David Wright: 0:01

My guest today is Jessica Leong, lead data scientist at Zurich and president of the casualty actuarial society. Jessica has a variety of roles and consulting that ensures and near and dear to my heart as a reinsurance broker. Jessica, welcome to the show. Great, David, thank you for having me. Yeah, I'm really excited to be here. First question, you work in a data science these days. And there's a lot of, I don't know, anks to there was at one point of the collision of data scientists and actuaries, and I'm wondering, what is the state of your thinking on what an actuary is today?

Jessica Leong: 0:34

Yeah, great question. We've been giving that a lot of thought at the leadership at the casualty actuarial society. And we have a new envision future that we rolled out just in November of last year. And this is our vision for the actuary and the profession going forward. It's that we are sought after globally for our ability to apply data and analytics to solve insurance and risk management problems. Okay. That is the vision. So it's very broad. And it speaks to, it speaks to this speaks to the space that we play in in a very actionable way. Right? If you look at our old envision future at the casualty actuarial society, it said something about how we were really about advancing the practice and application of actuarial science, which frankly, we thought was very circular. Wasn't a really good way of defining what we do, right? actuaries do actuarial science is not helpful. So we wanted to put out something that was more evergreen, and something that provided some direction, right. So whatever analytics, you need to actually solve the important insurance problems, that's what actors need to be able to do.

David Wright: 1:48

Okay. Now, what's interesting about that, is that that does not exclude other people from doing the business of actuaries. Right? So there's nothing about that which is proprietary to actuaries. You know, you can be a non actuary and living out that definition every day. Tell me about that. Is your attention there? Is there not? does not care? Yeah, good question. And look,

Jessica Leong: 2:14

if I look at my own, my colleagues and my team at Zurich, certainly there are actuaries and also non actuaries on the team, right? And if I look at the non actuaries and the data scientists, so my team, certainly they are also solving insurance problems using data and analytics. So I think there is room for us all. And there's enough. There's so many opportunities, frankly, to solve business problems using data and analytics. That Yeah, I don't think that there is that tension, as you say.

David Wright: 2:50

So if you take if I, as I'm thinking about this problem, or this question, anyway, it's not necessarily a problem. I don't mean to suggest that it has to be a problem. Thinking about the question. There is a very narrow, like legalistic definition of actuary, which is somebody who signs off in financial statements, right? There's a lack of regulatory authority, which is viewed on actuaries that they can do certain things that, you know, regular normies can't do. And so that's like, another possible definition. And then there's another one too, which is kind of related to that, but not in, which is actuaries are people who follow the code of conduct. Right. And essentially, the code of conduct the Code of Conduct doesn't talk about analytics, right? So it's almost as though if you go through the code of conduct, it's like a independent, completely independent definition of actuaries than the one you get, right? So yours is focused on the daily practice of actuary Well, one aspect of it, which is analytically in thinking, and if you you know, if you take the exams, you could be forgiven for thinking that actuaries are analysts every day all day. But if you read the code of conduct, you would have no idea. It would just be people who are just practicing responsible business analytics and being good, you know, communicating well with each other. And there's all this sort of more values oriented things should be read together, right? I mean, did you consider it should be considered the Code of Conduct? Well, how should we consider it in reference to death? defying an actuary?

Jessica Leong: 4:17

Yeah, good question. I think professionalism is a really important aspect of defining what an actuary is absolutely agree with you. especially in this day and age as we're battling through some really important questions in the industry and in our profession around things like race and insurance, right. I think professionalism is super important in that space. Did you I agree that there is also a regulatory aspect of being an actuary as well. And then professionalism plays a very, very big part in that regulatory aspect as well. The actuaries sign off On opinions, right and have an arm's length relationship, in a lot of ways with the business. And I think that's just something that is a dichotomy, I think about the profession that we'll have to work through as we move forward to try to. On one hand, we want to be really innovative and solve business problems using data and analytics. On the other hand, we need to maintain our level of professionalism, and sometimes an arm's length with the business right, as we can work on that aspect.

David Wright: 5:30

Yes. How do we balance the two? defender of the right to consumers of financial statements? Right, who I mean, there, it's a rough go, trying to figure out what the heck's going on inside of insurance company. I mean, especially looking at summary data, the archer is looking at more data than that, who signed up on the statements. And, you know, that's an important part because there's a lot of uncertainty, a huge amount of uncertainty. And one of the things that I like to, I like to believe is that actuaries actually wind up previewing a lot of the data science issues of the day. So if you study the history of actuaries, you study, actually the future of data science. And so one of the things that you'll see there is you see them integrated into business decisions in a deep way, which didn't really happen until fairly recently, where AI is showing up everywhere I work for a group of people who are primarily concerned with AI, and so do you, and so are you. And, and so now the business is just being integrated, right, the current definition that you presented, and then here we come with a lot of questions about values. And you can you can bamboozle people with statistics and with fancy algorithms, and the actuaries come prepackaged with this code of conduct, which governs their behavior on these very issues, and you don't have and the rest of the data science community. So here's the question, should they have one? Should there be a code of conduct for data science practitioners?

Jessica Leong: 7:02

Great question. Look, practically speaking, I think that will be very hard thing to do, right? Just as there is no good definition for a data scientist. And I'm sure you experienced that in your day to day job. You can be a data scientist by taking a four week boot camp, right and call yourself a data scientist. But I think so practically, it's very hard thing to do. But as we see in the news every day with all the ethical issues now that arise out of uses of things like AI. It's a very important topic, I don't think a code of conduct is what's going to help in this particular case.

David Wright: 7:42

So do you think does that make you somewhat of a skeptic of the actual code of conduct? Like, does it then not matter in some way? Or, you know, I tend to the data science data scientists I meet and I work with they're upstanding, ethical, moral people. The actuaries I work with and meet are upstanding moral, ethical people. Right? There's not I wouldn't say there's a difference between them. And that could be just an argument for maybe David writes, selection algorithm of colleagues and co workers and friends is what I need. But it could also be an argument for the actuarial Code of Conduct did not really mattering that much, which is I think we should be allowed to say it right. I mean, it's possible that that is superfluous. Right? It's a statement of fact, rather than intent.

Jessica Leong: 8:31

No, I think I think it matters tremendously. And our professionalism training and our professionalism, continuing education that we have to do every year matters tremendously, as well as disciplinary procedures as well. Right. All of that is alive and active within the actual profession today, and it is tremendously important. I think I didn't mean to say that. Look, I think from a practical point of view will be very hard thing to do on the data science side. Yes, good, in theory, impossible to actually apply in practice, right? There were just so many data scientists, and there was no good definition for them. We do not have that problem in the actuarial profession.

David Wright: 9:12

Now we have a society where the President very capable one I've heard. And, yeah, that is something that binds us together. Because you can also define an actuary. Maybe we just do this whole conversation with defining actuaries Jessica, because I don't I don't understand it. Honestly, I have lots of ideas. I'm not sure I'm thinking straight about it. But you know, we have a professional body. Right? And we haven't talked about exams yet. We're gonna get to exams. There's lots of easy questions for you on exams, I promise. But these are these are like a whole bunch of like, disparate activities, which can all be could all be applied independently. Like you could, in theory, take the exams not be an actuary. You could have beta code 100. That'd be an X ray. You could actually do apply data science and analytical tools to solving insurance conundrums, and not being an actuary, right. And so none of these so they it's like it's the intersection of things I don't know. Is this making sense? What? Should I be confused or should not be confused about this? What is the confusion? The confusion is just that none of it seems to be like complete, right? It always, it all seems to like, you know, we seem to be, like I said, the intersection of these things maybe. But, you know, I definitely it's kind of like one of these things where I know, you know, I know what it means to be part like, I'll tell you, I'll tell you this feeling I had when I first became an actuary, right, so I start going to the conferences, right? And, Jessica, there's a sense of community, like there really is, you show up? And you're, you're it's like, we're part of like, a family or something. And there's a real sense of camaraderie like I was used to as a reinsurance broker or going out going to conferences and like, harassing people, trying to get business off of them, take things from them take their time, so that I can make money, right. And then actuarial conferences is nothing like that, meaning people are trying to produce business. It's like, it's all like, Oh, yeah, definitely. I'll help you. Right. There's there's like, there's a, that really doesn't happen, because there's a different culture. And I don't know, I personally don't know how to capture that culture, because I think it's real. But I don't know where it comes from. You know? What do you think? Do you agree with the premise? Like if there is a culture, right, you're nodding So you, agree with that.

Jessica Leong: 11:14

Absolutely. A third of our members volunteer. It's amazing. Yep.

David Wright: 11:18

Which is, I'm going to assume very, very high for her for any organization. Right? Yeah.

Jessica Leong: 11:24

So yeah, you're right. The the community is a really important aspect of what it is to be an actuary. And if you think about it, and I was saying this to my husband, who's not an actuary, right, like how many, a lot of us still write papers, right? Yeah. I mean, how many, just normal working professionals do that on a day to day basis, right and volunteer for their professional organizations still write papers? So I think that's something to be very proud of. And something we have to make sure that we, we sustain going forward, I think that'll be very hard thing to replicate. If we had to do this all over again, right?

David Wright: 12:00

Yeah. Do you? Is there data on the rate of participation? Is it going up or down or steady? Is it it's pretty stable? As far as I'm good? And does it tend to be like, is there is there a insight into who participates other subsections? Like older members or younger members? Like do we know about who are the kind of that sort of participators?

Jessica Leong: 12:21

Yeah, yeah, we are able to take a look at who is participating throughout the organization. So one thing we are noticing is that the newer members are volunteering at a slightly lower rate. Right. So that's something that we want to get our arms around as well, because that's a good trend.

David Wright: 12:40

How big of a commitment is volunteering, you know, because I have some friends of mine who volunteered for exam grading. That must be pretty big one. huge resource load, right? conferences. Yeah, you're right. So there were various levels. Have you ever volunteered? I don't think I've done some roundtables. Part of like a committee. I was asked to you by a friend, but no, you know, I was once I was, I was talking to Jim Weiss guests on the podcast. And I was having lunch with him. And I said, who's a very active volunteer. And I really admire that in him. And as you know, I haven't really done anything about that. And he said, he made me feel better. He said, Well, you said you're doing this podcast that helps people. And I was like, Okay, I guess maybe, right. And for a while, I actually had a, I actually was producing content for actuaries, professional professionals, and I was like, you know, doing riffs on the precepts. And, and I used to do it at the intro before every podcast that would get the get the guests to read some of it when the precepts your watch, laminated them all. And I was releasing it as like a separate podcast feed of like some, like, you know, as famous as somebody comes on the show, reading a preset and talking to me about it during the soundcheck. But I don't do that anymore, because I just COVID stuff like, I still have sound problems as we, as you learned the beginning of this. But you know, I'm trying to support the actual community, but not through formal volunteer mechanisms, I say with some guilt, and shame.

Jessica Leong: 14:11

worries, the podcasts are a great way for you to contribute. That's wonderful. But yeah, look, you asked a question about, you know, what it takes to volunteer. It can look it varies greatly. But we've recently been trying on some micro volunteering opportunities. Interesting. So one of them that's been super popular is our diversity impact group. So you can volunteer in small ways to help the professional in terms of diversity, equity and inclusion, like volunteering to do an actuarial high school day, go into high schools, talk to them about the profession, for example.

David Wright: 14:48

That's a good idea. How about the absolute level of like, entry into the exam process, like are those numbers How are they trending up down scale population? Any kind of feel for that? For the health of the top of the funnel? Yep, good question.

Jessica Leong: 15:09

We keep growing. As a society, we have a really healthy growth rate. And we have had that for a very, very long time. So I don't know, it's like 567 percent, something like that. Right. Right. So that's very, very good. I think we need to understand that more. Why are we growing?

David Wright: 15:32

What's your what's your pet theory?

Jessica Leong: 15:35

I think it's it's always been a very popular profession. And for a very long time, it was on the top of the league tables, right? In terms. Yeah, the best profession, however you define that. And we're still near the near the top, I would say. Right, so that's one. I think, look, I chose profession before really before the internet was particularly widely known and used. But I'm gonna assume since the dawn of the internet, people, more and more people have found out about the actual profession as well, and made that a career of choice. And then, honestly, David, like, it seems like the PNC insurance community has been able to absorb an ever growing number of actuaries that we've produced. Since I joined, I think the number of factories is like doubled, or more than doubled. Right? So where do they all go? What do they all do they all do something really rewarding. So, in the next 1015 years, if a doubles again, what are they going to do? Right?

David Wright: 16:42

Hey, you know, I have so let me so let me talk about exams for a sec, because I have this, I have this like, here's like a tough question, which is, do you think the exams are getting or changing and their difficulty level over time? There was no intention for them to change the quality level over time. Yeah, what is your feeling? I think that they're probably getting harder. Because, you know, I believe in certain, like social psychology research, like the Flynn effect, for example, I think people are getting smarter over time. And I don't think the pass rates are going up on these exams. So I think and I just sort of had this anecdotal feeling as I was looking at the old exams, they look way easier. And you would do you know, you would try them out the games from the 80s, and 90s. And it was much simpler. Sometimes there are different like, there's more kind of memorization, this is all from memory as a little while ago, now that I was doing this, but I had this feeling that that they were they were simpler, easier to pass, and they're getting more challenging over time. And at the end of it about six or seven years ago, a lot more deliberately complex questions like these, Bloom's Taxonomy or something was called, I think, maybe some harder, more integrative thinking. And I think that's harder. So that's my sense. What do you think?

Jessica Leong: 17:56

Yeah, look, you're right, the direction that over the years, we push things to less rote learning more integrative thinking, right? Just mimics the work environment much better, like no one is going to ask you to recite things in the appendix of page three or something. Right. Yeah. And I think that's a that's a good trend. If it has, I don't think it was a no a work to deliberately make these exams harder to pass. It's in our efforts to make sure that the exam process is rigorous, and we're actually giving people the skill sets they need to be successful in their jobs. Right. Did you find that when you were? Is that what you found when you took the exams?

David Wright: 18:39

So? Yes, I think I would say that, I would. I would say that I think the exams are really good. And, you know, here's an interesting like, contrast back to the difference in data science. This is actuaries where data scientists, they their kind of main mechanism of, of I don't we call it matriculation, right. So like, what is the thing that puts them into the profession is the university system, and they take some unobservable, hidden quality, you know, no hidden process by which they, you know, come through this university system and get a PhD often, or something. And then they go, and we don't know what happened to them. Right. It's not standardized. And I think that the, I think that with the actuarial profession, not being part of the university assist university system has been very liberating in being able to actually incredibly egalitarian, first of all, right, because anybody can show up and take it. And I'd even do a math degree in college. I didn't take a math class in high school, when I did the real exams, so I had to like figure all that out on my own self study. 100% and it went fine. through it, at least, with some effort, but I would have it I would never have become an actuary had it. Have you ever been required? Take an actuarial course in university never. And I think you're you're really in for an actuary. I'm very diverse, actually not diverse in like a racial sense, right. But I'm diverse and under cognitive science because of the train salesperson, and somebody who avoided math classes because I was scared of how hard they were. And, and I was going to write, I eventually worked up the nerve, as you know, like a later adult to do it. And if I had to go back to university would have been a joke. I would never have done it. But why did you do it? Because it was, I was very excited about the work. I sat next to actuaries. And I was fascinated by what they did. And I wanted to do it too. And I also had, so here's a story. I was sitting next to a reinsurance CEO a little while ago, and it like some kind of dinner party or something like that. And he was an actuary, from actuary, now the CEO of this company. And he said to me, I asked him, I said, so he moved on from the actuarial side to the underwriting side. I said, why'd you you know, what precipitated that decision? He said, Yeah, I was looking at those underwriters. And he said, You know, I said to myself, they're not smarter than me. And I the same story. So I said that a bunch of actuaries work. And and I was like, they're not smarter than me. And no, you know, I mean, turns out, they probably were, but they, you know, because, you know, the exams are really hard, but I was still able to do the work. And I was not in love with the academic material, like math is like an independent self, you know, serious study did not really interest me. But the work that actors were doing, I found fascinating, and I loved it. Absolutely. Love it. It's great. Unusual, math with a purpose, basically. That's right. Yeah, without without a way, that a reason. for it, I had no interest in it. And to me, having worked in the business for several years first, that is the thing that gave me the spark to want to pursue it. And again, you know, I think there's a wonderful advantage of the profession, you know, is structured, to actually find people like me, and, and encourage me to, to kind of become like, fully, like, capable contributing member of the, the group. Now universities don't have this. Right. And so they don't have this exam system. And so they're a lot less accessible. I think. What do you think?

Jessica Leong: 22:11

I do agree. Yeah. And we're looking in part of our strategic plan that we rolled out with our envision future, we're looking at how to diversify our pipeline. And diversity means a lot of things. It does mean racial diversity, gender diversity, but it also means diversity of thought, and our realization that a lot of our members do come through a university system nowadays, right, they study actuarial they get through a lot of their exams during their actuarial degree. But we also really value people like you, who decided to make a career change who have different backgrounds, right, and can bring different points of view to the table. So I think that's fantastic. I don't know how to attract more people. Like you.

David Wright: 22:56

Yeah, I don't know that there is like, there's nothing specific, right? I wasn't recruited by anybody, like, I've just worked in the business. And, you know, if there's one thing that was, was keeping me out, it was that it was intimidating. And that at first, I didn't know very people who had done it, right. And, you know, you can look at the actuarial profession and say, you know, they don't look like me. And so I'm not, you know, one of them where, you know, a bunch of math nerds or something like that, right. And I don't identify as that kind of person with those sort of cognitive traits. But, you know, I didn't didn't care, ultimately, and you know, when did it and that was great. And that's, that's it makes it very accessible. But here's like, the flip side, and I'll get your reaction to this, I feel like there still remains this kind of undiscovered quality of it, it winds up being a kind of like practitioner discipline, as opposed to like a really high status, like everybody went to Harvard kind of thing, which maybe you did, I don't know. But, you know, I think that there's something like linked in society to the high status institutions that, that we lack. And that because we're part of insurance, which is kind of not a high status institution. And then we didn't, you know, there's not like some obvious like the credential as a bunch of letters after and nobody understands they're not in the business, right. Within the insurance. It's a high status institution. But in the global sense, it's not, you know, high school kids don't dream of being an actuary, unless they read a bunch of books on licensed professionals to work for 2010. So, when you think about that, do you agree with that, that that is a challenge? challenge in terms of status? Yeah. attracting talent? Maybe not since it's happening anyway. But

Jessica Leong: 24:38

yes, it's a challenge, right? I think a lot of smart people who love to use data and analytics to solve business problems are choosing other paths, right, that they think might be more interesting, give them more scope. So like their data science career path, right? So that's a very obvious one. So in that respect, it's a challenge. But I would also say that that your profession is still held in decently high regard, right? I don't know about you. When I tell other people I'm an actuary. Actually, I have a choice, right? I go to a dinner party that say I'm an actuary, or I'm a data scientist, right? What do I, what do I choose? Whatever, it's six of one half a dozen or the other. But if I eat frankly, the one, I tell him a menagerie, they're very impressed. Right? Yeah. You must be very smart, blah, blah. They don't know much about it, but it just must be very smart. Something something right. Kinda like that. I told them if I was a doctor or something.

David Wright: 25:35

Yeah, that does sound like you hang out with people who know what actuaries are. I don't don't know that I do. They'll say an accountant. No, I'm not an accountant. But let's move on. As somebody joked to me once the actuaries like accountants, but without the personality, which is, you know, it's not it's a funny joke, but maybe not moved out a great job. Here's another easy question for you, Jessica. What do you think about the CES? So a merger? That didn't happen a year ago? Good question. Can you come up with an argument for or against it both actually can do can be one of each.

Jessica Leong: 26:13

You think come up with arguments for both. One thing I want to say is it is not something the leadership or the board is actively discussing? Right? Yeah. I think when I came into my role as President, you know, the way I saw it was this is a question we have talked about in very recent past. I do not plan to rehash this. Yep. So that's one. But I can see pros and cons from both both sides of that of their argument.

David Wright: 26:41

Yeah. What would be one of you?

Jessica Leong: 26:43

Look, I am Australian. probably tell from my accent. I come from a country that had one actuarial organization. Yeah. Which made sense to me. And I will admit, when I came here, I was like, Oh, what's this? And what's, what's the CIS? And what is the SLA and what is the AAA, right. And so that is obvious level of complexity that we have here in North America. So that's one, one side of the coin. And I paint this in very simple terms. But I think on the other side of the coin, we have, as you say, a really valuable community of actuaries within the CIS, right, you go to a conference, you feel immediately at home accepted, everyone knows each other. It's a really great collegial community that we have built. Right. And we all help each other. And that is something probably quite fragile. Right? We have to be careful that we sustain that going forward. So that is a big consideration on the other side.

David Wright: 27:53

Yeah. I, when I was considering it, I was looking forward to the debate, which we didn't get a chance to have as a community. And so that, that was that was too bad. Because that was, it never occurred to me that that was something that we should even think about. Right? So to me, like, the inevitable logic of consolidation? I just don't, I just don't buy it. I don't think I think that where we see lots of consolidation in, in industry, I feel like there's very logical reasons for it usually to do with enhanced valuations for larger organizations on a multiple basis. So you can buy a company at 8x valuation, and you can value yourself with 12. There's magic there. And that just is compelling. And so it doesn't happen for no reason. Right? So that's a reason. And to me, I just didn't see any reason. Now, as I thought about it more, I started thinking, you know, could one reason just be that the leadership of one or the other above, you know, just looking to do something? Right? Is it just like a purely like an agency cost problem here that they just want to do something and plant their flag? I don't know that that was the case. But I don't think that the strong version of the argument was ever really very well articulated. But let me give you how I thought about it. So to me, the only so your point about culture, I think is is a I like that one. But to me like the the most massive issue that could ever face the actuaries actual communities is independence. And I think that if we become more heavily regulated as a profession, that to me is should be our guiding star is to avoid to maintain independence and control over the examination process over disciplinary processes over our interactions with state regulators. I think that the fragmentation of the actuarial society and the fact that it's under the radar is very deeply linked to the to the fact that regulation is by state United States and not federal, I think it was federal we would be a foregone conclusion we'd all wind up because it's just easier to interact with one body. If you're a federal federal government was Started one person, probably. But that's not like that. I think the states aren't quite as stringent about that. And I, and I think that independence is the most important thing. So to me, then if that's true, that's how I feel, then you have to analyze any kind of movement in the actuarial organization as one is it moving towards greater independence or away from better defense. And I could see both in the sky. So a merger is I can see us having a stronger lobbying effort, which I think was was mentioned, but not really emphasized in the way that I would have with any any government organization, if we were together with more resources for lobbying, which I think it would probably work to preserve our independence. But then again, it might put her head up above the parapet. Right. So now Oh, they're all one big unified group of actuaries. Now we have a throat to choke. Right? And we could we could be a target for all sorts of special interests and whatnot. And then that would inevitably slide us down to greater regulation. And so I in the end, didn't get a chance to have this debate with anybody. I'm not asking you to debate these points, either. And maybe you'll get proposed again someday, and we can't have this debate. But I think that at least the framing of actuarial independence being the most important thing is is something that I didn't see discussed as widely as I would have liked. Do you have a reaction? No.

Jessica Leong: 31:17

No, I hear you. I think that is an important point to keep in mind. And if you look at what's happened to others societies over the years, and not that I'm a great historian, either there has that has been something the independence part has been something that has evolved, right, and other countries like the UK and Australia. So that is something that we need to be mindful of. Right. That is, you're right, probably not completely top of mind all the time, because there's not an issue that has been that front and center in the US.

David Wright: 31:47

It's the water we're swimming. Right. We I mean, it's incredible that, that there isn't like a if I remember, I sat through a talk once at one of the Cavs meetings where there was a presenter talking about how exactly states define an actuary, or, and it's fuzzy, like, there's like, there's not a lot of because you can sign off on financial statements if you're an ncaas, under certain circumstances. And there's all sorts of like, weird legacy definition criteria that get involved in like, who actually can perform the acts that are supposed to be formed by an actual rates look a little bit of a mess. And it's actually it seems to me that there is this, everybody's Okay, with not really asking too many questions about it. Because it's working. It's not not working. There haven't been, there hasn't been a huge rash of insolvencies, right? There hasn't been like, there's no witch hunt out to look for whoever signed off on the person with various actuaries. And as long as that state continues, state of affairs continues, then then this mess we're kind of looking at right now. Kind of hard to see who loses, right? Why make Why make the change? And anything that like, disrupts that equilibrium, to me is just kind of terrifying. So I'm like a deeply conservative, accurate. Say that. Yes. Interesting. You said, most, most actuaries aren't like me, you think they want to know most factories are very risk averse. Let's go with that. All say, Yes. I'm on board with that. You know, I'm fully on board with that. So tell me about like, we have even talked about your presidency at this. Yeah. So tell me some things you wanted to accomplish. You want to accomplish? What are you working on? What are what are your priorities?

Jessica Leong: 33:32

Great question. Look, my priorities central around the three year plan that we rolled out in November last year along with that envision a future. It is our strategic plan of what we want to do over the next three years to move us towards our vision future, right. So it has four parts to it. One is building skills for the future. Two is developing our pipeline. Three is growing internationally. And then number four is making sure we have an operating model that can support those first three things. Okay. So you want me to go through each of them?

David Wright: 34:05

I do. Okay, I do. Can you tell me first? Was this a plan that you inherited, inherited? Or was it one that you developed or involved in developing? Like, is this something that's bigger than just your your kind of? office? holding period?

Jessica Leong: 34:25

Yeah, good question. So I held a board retreat when I was president elect as as the what each President Elect does, and I used it, to get the board together to develop the outline of this strategic plan, our strategic plan over the next three years. It was actually it was a lot of fun. And these are the four areas that we all agreed we wanted to work on, that would move us towards that envision future.

David Wright: 34:54

And how long is the term of the President.

Jessica Leong: 34:57

So this is how it works. So you're When you agreed to do this, you're on for a three year, three year term. So the President Elect, then your President, and then your chair of the board.

David Wright: 35:09

One year each. So you will have begun a three year implementation and year two of your tenure.

Jessica Leong: 35:19

Yes, sir. Yep. Yep. So your one is the year I'm president, basically. Yep. This three year plan?

David Wright: 35:26

Yeah. Right. And so your successor will need to be on board with this plan? Yes. And you already noticed success rates?

Jessica Leong: 35:33

Yes. And Kathy was there when we did this board retreat? Okay. Very good.

David Wright: 35:39

That's handy. So yeah, so let's go into some detail, then. What are you doing exactly to further these goals?

Jessica Leong: 35:46

Yeah, great question. So building skills for the future is an exciting one. So that's talking about the accuracy of the future and what skills I need. Yeah, right, both. So we're talking about basic, but also continuing it. And we're thinking the actor of the future has three core skill sets, right. So one is analytics, and the Klein like whatever analytics, you need to solve the important insurance questions of the future. That's the analytics we need our members to know. So that will mean advanced analytics. Number two, business problem solving. I think we need to up our skills there in a pretty big way. So from my viewpoint, as we have more big data, right, as data gets bigger as analytics, in grows as a skill set, there are going to be more and more new problems that you can solve with data and analytics that you consult for. So what I find is actors are good at solving the traditional problems, reserving pricing, etc, right? And we're sort of given a book, step by step how to do these things. What about the new problems that you can now solve with data and analytics? Right? That is, that's been very challenging, I'll say for me and my team. And you do need to really up your skills in terms of problem solving, in order to be successful in that space. So that's the problem solving. And then number three, is just the domain knowledge, which for us is PNC insurance. So we are thinking, the actor of the future with those three skill sets. That's that's really the vision, right? And I used to call it a unicorn whereafter. But then I think the CIS marketing staff were like, you know, unicorns don't exist. Jessica, stop saying that word.

David Wright: 37:39

Funny. Interesting. So I want to you, you, you published a or your private presentation that I found I was doing some research for this. We were talking about the the progress analytical tools. Did with Domingo and other Gentlemen, I forgot her name. But those interesting presentation where, you know, I think that it opened with a kind of like lament about, or this question of whether or not things had advanced, then proceeded to present all kinds of interesting advances, I think, analytical tools. And I'm wondering what you think the state of it is now vectorial tools, because there's always this, there's always this, I guess, irony maybe that we had developed analytical tools that are very sophisticated, but multaq most archers use basic triangles, important person, still. And I wondering what that was probably like eight or nine years ago, I think you might have given that presentation. So in 2021, what do you think about the state of the sophistication of the tool kit

Jessica Leong: 38:44

of the actuarial toolkit or the wider toolkit that you could use to solve insurance problems?

David Wright: 38:49

Or? Both? Sure.

Jessica Leong: 38:54

Look, I mean, if I just think about the work me and my team do today, it has even so I've been at Zurich for six and a half years. And in that time, there are things we couldn't do when I first joined that we totally can do now. So it is watching, like implementing things around image recognition, for example. Just frankly, having the rule computing power to actually implement it, having the open source code to frankly do it pretty easily. All of those are becoming more and more reality, right? Or things around natural language processing, and the development of tools like GPT, three, all of these things that are happening in the broader analytical space, it's moving really, really quickly. And companies will release my company is taking advantage of of all of that.

David Wright: 39:46

And I think it's really interesting. Those aren't reserving techniques. I don't think I have it pretty cool if you could. Pretty interesting anyway. I could probably imagine some really interesting ideas. Experiments but on how about within the actual real? Well, let's say, you know insurance analytical toolkit things actuaries would use in their day job as an actuary. How about the state of innovation or advanced in those tools?

Jessica Leong: 40:15

Great question. So, look, more and more predictive analytics is getting into the toolkit of the actory. From a day to day basis, right? So even just simple things like basic multivariate glms, right. We're seeing that used more on a day to day basis for for x rays. And I think that that is a step in the right direction. But we do need to go to go further for an actuary, and they're talking. So that's something we're talking about as we think about the exams as well.

David Wright: 40:47

Yeah, yeah. I was amazed when I took the exams, this is like, more than 10 years ago, I guess. And I was doing it, but that, that there was no, no programming. There is now there has been since then. I think the very last exam I took did have some stuff on glms. You know, like, serious work on GLM. And I was just kind of amazed that it hadn't hit yet. And I kind of starting to kind of flow through. But I, you know, I feel like there's a, there's a challenge in the data that actually leads us with that doesn't really doesn't really help to have more tools, because the data can be so limited, you know. And I'm wondering whether that's just sort of the constraining factor is that must the data changes? Why would we need new tools?

Jessica Leong: 41:40

Yep. Yep. I think data is probably one of the big opportunity areas for all the various players in the insurance space, right. today. If I think about what holds us back, at least of my team, it will be the data more than anything else, right. We have the analytical capabilities, but what about the data? So I completely agree with you, particularly like you fight in the reinsurance space? Absolutely. commercial insurance space. Absolutely. Right.

David Wright: 42:05

And, you know, I think there was this kind of revolution that broke over the actual community in the in the late 80s. I think it was when they started, when they the creation schedule P. Right. Suddenly, you had this publicly available data set of, of actuarial triangles. Right. So I'm wondering if it's like, within your it's in your minds to lobby to any IC to compel companies to disclose more data in the in the annual statement? Because that will be one way to get it into the system, then you're forced to interesting.

Jessica Leong: 42:40

No. I don't know how the shedule p like how that came about in the first place.

David Wright: 42:46

Yeah, I mean, I it was a paper is listed in one of the in an exam. I guess it's six, is it? The one that's on the regulatory stuff? There's a little little paragraph of history on it. Feldblum, shalom Feldblum. And I think it's him. And it says that there was a huge effort that was underway. And it maybe supplemented this with some other research I've done just because I love this stuff. There's huge controversy about and you can imagine the companies right insurance companies, not being terribly happy about this. But in the wake of the liability crisis, think of the Think of the like, the regulatory political environment for insurance companies, then that happened now, I'd be terrified for the for the independence of the actuarial society, if you had a legit economic in your pain felt by average people, because reserves were inadequate, and insurance companies, that would be a big problem for us. But then they did. And one of the responses was scheduled p, they said we gotta be able to evaluate these companies. And in the late 80s, was when that came about, I think it was launched in the early 90s, when schedule p was the very first thing to be forced, forcing organizations to disclose that, you know, pretty intimate information about their business. I didn't schedule peasy online. I mean, it is incredible how much data you can get out of there. And so it seems to me like, you know, I don't know, I wonder what kind of tools most actuaries use before schedule P. I probably used. I wonder if it was a similar kind of like, you know, we're thinking now about pornographer, gusset, when back then they might have been, you know, that might have been the machine learning of the day. I mean, if only we had better data, we can use that. Perhaps what would be the data you would want from every insurance company? So you're now working inside a big insurance company? If there's like a data item that you could, you could you could get? I don't know, like if you were a reinsurance company, right? What would it be? Do you think? I have an idea, I'll give you mine. You go first. No, no. My would be very detailed exposure to exposure data, to me is the key. I think that that's very poor, very poorly maintained. Because it's not used for many things. If it's revenues, you can sort of imagine it being the case but you Whatever their driver is have a reading algorithm. That would be I think that would unlock a lot of innovation because it's like, you know, it's

Jessica Leong: 45:05

big. Yeah, good question. I think, look, I actually think claims data is one of the most important strategic data assets that an insurance company at least carries today. Yes, you know what, you can actually buy the exposure data, right? Sure. Like, if you wanted to find out something about various companies, or whatever it is, you're insuring, you could buy that, right? Probably for a price. Whereas for the claims data, usually you can't buy it by paying for the claims.

David Wright: 45:37

ran very expensive.

Jessica Leong: 45:39

If I think about like, we get approached by an shoretex. And the one time they ever want to actually work with us to develop things is because they want access to our claims data. That is the one thing they cannot buy.

David Wright: 45:51

That's good point. I think your answer is better than mine. Okay, so we're at a time. Jessica, do you have any asks of the audience, what could you if you could, what would you any closing thoughts on on your mind today? No, I just want to thank you, David, for the cast. right about that. I'll do that for you. Because I think people should do that more or start a podcast.

Jessica Leong: 46:18

Sure, volunteer. If you're a cis member, definitely volunteer. Great. It's been a pleasure, David. Yeah.

David Wright: 46:25

Thank you, Jessica. My guest today is just Leong.

Jessica Leong: 46:28

Thanks so much.