Corporate Actuarial
Understand claims development, estimate reserves, and explain portfolio results.

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Montréal · Toronto · Calgary · Québec · Laval · St-Hyacinthe
Grouped by team and career level. These illustrative teams do not imply reporting relationships.
Understand claims development, estimate reserves, and explain portfolio results.
Build rating models and turn personal auto and property experience into pricing decisions.
Work with underwriting partners on commercial portfolios and pricing strategy.

Toronto, ON · Montréal, QC
Understand claims development, estimate reserves, and explain portfolio results.
Fictional teams, people and positions · Homepage demonstration.
Director, Corporate Actuarial
Toronto, ON
Fictional exampleManager, Actuarial
Toronto, ON
Fictional exampleSenior Actuarial Analyst
Toronto, ON
Fictional exampleSenior Actuarial Analyst
Toronto, ON
Fictional exampleActuarial Analyst
Toronto, ON
Fictional exampleActuarial Analyst
Toronto, ON
Fictional exampleActuarial opportunities. The teams behind them. A clearer path forward.
First seen Sep 28 · Open
Practice area and career level are ActNet classifications. Team affiliation is only shown when supported by a public source.
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Share plan & other savings: up to 12% of salary or even more (ask how you could earn guaranteed income for life)
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10%
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We’re on the lookout for new talent for our growing teams. We’re currently seeking Senior Actuarial Analysts!
#LI-Hybrid
Il s'agit d'un nouveau rôle au sein de notre équipe en pleine croissance | This role is a new member of our growing team.
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One question. A clearer understanding.
Explore StudyActNet official study guides with original worked examples.Probability concepts, original examples and study guides.
Common mistakes arise from modelling the wrong count or waiting time. Define what is counted, the observation window and any conditioning. A distribution name should follow those choices, rather than the appearance of a familiar keyword.
In a toy homogeneous Poisson process with rate 2 per hour, N(3) has mean 6. The wait until the first event has exponential rate 2 and mean .5 hour. The wait until the third event has a different distribution and mean 1.5 hours.
Write three different questions about the same process: a count in a fixed window, no event before a time, and the third arrival time. Check that each answer’s units match the variable. Do not use these assumptions for changing-rate processes without adjustment.
ActNet editorial guide · October 1, 2026 · Original illustrative examples.
Editorial guide · Oct 1
Common mistakes arise from modelling the wrong count or waiting time. Define what is counted, the observation window and any conditioning. A distribution name should follow those choices, rather than the appearance of a familiar keyword.
In a toy homogeneous Poisson process with rate 2 per hour, N(3) has mean 6. The wait until the first event has exponential rate 2 and mean .5 hour. The wait until the third event has a different distribution and mean 1.5 hours.
Write three different questions about the same process: a count in a fixed window, no event before a time, and the third arrival time. Check that each answer’s units match the variable. Do not use these assumptions for changing-rate processes without adjustment.
ActNet editorial guide · October 1, 2026 · Original illustrative examples.
A little perspective goes a long way.
Explore The CommunityActNet official sharing posts about actuarial work.Career questions, actuarial conversations, and people who get it.
A rate indication estimates the change needed for a defined portfolio under selected assumptions. It is not automatically the increase customers receive.
A reproducible indication workbook or pipeline typically connects:
Suppose projected loss and loss-adjustment expense is 76 per exposure, current premium is 100, variable expenses are 25% of premium, and the selected margin is 5%. With no fixed expense in this toy model, required premium is 76 ÷ (1 − .25 − .05) = 108.57: an 8.57% indication.
That result does not by itself answer whether to implement 8.57%. Product teams still consider regulatory requirements, changes by segment, distribution, retention and effective dates. An implementation can differ from the indication; the decision and its expected consequences should be documented.
Refreshing data, validating trends and explaining actual-versus-expected results is recurring work. Replacing the indication methodology or redesigning the rating plan is a project with testing, review and implementation dependencies.
ActNet editorial guide · October 1, 2026 · Original illustrative examples.
An unexpected age-to-age factor is a signal to investigate, not a complete explanation. Start with the data and the claims process.
Show paid, incurred, case outstanding, claim counts and average claim amounts. Compare results with and without separately identified large claims. Document whether recoveries and allocated expenses are treated consistently. Reconcile the same valuation date across all exhibits.
Imagine incurred development accelerates while paid development barely changes. A change in case-reserve practice is one possible explanation; faster payment is another hypothesis that the paid data can challenge. Talk to claims colleagues rather than forcing both triangles to tell the same story.
If recent factors are distorted, alternatives may include different averaging windows, segmentation or a method less dependent on immature experience. Record what changed, the reason, the impact on ultimate losses and what future observation would invalidate the selection.
The deliverable is not just a factor table. It is a reviewable chain from data issue to assumption to financial effect, with remaining uncertainty made explicit.
ActNet editorial guide · October 1, 2026 · Original illustrative examples.
The company label tells you less than the flow of premium, claims and decision authority. Start with who issues the policy and bears the insured loss.
“Who uses this analysis, and what decision does it change?” is more informative than asking whether the role involves modelling. A pricing analyst at a carrier might maintain a production rating plan; a consulting analyst might build a model and hand over documentation. Neither description alone establishes the proportion of routine work.
These are operating-model distinctions, not a claim about any named employer’s internal teams. Licensing, delegated authority and risk ownership must be checked for the specific legal entity.
ActNet editorial guide · October 1, 2026 · Original illustrative examples.
Editorial guide · Oct 1
A rate indication estimates the change needed for a defined portfolio under selected assumptions. It is not automatically the increase customers receive.
A reproducible indication workbook or pipeline typically connects:
Suppose projected loss and loss-adjustment expense is 76 per exposure, current premium is 100, variable expenses are 25% of premium, and the selected margin is 5%. With no fixed expense in this toy model, required premium is 76 ÷ (1 − .25 − .05) = 108.57: an 8.57% indication.
That result does not by itself answer whether to implement 8.57%. Product teams still consider regulatory requirements, changes by segment, distribution, retention and effective dates. An implementation can differ from the indication; the decision and its expected consequences should be documented.
Refreshing data, validating trends and explaining actual-versus-expected results is recurring work. Replacing the indication methodology or redesigning the rating plan is a project with testing, review and implementation dependencies.
ActNet editorial guide · October 1, 2026 · Original illustrative examples.
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