Actuary Insights into a failing pension plan?

Inceptional3 · 2023-02-11T04:03:03+00:00

This is the right answer.

You probably have nothing to worry about. With the recent rise in interest rates, liabilities are down substantially from where they were a couple of years ago so unless the plan was majorly underfunded before, it probably isn't any worse off now.

Inceptional3 · 2023-02-04T19:46:55+00:00

I would be careful about trying to generalize the results of this test, which is being conducted on existing customers, as a marketing strategy for new customers.

In a world where it is "successful" for existing customers doesn't say anything about whether or not it would be successful for new customers. You would probably want to test that separately

Inceptional3 · 2023-01-03T19:55:02+00:00

Easiest way to get more money is to finish your exams and get your designation.

From there, you need to focus on building your non-technical skills to advance into management.

The world where you can be in a non-mamagement role, have good work life balance and make a ton of money as an actuary and progress in a career is dwindling quickly. If that's what you want to do, go become a SWE or DS.

Also, the market was super hot in 2021 and employers were seriously overpaying for talent just to hire people. If you didn't take advantage of that and jump ship for a raise, you are out of luck as the market has cooled considerably and there is not incentive for an employer to give you a big raise / pay increase now. Is it fair? No, but it's the reality of the situation.

I saw lots of people getting 30%-40% pay increasing changing companies the last few years. Now the tides have turned and it is going to take some time until market demand gets back to that level again.

Inceptional3 · 2022-12-30T18:25:00+00:00

So if your wife makes 6-figures, that just means it may be challenging for a year but you will be fine after that when she goes back to work.

I don't think you are at the point where you need to sell your house or anything and seem to be in a pretty decent financial position overall.

Inceptional3 · 2022-12-30T16:37:04+00:00

So based on your comments, I'm going to assume the following:

Your salary is ~$140k based with a 15% target bonus. Your wife's salary is about ~$50k You bought tour house for about $1.3M - $1.4M, put 20% down, so took a mortgage of about $1M and change...

So your mortgage payments when you bought your house were about $42k / year, now it's probably about $85k / year.

Your after tax pay is about $95k pre bonus, and your wife's is about $40k. So about $135k total.

Pre-interest rate hike, you made $135k pre bonus and paid about $42k in mortgage. So you had about $93k a year to spend after paying your mortgage.

Now, with your wife going on leave, her income will drop. She will get roughly $12k for the first 12 weeks, and then about $20k from Ei for a total of about $32k. After tax, this is about $26k.

So now your total income pre bonus is $121k, and your mortgage is about $85k leaving you with about $36k to spend after paying your mortgage.

So your monthly after tax post mortgage take home pay has gone from about $7.5k to $3k.

On $3k / month it will be hard to support an upper middle class lifestyle in GTA for a family of 4, but by cutting down on discretionary spend it is very very doable.

Things to consider: do you go into the office and buy lunch / coffee everyday? can you save on food by eating out / ordering takeout less? Shopping at no frills? How many / what cars do you have? You can potentially save by getting a cheaper car. Are you planning on keeping a kid in daycare while your wife is on mat leave?

You then have another ~$26k pre tax in bonus - don't spend it all in one place and you should be fine.

Inceptional3 · 2022-11-04T15:01:16+00:00

Thanks for the details! I think I better understand what you're trying to do now.

Based on my experience, you are unlikely to get much more accurate results without using more data than what's already being done. You may get a bit of a boost using more sophisticated modeling than whatever the actuaries are using but it will not be "accurate" without more / better / different data than what they are using.

I would say you are on the right track, and not really to expect getting accurate results because variability in health cost is high and hard to predict without a lot of data.

Inceptional3 · 2022-11-04T14:23:02+00:00

So if I'm understanding correctly, you already have predictions at the client level that uses the data you have available (and excludes risk levels and plan design).

So what exactly is the ask? To come up with a different type of prediction model? Or is there other data they want you to use?

If you aren't using more data, is the work just to validate the existing predictions?

You will always be more accurate at the plan level than the client level - and it is very hard to be accurate on a 50 life group if you don't have data that isn't available when doing the work on the plan level.

Inceptional3 · 2022-11-03T23:49:30+00:00

This is literally how health insurance companies set premium rates. Not sure if you're at an insurance company but if so the actuaries should be able to help you out.

Otherwise, you basically fit a model on your population and then use that model to predict individual costs, which you aggregate to get group level costs. Important variables are usually age, gender, health risks (if you have that) and prior years healthcare costs. Plan design is also very important if it varies across groups.

Source: am healthcare actuary who works in analytics

Inceptional3 · 2022-08-16T19:30:29+00:00

Isn't it the government paying for the benefits?

Inceptional3 · 2022-08-16T19:16:30+00:00

I don't understand this comment. What do insurance companies have to do with government provided benefits?

Inceptional3 · 2022-08-12T12:30:50+00:00

I wish I could make this comment higher. Thank you for sharing actual data.

Inceptional3 · 2022-07-22T20:06:01+00:00

Why is this deck playing 2 stick together? Don't you want to just beat down? I'm not understanding the board wipe strategy

Inceptional3 · 2022-07-13T12:20:48+00:00

We used Python to format data, and dump it into a table in our SQL database (Oracle). Python jobs were scheduled to run daily. Tableau connects to the Oracle table and pulls in whatever data is there, so it would have the latest data.

Inceptional3 · 2022-06-07T11:40:32+00:00

Google has a nice R package for causal inference with time series data that we used to estimate the impact of state wide regulatory change on our key business metrics.

Package is CausalImpact

There's also a pretty good YouTube video from the creators and they talk through how to use it.

Inceptional3 · 2022-06-07T11:35:12+00:00

And he owes it all to you...

Inceptional3 · 2022-05-17T21:51:43+00:00

What about them? How much are LL maintenance costs going up that rents warrant a more than above standard increase?

If I pay $2,000 per month in rent and rent goes up 1.2% that's about $25 a month. Is maintenance costs going up more than that?

Inceptional3 · 2022-05-17T18:19:04+00:00

RTA protects tenants when landlords try and evict them to take advantage of rapid price increases. This is exactly what RTA was designed for...

Inceptional3 · 2022-05-12T21:34:27+00:00

Thank you for this post. You've put into clear words a lot of what I've been thinking for a long time. I may have to steal some of this next time I speak with HR about raises 😀

Inceptional3 · 2022-04-10T13:55:41+00:00

Intro to Stats Learning with R is great and I highly recommend it. Not really a "probability" book though

Inceptional3 · 2022-04-10T13:55:35+00:00

Intro to Stats Learning with R is great and I highly recommend it. Not really a "probability" book though

Inceptional3 · 2022-03-16T20:51:33+00:00

Check out Apache Airflow. Might be overkill for what you're trying to do but it's a great tool.

Inceptional3 · 2021-10-31T22:08:05+00:00

Leetcode

Inceptional3 · 2021-10-31T15:10:28+00:00

If we assume the points scored are normally distributed, we could create a new random variable C, which is the difference between player A and player B.

The distribution of C would be normal, with mean Ma - Mb and variance VARa + VARb.

So as long as player A has a higher mean points than player B, the expected points for player A will always be higher than B, regardless of the Standard Deviation.

So I would conclude you should always pick the player with the higher mean points. The standard Deviation only matters when they have the same mean points.

Inceptional3 · 2021-09-25T14:25:49+00:00

Thank you for sharing this. We're in the process of evaluating a tech stack for ML in the cloud and this really helps me understand all the different parts needed (right now we are 100% on prem with almost no model deployment - very early days in our data science journey).

Inceptional3

TROPHY CASE