Often we talk about actuarial practice or software issues. This time, we’re going to talk about the actuarial profession in general. Which, really, is in keeping with this blog’s theme of building better actuaries, because we’re not just striving to create monolithic model-builders with no business sense to speak of.
We just wrapped up participation at the 2020 Society of Actuaries Virtual Annual Meeting, and, frankly, it was a one-of-a-kind experience. This was the first year the meeting was held online, and so there were certainly some growing pains.
As usual, there were education sessions, networking opportunities, and an exhibit hall. We talked to actuaries at all of them. And we learned some lessons, which we’ll pass on to you here. We’ve got 3 primary take-aways about the actuarial profession itself, and then one bonus lesson about technology.
1. Risk management is not easy
Insurance is complicated
For instance, consider something like a long term care policy. In plain English, if you can’t take care of yourself, the insurance company will pay someone else to take care of you.
However it’s not that simple. Under the hood you’ve got a myriad of policy definitions, exposure periods, experience periods, claim periods, benefit amounts, riders, statuses (active, disabled, recovered, etc.), whether benefits are reimbursement or indemnity, and so on.
Fundamentally, there are a lot of moving parts. Many more than some other industries such as bank loans or mortgages.Which leads to many more aspects of those insurance policies that administrators, sales professionals, and actuaries must keep in mind.
Additionally, the alphabet soup of regulations (ASOPs, PBR, LDTI, IFRS, AG 49, etc.) continues to grow, seemingly without end. This forces actuaries to manage risks of policies that are reserved under methods developed in the 1950s alongside those being sold today. It can be overwhelming.
Despite these challenges, actuaries have historically thrived in this environment. They have become an essential piece at the center of the puzzle, like “insurance engineers”. They connect underwriting with IT, administration, claims, sales, investments, and more. Which involves them in many more decisions than the majority of their coworkers.
This product and regulatory complexity has often also led to multi-step convoluted workflows just to get from a raw data set to something like a reasonable output report. There can be extract/transform/load steps, model validation procedures, sign-offs and approvals, or even manually moving data from some output location to a centralized data warehouse or data lake.
Often, actuaries have taken on these responsibilities with less-than-ideal tools or resources. Because, well, they’ve got a job to do, and they’re going to do it. Right?
Data is thin
New line of business? New rider? New exposure to a global pandemic that didn’t exist a year ago?
How do you account for those? How do you get a handle on what’s supposed to happen and what the spread of risks are? There’s never enough data to make a fully reliable prediction, so many actuaries turn to judgment and experience to help guide them.
Whether it’s because an individual company experience isn’t credible, or it vastly differs from industry experience, or there isn’t any industry experience to compare against, actuaries never seem to have enough to make a confident decision
There has been quite a bit of talk recently about how Data Scientists are approaching the domains of analysis and prediction, encroaching on the traditional skill set of actuaries.
But we don’t see this as direct competition at all. Instead, actuaries should be looking to harness the skills of data scientists to understand hidden patterns within the data sets they have. Actuaries can then apply their own domain-specific expertise to product design, policyholder intervention strategies, investment management, and so on.
With all of that, we don’t anticipate data scientists ever fully replacing actuaries. Because there is, and always will be, a need for judgment. Sure, a model can tell you that there’s a 15% chance of ruin in ten years, but it ultimately can’t make the decision whether that chance is more than compensated by the upside potential in the meantime.
Good judgment is essential
Don’t forget, the world is ever-changing.
That’s why humans will always have a seat at the table and judgment will always be required. Because as much as one can build and deploy a model to predict the future, that model is only good as long as it continues to describe the world around it.
When the world changes and the model no longer fits, judgment is needed to interpret the model, change the model, or ignore it entirely.
Typically, weighing those risks and rewards has fallen to actuaries. They are the ones with the deep domain knowledge that has allowed for wise advice and reasoned decision-making. We’ve heard of actuaries being called “the adults in the room”, evaluating pros and cons of the situation so that decisions are made with appropriate care.
A good question might be, why? Why would actuaries be so qualified? Is it simply because we know probability better than the data scientists and programming better than the mathematicians and regulation better than the sales force? We don’t think so.
2. Actuaries are a profession qualified to handle those complicated issues
Far more than simply performing tasks for hire, actuaries take on responsibilities not only to their employer but to a society as a whole.
Many of the decisions actuaries weigh in on have significant potential impacts for people who didn’t make their own choices. Low-quality decisions in these areas could lead to far-reaching negative effects, if made poorly.
Not just anyone can come in and perform those judgment tasks. Nor should they. Similar to asking whether a doctor is qualified to perform a certain type of surgery, we should also recognize that these big-impact decisions need a
In order to discharge those responsibilities at a high level, actuaries start with a solid base of technical skills (see point #1 above).
And in order to become fully qualified, there are further professional standards depending on where you’re practicing. Together this means that actuaries have a high bar to meet in terms of technical skills, data applicability, model integrity, communication of results, and so on.
We develop these skills through the examination and residency processes.
Examination is via the various professional bodies: the Society of Actuaries, Casualty Actuarial Society, the Institute and Faculty of Actuaries, the Institute of Actuaries in India, and the Actuaries Institute (Australia), for starters. Residency is the early-stage on-the-job learning which happens in parallel with the examinations.
This process ensures that actuaries are fully competent to handle the complicated, intense, multi-faceted aspects of insurance systems.
Additionally, actuaries continue to hone and refine their skills through peer-to-peer networking and meetings such as the Annual Meetings and topic-specific events. This is a time to set aside competitive pressures and focus on making the work better. Such knowledge-sharing ensures a constant progression of skills and a perpetual advancement of the profession.
And actuaries value continuous learning. We love to dive in and investigate just about any problem at just about any time. Perhaps it is the examination process that entrenches this attitude, but it seems like actuaries are naturally curious problem-solvers.
While this is a great quality, and so necessary as the world advances, we feel like simply being technical experts with quantitative skills is no longer enough. There are great leaps in qualitative skills that actuaries can and must make in order to enhance their own career opportunities. As well, they must improve in these areas if they hope to continue to find themselves given the opportunity to solve those interesting problems for society.
Which leads us to the third take-away:
Actuaries still need help with qualitative skill-building and risk-taking
Also called “soft skills”, they are indeed very critical
Some of these qualitative skills that actuaries need to enhance are communication, relationship-building, delegation, and recognizing limitations. “But actuaries are good communicators!” you say. “They tell me every single detail of their project, even when I didn’t ask!”
Yeah, that there is the problem. There’s a difference between broadcasting everything in your head and refining a message to the intended audience’s needs.
And, harkening back to the first and second points, actuaries often end up taking on responsibilities they shouldn’t in developing these complicated products and convoluted processes. Which leads to a less-than-ideal solution implemented in a less-effective way, and just gets installed as the “official” end product that future generations have to suffer with.
Instead, we think it now becomes imperative for actuaries to recognize when they’ve met their limit and pass the problem on to others who are more qualified for that specific concern. That could be data scientists (for a decision model), programmers (for a user interface), or investment analysts (for portfolio selection).
And related to the idea of recognizing limits, just getting more and more precise numbers out of a model isn’t good enough. Actuaries need to know how to relate the results of their work in a timely manner to the broader objectives of the company.
Sure, if you tell me a rate is 5.42, and then spend the next two weeks refining it to 5.37, you’ve gotten more precision. How does that really help us when last quarter’s rate was 3.8 and the one before was 1.4? Something’s going on and you just wasted two weeks of valuable problem-solving time.
So actuaries need to take a bigger picture view of the work they are doing and how that work fits into the strategic decisions their employer or the industry is facing. Otherwise, they will find themselves replaceable by algorithms. And that leaves an opening for other professionals (MBAs in finance perhaps?) to take over that strategic decision-making role, perhaps less effectively, using those algorithms.
This isn’t just our opinion
We heard this sentiment multiple times in networking sessions. Here’s a few quotes (slightly paraphrased, ‘cause we may have forgotten to correctly attribute them. [PS – If you remember that you said one of these, and want to claim it, let us know!]
| “We’re a profession that loves the band-aid solution.” |
| “Actuaries have a hard time giving up the problem-solving hat… almost to our detriment.” |
| “Actuaries think they can solve all problems. They’re good at solving them technically but lack in thinking about how to solve them strategically.” |
| “We’re good at jumping at the problem, not so good at scoping the problem.” |
| “As actuaries, we know how to measure risk. Once you measure it, what do you do?” |
Actuarial work of the future looks different than it did even five years ago
Additionally, we think actuaries need to be more service-minded and develop a preference for continuous improvement. Project-based actuarial work, where you do a thing once and assume it’s done, is no longer the way of the world. Software-as-a-service and a cloud-based world, where everything is perpetually updating to the latest version, mean that the environment around you changes fast.
Actuarial work is going to have to adapt.
For example, pricing of insurance policies is going to have to become more continuously dynamic and responsive to ever-changing external forces. Life insurance rates shouldn’t have to be static for years as has been in the past, just because “pricing takes so long”. Pricing cycles will have to get shorter.
Disruptors in these spaces, harnessing the powers of new technology, will soon become the leaders. Those who are still trying to work like it’s 1999 (or the early 1900s, as the case may be – you know who you are) will find themselves significantly behind the curve.
Risk is not a four-letter word
And finally, actuaries need to develop more comfort with risk-taking. We’ve often been told to manage risk, but it seems we as a profession have conflated that into minimize risk. There is upside potential, too. The SOA’s motto is “Risk is Opportunity”, in case you’ve forgotten.
Comfort with risk-taking is neither a quantitative nor qualitative skill, but a mindset. And taking risk is hard because it often involves change.
Frankly, change is hard. It’s much easier to stay in the comfort zone than to risk moving out of it, and potentially exposing yourself to loss or failure.
Yet we know that risks are not static, and that with every downside there is often significant upside along with it.
Ultimately, change is inevitable. Growth is optional. [Heard that from someone! Wish we could remember who it was and attribute it correctly.]
In short, actuaries will need to learn how to become robust business professionals designing and implementing complex financial systems. They may be “insurance engineers” after all, and that would be a great badge of honor.
Bonus take-away: Be careful about promises from untested technologies
At a traditional in-person conference, you engage in spontaneous conversations strolling through the exhibit hall or in the line for the buffet. With this virtual format, many were wondering just how we were going to be able to make those valuable connections.
We were offered opportunities to promote ourselves through our virtual booth. This was promoted as a lead-in to high-quality meetings that may not have otherwise happened. Okay, cool, we can deal with that. We’ll get to meet people when they “visit” our virtual booth, chat them up, and go deeper.
Plus, we were told there would be some AI-supported matchmaking during networking sessions. Even better! We can show some interest in a specific person, and then they won’t be able to avoid us for at least 5 minutes.
In all, the tech seemed promising. However, implementation left many unsatisfied.
In our first networking session, where we were scheduled for 8 conversations of 5 minutes each, we talked to 1 person for 15 seconds, and 1 for 5. The second session, where we were again scheduled for 9 connections, we talked to 3. Better than the first, but still far below expectations.
To the credit of the SOA and the platform vendor, they did begin making changes quickly and adapting the networking format and technology. Day 3 and 4 meetings were executed much better, leaving us with a more positive impression than if nothing had been changed.
Which, unfortunately, happens too often. There’s a defeatism that sometimes comes out when facing adversity: “That’s just the way it is! We can’t do anything about it!”
That’s a load of crap. Here’s a video we’ve come to love as an illustration of the problems with that mindset.
You can always do something about the situation you’re in. As long as you’re continually asking the question “Why is this the way things are?” and adapting when things no longer make sense.
The caution here is not to avoid all new technologies. Far from it! Just be ready to modify and change your approach if that unverified promise from an unproven technology doesn’t quite pan out like you anticipated.
Your response to adverse situations such as this will tell much more about your character (as an actuary) and your mindset than it does about the technology itself or the marketing around that tech.
Change is inevitable. Growth is optional.
Once more, it’s back to optimization of the risks you face, rather than avoidance of them all together. Remember: risks exist. Change is inevitable. How you deal with the situation is the only thing you can control. We leave you with yet another unattributed quote to ponder:
“Whether that relates to hiring, interacting with customers and vendors, or risk evaluation and management, those companies [and actuaries] that rise to the challenge of innovation will come out on top.”
So respond well to adversity, do good work in the in-between times, and we’ll see you at the next one.