Julia Romero - Lead for Actuarial Engineering and Advanced Modeling, Haven Life

Julia Romero - Lead for Actuarial Engineering and Advanced Modeling, Haven Life

December 1, 2020

Julia is the lead for Actuarial Engineering and Advanced Modeling at Haven Life, an online life insurance agency backed by MassMutual. At Haven Life, Julia is focused on integrating and applying data science and other analytics models to drive innovation in actuarial technology. Prior to joining Haven Life, Julia worked as an actuary at AXA US, where she focused on the development of agent based models of annuity policyholder behavior.

How long have you worked as an actuary?

I’ve been working as an actuary for 10 years. 

Which markets (includes domains and global markets) have you worked in as an actuary?

I’ve worked in life valuations, variable annuity pricing and in-force management, and traditional life, all in the US.

If you could have one superpower, what would it be?

I’d like to fly. 

What do you see as key characteristics of innovative actuaries?

I don’t think this is particular to the actuarial profession, but people who are curious, passionate, open minded, flexible and comfortable with uncertainty - these are the people that thrive in innovative environments and tend to bring a lot of innovative muscle to the table.

What factors do you believe influence the impact actuaries can have within their organizations?

I think this answer is also going to be pretty similar for folks in quantitative professions in general.

The factors that influence the impact that an actuary can have comes down to having an organization centered around a vision that your work can connect to, and understanding at a personal level how your work connects to that vision.

Then it’s having supportive managers and teams that help you articulate how your work matters to that vision. That involves senior leadership and feeling represented on the senior leadership team, which I firmly believe matters more, not necessarily actuary to actuary, but person to person.

What are some key ways you see the actuarial profession evolving in the next few years?

Well there’s the pat answer of ‘actuaries are going to become data scientists, and do all those things, insert crazy math meme here.’ But to me, I think the special sauce actuaries bring to the table, and what we need to invest in, is our ability to understand the business around us in a rigorous, highly quantitative way.

This is not just understanding the data around us, but fundamentally understanding how the data matters to the business and articulating that with the trust vested in our profession. Doubling down on professional standards and the notion that what we’re doing needs to meet a given standard of work.

I obviously think it’s important for actuaries to perform basic data science exercises and become fluent in programming, but I think that’s table stakes for any job really. For the profession, I think it’s honestly putting ‘profession’ in bold. There’s something real and rigorous, something that has body and stands behind the opinions you give. 

Despite there being significant collaborative potential between data science and actuarial science, the two expert fields don’t always mesh in insurance. How do you believe they can work together more successfully?

I definitely agree that this challenge is a real one. I think there are three models people try: 

  1. Data scientists who are embedded with business teams. So if you’re a data scientist and you work with marketing, you may not have an insurance background, you learn from a marketing standpoint and that’s your frame for thinking and working. This can make it hard to work with actuaries, who tend to have a different perspective.
  2. The center of excellence model places all the data scientists together and jumps in, which can sometimes rub folks the wrong way. Some people might be inclined to say, ‘I’ve been doing this mortality study for 15 years, what do you want from me, new guy? I see you’ve used a more complicated methodology, but your A/Es are the same as mine.’
  3. The hybrid model, which I’ve found more successful. 

When I was working on variable annuity policyholder behaviour, we took a hybrid approach where there were more traditional data scientists working in partnership with someone in the business with a data science background.

I worked closely with someone with a data science background who was a data engineer, and that led to really efficient, effective, fruitful collaboration because it was more of a partner than someone there to do a mission.

I think the question itself gives the answer: there should be good collaboration, but there isn’t. I think it’s fundamentally about how data scientists and actuaries are poised to work together, which is very ‘they’re going to do this and I’m going to do that’ as opposed to ‘we both do these things and they work better together.’ It’s about how you assemble a team, how you position what that team’s mission is, and how you incentivize the folks on that team to get to the best answer.

What makes innovation impactful? 

Innovation is impactful when it makes a difference to real people.

If you do something that lets the company save 32 cents a year per policy by pushing everybody to electronic billing, that’s great. But being able to say, ‘by pushing people online, I got people to interact more with their policies and made some people aware that the coverage they had wasn’t appropriate for them’ is impactful.

Making the product we offer matter more to the people it’s supposed to help makes innovation impactful. You should build something that matters to people, particularly in insurance because what else are we here for? We’re here to make things a little bit better at a terrible time. So make a difference!

What are some of the more impactful innovations in the actuarial field and why?

It’s hard, because the actuarial field is a squishy thing.

Obviously there are people with credentials and people without, but if you were to take the John Hancock Vitality product as an example, is that an actuarial innovation? Actuaries worked on it. It definitely makes a difference because if you have your insurance policy attached to your wrist you’re going to think about it more.

There are also examples, like the original Vitality applications in South Africa, where it enabled  insurers to offer coverage to people who are HIV positive and generally underserved. That’s so important, but is that actuarial innovation? Again, actuaries worked on it, but not alone. That part is a little fuzzy.

Even as we get to some of the products in the market today, like those sold by Haven Life or other insurtechs, where can offer life insurance to someone at a price point they can afford and a timeline that works for their life - selling term life isn’t innovative, but selling term life to those who never had the time or cash for it, that makes a difference. 

Earlier this year, a bunch of amazing actuaries at MassMutual and Haven Life rolled out HealthBridge, a program that provides  free life insurance to frontline workers.

It took a ton of insurance product innovation, including tech innovation to get that product out the door. Think about pricing a product for people who work frontline in hospitals, pricing the mortality of that product, in March 2020. That took a really, really innovative approach to figure out how to leverage the experience from South Korea and other countries to understand how the virus mortality might emerge here. 

What is the best type of change actuaries can adopt to become more influential in the insurance industry?

I think it’s been the SOA’s mission to improve actuarial communication skills, and I think this is the most important thing.

From what I’ve heard, it’s gotten better, but there’s no way to have your work appreciated if you’re not the best advocate for it. It’s figuring out how to make our case in a way that is clearly aligned with what we’re here to do as a company and industry. How do you sell your work?

We, as a profession, tend to do a pretty terrible job at this, and in all honesty we don’t even do it half the time. Actuaries can kind of turn into an answer vending machine, and we need to be really deliberate in going to the next step - providing a robust answer and then making it clear about the implications of that answer and what we think should be done about it. Getting to a solution not just an answer.  

What advice would you give someone considering an actuarial career today?

Honestly, learn how to write code well. Pick something, Python or Javascript or whatever, and learn how to do stuff in that.

Understanding how to think algorithmically, which I think is the muscle you’re building, is everything in succeeding as an actuary today (and not for nothing being able to automate things is a HUGE asset for a student actuary today). It makes all of the difference, whether it’s thinking about product design, sales funnels, underwriting, or just fixing models, all of those tasks become infinitely easier if you know how to think algorithmically.