic impact estimates per captive are as high as C$564,400 annually, demonstrating how a healthy captive market positively impacts a domicile. For example, in 2016, Delaware’s 1,081 captives generated US$360 million in economic activity, US$109 million in labour income and 2,573 jobs. Alberta already has a sound foundation for success. The province’s speed of licensing means companies’ applications are approved within six weeks of being submitted. Alberta allows limited partnerships as a corporate structure for captives as well as the ability for companies to insure risks in other provinces. Being located in Alberta means time and cost savings for captives that can then avoid the expense of offshore travel for setup, board meetings and administration, aided by easy access to the regulator. Allowing for non-resident captive managers has proved attractive to companies from other domiciles, but fine-tuning these and other regulations is key if the industry is to flourish in Alberta. For example, while four of Alberta’s 20 captives have established operations in the province, if Alberta were to require captive managers to be based in the province, this would generate a higher impact from employment and greater economic benefits. To successfully compete with Barbados and Bermuda, Alberta needs to lower its minimum capital requirements for captives — $250,000 for pure captives and $500,000 for association and sophisticated insured captives. The Alberta government should also permit inter-company loans as an acceptable form of capital, as Bermuda and Barbados already do. Alberta needs to expand its policy of not requiring collateral for reinsurance so that Alberta’s captives can access the Bermuda and Swiss reinsurance markets, which account for 27 per cent of the global property and casualty reinsurance industry. Successful domiciles for captive insurance also allow for protected cell captives (PCC), which attract smaller entities because their operating costs can be up to 50 per cent lower than pure single-parent captives and the cells can be set up in days. The domiciles examined in this paper also have no insurance premium tax (IPT), engage with regulators and the industry via trade associations and hire experienced captive regulators — something it could take years for Alberta to achieve unless managers are recruited from elsewhere. Alberta needs PCC legislation targeted at captive insurers, while examining the feasibility of creating an annual dollar IPT maximum and lowering IPT rates for captives. The province ought to also encourage the creation of an industry association whose members would engage with government on legislation and hire senior regulators to bring their expertise to the province. By learning from the experiences of other domiciles and implementing their best practices, Alberta can quickly begin benefiting economically from the growth and vitality of the captive insurance industry.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.004
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.078
Threshold uncertainty score0.156

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.002
Science and technology studies0.0060.004
Scholarly communication0.0050.001
Open science0.0010.003
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0050.001

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.031
GPT teacher head0.269
Teacher spread0.238 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations0
Published2024
Admission routes1
Has abstractyes

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