Case study: New York Life (NYL) and Virtusa discuss how digital transformation modernized NYL's Insurance landscape to fuel business agility and scalability

For over a decade, NYL and Virtusa have partnered in driving complex multi-year digital transformation programs. From designing and incorporating a single microservices-powered platform to support NYL's insurance and business factions, implementing a re-usable master data governance platform to fix data quality issues, to innovating NYL's end to end business model with microservices and digitization, Virtusa and NYL's robust partnership continues to steer towards a transformative and successful future.  

In this panel discussion, learn how NYL overcame business challenges and partnered with Virtusa to achieve digital transformation and innovation to increase productivity and stay abreast of market conditions.  

Transcript:

Brijesh Raval (00:10):

Good. Jake,

Brijesh Raval (00:11):

We good? Okay, good afternoon everybody. My name is Brijesh Raval and I am a Client Service Partner at Virtusa. And I have with me Betty Smith, the CIO at New York Life, and I have Ganesh Iyer who is Head Of Insurance at Virtusa. Today we are going to talk about how New York Life embarked on their digital transformation journey. But before I start that, just wanted to talk a little bit about the environment and the business state that we are in and talk a little bit about VUCA. I do not know if people have heard about it, but VUCA is where we are right now, stands for Volatility, Uncertainty, Complexity and Ambiguity. Interestingly enough, this term was coined by the US Military during the Cold War era and it has come back and hit the business community, I would believe, since we got hit with Covid and there has been a lot of Complexity or Ambiguity and Volatility in the market. So Ganesh, why do not I start with you and ask you how insurance carriers are dealing with this environment and what are you seeing that it happening in the industry?

Ganesh Iyer (01:34):

Well, thanks Brijesh. Good afternoon everybody. We indeed are in very foggy times and you will be a little surprised as to why I talk about it as foggy times. It is not a big times, but foggy times. So on one side there are some bright things which are happening over the last several years, insurance actually has been growing. I do not know how many of you have been in the industry, but we always used to be phased with the fact that insurance market is ringing, especially the developed donations, the insurance market is ringing. Whereas if I look at the pandemic and post pandemic era, we actually have seen an increase in return premiums. We are seeing an increase in enrollments. So all of that is very good. Similarly, if you look at the interest rate regime, I think we have never had it so good. I think insurance carriers are really happy that they are able to yield much more on their investment returns.

(02:29)

So these are good times. On the other side, things are very confounding, I think, you know, have increased losses thanks to natural catastrophes. You have the geopolitical tensions causing still several issues around supply chain. So many of you will be looking around the curtain and saying, is the inflation? Is the recession here? Is it not here? So I think we are really still trying to predict that and on top of it, you have this runaway inflation. All the carriers are really faced with really increasing costs and it is impacting everybody's bottom line, big time. Now add to this the fact that there is a very mixed labor market. So once victim, you keep hearing in the news, I think it is very popular to hear about layoffs happening. Whereas on the other side, if you look at the enterprise market, if you look at the unemployment rate as of last week, it was still 3.7%, one of the lowest it has been in decades.

(03:30)

I think it is very confirmand to figure out where is this labor market actually going right now, some more facts which are true is global aging is a reality. You know, suddenly are going to have many more aged people in the ramifications around what it means for claims, more accident claims, retirement products, what it means for wealth, which has lived behind by the baby boomers. All of that are real, which brings us to insurance carriers you are trying to deal with, how do you really look at that retiring workforce of thousands of people? What are you going to do about replacing that talent with a younger generation who does not want to work in the typical way that you are been used to? Insurance employees working, they have a different expectation of what they want from life, their careers and so on. So it is a very mixed environment, very foggy environment out there.

Brijesh Raval (04:21):

So Betty, how are you seeing this? Do you agree with what Ganesh is saying or do you see things a little differently?

Betty Smith (04:27):

Yeah, no, I agree. I will add one other point in that we are continuing to see an increase in consumer expectations on how they actually interact with us and how they expect us interact with them. They are looking for more differentiating experiences based on where they are in their financial journey. So for example, being able to connect to a financial advisor to really go through their overall advice and guidance on where they want to be, what their financial goals are and so forth. And then other consumers want more self-service capabilities that we need to grow to build out so that they can transact on their own. So that it another big piece in the whole mix,

Brijesh Raval (05:26):

And I think both of you guys talked about talent is scarce and tough to get. Do you see any impact, Betty, on your budgets and spend this year? How are you think things play out for New York Life this year?

Betty Smith (05:43):

Yeah, I think two things just to address talent a little bit. Talent has been difficult to get in the marketplace and we have put a number of programs in place to help upskill and grow our talent. Looking at the landscape of new technologies and advanced technologies that we want to be able to master and leverage as part of our tech stacks on the other side, on the budgets and so forth, A lot of focus on increasing efficiencies, being able to continually look at how we cost manage our run portfolio to be able to free up funds to be able to put more into innovation in modernization. So kind of shrinking and simplifying our technology stacks is a huge priority for us.

Brijesh Raval (06:47):

That it a perfect segue. My next question was going to be to dive into our case study. Can you explain some of the challenges that you guys were facing that prompted you to start this digital transformation for New York Life?

Betty Smith (06:59):

Yeah, yeah, sure. So New York Life is over 175 year old companies. So like many insurance companies, we have our fair share of legacy with a mix of modern tech stacks. We also grew up in a world where we have big mainframe systems, we have lots of data disparate, a lot of point-to-point connections, as well as a lot of batch jobs. So we have over 1500 applications and most of our applications, well I should say a fair share of our applications still live within our on-prem data centers. So we had a big challenge of, as we started our digital transformation, we had started really looking at how were we going to modernize our front end systems to meet those expectations on the experience for our customers and the interactions between us and our customers. And those are all based in the cloud. So we, we have moved all those applications up in the cloud. So we created a new challenge of how do we get more real-time data between our cloud and our on-prime systems.

Brijesh Raval (08:33):

To help us understand how EIS, which stands for Enterprise Integration Services came into being. Because you were the one who started that practice. So tell us how that came into existence.

Betty Smith (08:47):

Yeah, so when we started to look at again, how are we going to efficiently simplify our ecosystem, have these connections from our front end systems to our backend systems, there was a pretty big void in terms of creating and skilling for an effective and an efficient integration layer. And that it where we started to create what we have called our enterprise integration services. So we landed on the MuleSoft platform to build out our API network system, and we realized fairly quickly that we did not have all the talent and skills we were going to need to really accelerate the enterprise integration services. So that it when we tapped into Virtusa.

Brijesh Raval (09:43):

Perfect. So that it my next question for Ganesh. So Ganesh, you want to talk about some of the challenges when we started this program and then suddenly you had to get people staff to meet to various dates and requirements?

Ganesh Iyer (09:58):

No, EIS three letter acronym. A very simple project. I am joking obviously. So EIS was a very complex, daunting project and I think we employed a multi-point strategy to address it. I think the project initially started off by executing on three POCs within a timeframe of four months. So we embarked on that and hey, Presto, things changed, the budgets changed and we then had to deliver, and Betty's got a smile at this, but we were going to deliver it now 90 days. So as soon as we started off the bat, we had that challenge, we dealt with it and we succeeded with that. So we started with a six people team, I think at that point of time, and the POCs were successful, but this was one of the first projects in New York life on cloud. And like Betty mentioned, they had chosen MuleSoft as a ecosystem.

(10:50)

It required really a bleeding edge technology project like this required a right set of skill sets. And we realized very quickly we got and require really strong SMEs, Architects, Cloud Folks, a lot of Domain Experts, and we had to scale and we succeeded in scaling this from six to almost 60 people within a couple of months, which I think is a phenomenal thing. So we literally ran dedicating hiring days in the US then in India and as well as in Shri Lanka where we happened to be the largest IT employer and really managed to get this team up to speed. Then after we worked very closely with MuleSoft for the politational elements of the solutioning. So we have a lot of due diligence done on that. Thereafter, they had some unique challenges specific to New York. New York has, I am sure with any large carrier, they had their enterprise architecture boards and the system architecture boards, and this was the first time they were doing something in the cloud.

(11:46)

So we had to figure out a way to have them bless these architectural stuff that we had done. We cleared that, we got that blessing, and thereafter we really adopted a factory model to really accelerate a whole bunch of the development. So it was a very unique virtusa art driven factory approach that we got into development of the APIs, needless to say, a lot of tight program management governance, working with the stakeholders and obviously taking a lot of help from New York life leadership across. So it was a challenging project. I would just add one thing. I think understanding the legacy domain was very critical and I think we really got a lot of the virtuous domain experience to bear as we worked with New York Life through working through this.

Brijesh Raval (12:34):

Perfect. So Betty, let's talk about the solution, right? Because you were essentially replumbing the entire environment and like you said, it is not easy, it was very mainframe, a lot of bad jobs, and on the other side you have Salesforce and Adobe asking for real time data. So what were some of the challenges that you remember that you want to highlight a couple?

Betty Smith (12:59):

Yeah, so as part of this whole solution, we architected a three tier approach to our APIs, our system APIs, our process APIs, and then our experience APIs and within the system APIs, those are the ones that we want to make sure have the most reusability in the whole organization and tapped into our various data sources. So trying to make sure we got the right data was a major challenge for us because a lot of our data sources went through a number of ETL and as you said, batch processes and so forth, and sometimes business rules were baked into those processes, changing the data elements. So really understanding the domain and the data and making sure we were going after the right data sets was critical. Also, just the change management aspect of moving to an API and a reuse type mentality versus point-to-point connections. It is very easy for people and quick and quick to stand up, new point-to-point connections we had close to what 5,000, 10,000 point to point connections that we have had to take down in the ecosystem and make sure we did not break anything as we did that. So that mind shift within in the training within our Developer teams, our QA teams to really look at how to leverage APIs in a reusable way was a critical component to how we succeeded in all this.

Brijesh Raval (14:50):

Betty, how was the EIS program and I heard one thing led to another and suddenly as you were doing really well on this, you became responsible for the data program. I think that it an interesting story. If you can just highlight.

Betty Smith (15:07):

Yeah, I mean, as I mentioned the data, we have hoards and hoards and hoards of data and trying to get that more centralized in a way that was reusable and more accessible in a real time mode across the enterprise was key to that. So joining enterprise integration services, what we called enterprise data management was a very good marriage in terms of bringing those two functions together to work together in terms of really starting to simplify, centralize and really organize our data so that it flowed properly, we were able to get it in more real time mode and the integrity of the data was critical in all that as well.

Brijesh Raval (16:10):

Ganesh, how was Virtusa handling this sudden surge of demand and also different skill sets now? Because we had to go from API to managing data.

Ganesh Iyer (16:22):

Very interesting story. I think very clearly the success of EIS's really prompted the manifestation of this program to move into the data side of the house, and that is how that built. So EIS was inherently organized as an integration platform offering and somehow it got very heavily intertwined into the data side of the house. So inherently integration platforms require a much more deeper understanding of the data as it pertains to a lot of heterogeneous systems. And most times in insurance companies, and I heard this in the past from a couple of other speakers, it is almost impossible to given this just the sea load nature of systems of legacy systems, the legacy architectures, the inconsistent metadata, just data definition, it is impossible to get that kind of clarity. And really the enterprise data management program real, it really transformed and ensured conformity of the data to that single version of truth that was required by EIS for it's microservices data layer. So it was a phenomenal success that was institutionalized thanks to really bringing these two organizations together and getting this whole data program going at the same time. So I would say all in all, it just Metamora very nicely into one swim lane.

Brijesh Raval (17:44):

So what kind of Virtusa tools or accelerators you built, you know, were under time constraint and you had to bring all this together. Would you like to highlight some of that?

Ganesh Iyer (17:56):

Sure. Actually, like I mentioned initially we started scaling the team very rapidly and I think when we reached steady state, we realized that there is even more scale that is required from the program and very quickly we realized that we can not just throw more resources at this program, that we needed to really think out of the box and see what can we do to increase more productivity. In Presto, we came up, we really leveraged a gamification tool that we employ within Virtusa called ERA Insight. Essentially it is a tool which rewards good work know it is a way of tracking how everybody is working. And so essentially right from the architect, the developer to an analyst to a QA register, everybody is being tracked in terms of their output. Furthermore, the system also has a workflow wherein if somebody checks in data and finishes a task, the next person in the chain knows that the task is completed. So it has also enabled that I think this system really, this whole gamification system helped people really flourish. So we had people who would get more points if you really check in court and it is without defects. Similarly, a requirement analyst will get more points if the requirements are explicit, things of that nature. So either you belong to the hall of fame or you belong to the hall of shame.

(19:22)

So every month we ended up having kings and queens declared and that really provided a lot of productivity. So in addition to that, obviously we had a slew of accelerators right from analysis to deployment and with also the first time within New York Life we used a save Agile methodology. We employed CICD, dev hub ops and so on. One last piece in terms of acceleration was around automated testing. So we really started looking at how do we increase the automation significantly by providing more tools to the teams. And I am glad to say that we actually moved the extra to developer ratio from 40% to 25%. All of these helped in really accelerating the program to where it started really producing the kind of quick results that NY's was expecting.

Brijesh Raval (20:13):

So Betty, let's move on to the outcomes. Do you want to highlight some of the key outcomes and the benefits that you get from the program and how it is putting New York Life in a place to get to that next generation of the transformation journey?

Betty Smith (20:25):

Yeah, I think one big highlight is I mentioned we have a number of legacy systems. Those legacy systems are 40, 45, 50 years old. Very few experts left on those systems with the rate individuals are retiring. One of our client system houses all of our core customer data and the system was 45 years old and we had one employee left on that system that was an expert. And through the work that we did in APIs and putting in the discipline around API Architecture and Microservices, we were actually able to deconstruct that whole system and rebuild it all using a microservices architecture, which is now faster than the system that was there. The data integrity and quality is much higher than what it was in the old system, and more importantly, more people know the system. We have been able to fan out and have more experts across that system. So we completely de-risked one of the key legacy systems in the organization.

Brijesh Raval (22:06):

That is a fantastic story. We went from EIS to data and to tech debt reduction. Ganesh, what were the outcomes from the technical perspective and innovation and how did this project help you become a more strategic business partner for New York Life?

Ganesh Iyer (22:23):

No, I think Betty summarized it right? I think on one side the reusability of the APIs was something that one had not predicted. I think it really changed the way everybody in New York life viewed the API application. So I think that really that whole reusability almost 35% reduction in reuse of APIs was huge business benefit. And then obviously the sidebar benefit was this decommissioning of some of the peripheral, what I call a tertiary application systems which exist in the environment. So that was a very nice benefit, which came out of it using some of the tools we managed to reduce 40% in the ETL processes. We used the LLM and PLM modeling. I won't get too deep into that, but I know that really helped on the data side. So lot of these small, in fact, I think if I recollect right, EIS and ADM was the only two engagements in New York Life which received the most funding from business thanks to the success that it was seeing. So I think it just underscored that the project paid for itself many, many, many times over and it was truly successful. I think this whole both on the integration front and on the data front, I think Betty and the team really delivered far more to the business than they had expected.

Brijesh Raval (23:40):

That it true. So Betty, what's the future?

Betty Smith (23:44):

So obviously those programs live on and continue to expand. A lot of people have talked about value streams. So we are also embarking on a transformation of our model based on how we actually set up our enterprise integration services. That function started off as a typical shared service. The work had to go through that team to get done, but we quickly realized that moving into a value stream model, you want most of your resources to be able to work as independently as possible where you get your speed to market efficiencies and productivity. So having a lot of shared services group that the value streams now need to be dependent on actually slows things down. And the model that we had shifted when we were building out enterprise integration services was moving from a shared services to what we call a center for enablement. And the idea of a center for enablement is the mindset in that group is really about how do I create self-service capabilities that other organizations like the value streams can consume very easily and on their own. So APIs obviously was a great place for that to happen. We built some, most of the system ones, the process layer and the experience layer are with the value streams to actually build out those APIs as we move forward. And so using that model, a number of our other shared services group within the organization such as Security Cloud and some of the other ones have all moved from a shared services function to now what we call centers for enablement.

Brijesh Raval (25:53):

That it fantastic. So Ganesh, what is it for Virtusa now that we have a success story, how are we trying to help other customers do similar things?

Ganesh Iyer (26:03):

One is we continue to engage with New York Life. We are still a trusted partner and are part of this whole value stream journey with New York Life. So glad to say that. I think reflecting on a couple of things, which obviously we heard during the course of the earlier sessions, one thing is for sure, you know, can continue to build all the fancy things in the front end. I know your contact centers, your portals and so on, but legacy in insurance is here to stay. You can not really, I do not think carriers have the option of just ripping and replacing what they have in place. So I think what I call is digi proofing, which is digitally future proofing a legacy is one of the biggest more critical options, which is exactly what New York Life did, which has got implications both on the AP application and microservices and the data.

(26:55)

These continue to be something that we really, really focus on, we really engage on. And I think it is not only relevant only from the life standpoint, I think across the board of all kind of insurance companies Digi proofing is something they have to contend with and that is the only way I heard. I think maybe Dipa said this, you know, either are going to be part of this bandwagon or you are going to fall up the bandwagon. So if you do not do something about this quickly enough, and I think with the course of the last three, four years, you do see customers trying their best to jump on, but they end up doing a whole bunch of these fancy lipstick stuff on the front end. But if you do not take care of your backend to contend with it, which is exactly what the proofing story in New York Life was all about, it is going to be difficult and that is where we are focused on very heavily as well.

Brijesh Raval (27:41):

Thank you. That was fantastic. I think we have about two minutes remaining and would be happy to take any questions.

Ganesh Iyer (27:57):

No question. I guess we are very impactful.

Brijesh Raval (28:03):

Okay.

Ganesh Iyer (28:04):

Okay.

Brijesh Raval (28:04):

I think we can give some time back. Thank you very much guys.