May 1, 2014

Leveraging Real-world and Risk Neutral ESG solutions within Insurance

 

 

In this video blog, Alex Marion, VP of Product Management for Insurance speaks with CMO, Jim Jockle about practical use cases for Economic Scenario Generation in today’s Insurance marketplace. Alex addresses how real-world ESG solutions are being leveraged to project forward liabilities for economic capital applications, as well as risk neutral ESGs for the pricing and hedging of embedded derivatives within insurance products.

Alex describes how insurance companies are increasingly looking to leverage consistent modelling for building out an effective nested stochastic framework to overcome run time issues, andbetter manage “de-risking” within the variable annuity market.

Weigh in and continue the conversation on Twitter @nxanalyticsLinkedIn, or in the comments section.



Video Transcript: Leveraging Real-world and Risk Neutral ESG solutions within Insurance

Jim Jockle (Host): Hi welcome to Numerix Video Blog. I’m your host Jim Jockle. Joining me today is Alex Marion, VP of Product Management here at Numerix for insurance products. Alex how are you?   

Alex Marion (Guest): I’m great.  

Jockle: Alex last time we talked, we talked about trends in insurance companies and elements of onboarding new technologies. And bucking the trend of overseeing more on the banking side and the capital market side, where we’re starting to see a lot more outsourcing and investment. In insurance, we’re seeing insourcing. And one of the areas in particular is around economic scenario generation. Perhaps, first of all, could you give us a good definition of economic scenario generation? And then let’s talk about some of the trends of why insurance companies are starting to inboard new technologies.         

Marion: Sure. Well there are two dominant use cases of economic scenario generation technology in insurance companies. The first one, is risk neutral ESG’s. Which are risk neutral models which are models used for pricing and hedging, embedded derivatives in insurance products such as variable annuities or fixed index annuities. So, risk neutral dynamics are the absolute correct dynamics to use for valuing these embedded derivatives just like they would at banks.

The other use case is what they call real world or realistic scenario generation and under these, that have been around for a while in insurance companies and companies are now using a stochastic set of real world scenarios to project forward their liabilities for capital and reserving requirements. And they’re looking to do that on an enterprise wide platform so for things like AG 43 calculations, or risk based cap, or economic capital applications, they’re all using these real world ESG solutions to project forward their balance sheet across different lines of business.

Jockle: So we’ve also in annuity space have seen a lot of moving around in terms of people entering the business, people exiting the business, buying different books of business, what is a best practice as it relates to building these books after driven through lack of a better term acquisition.

Marion: Sure so there has been a lot of M&A activity in the insurance space, a lot of it has been about rebuilding capital positions and trying to decide how do we effectively deploy capital. So when risk managers in insurance executives are looking at the opportunities in a market they have to have the tools that help them turn data information into management decisions. What lines of business will I best deploy my capital to? What other lines of business should I be de-risking - are they consuming capital? And to do that they really need a consistent enterprise risk management framework across different products and different lines of business and economic scenario generators allow them to unify these different legacy cash flow systems and different valuation systems in the single consistent framework.

Jockle: So you’ve mentioned in essence – stochastic on stochastic issues. Which brings its own host of challenges in terms of deploying different hybrid models and moving away from more traditional – black and things of that nature. Tell me a little bit more about the onboarding’s of this type of technology and how equipped are these companies to maneuver more complex models.

Marion: Sure. So if you look at the variable annuity market or the fixed index market where these annuities have these embedded derivatives, a lot of companies are bringing their hedge programs in-house. Right, so they're dynamically hedging the embedded derivative risk whether its guaranteed minimum withdrawal benefits, other VA guarantees, or some of the fixed index annuity crediting strategies. When they do reserves calculations or hedge strategy projection on some of these businesses, they have to project forward that hedging strategy and to do that, they have to have an outer loop of realistic scenarios to project forward the business but they have to revalue those hedges and the liabilities at each interlope node along those real world paths.

So that’s the general framework of the nested stochastic problem and it can be very computationally intense. Now if you have a consistent modelling dynamic between your risk neutral models and your real world models, you can build out a nested stochastic framework that’s consistent, it’s defensible, and it’s optimized for computational run time. And a lot of companies now are looking to use cloud computing solutions to enhance their nested stochastic capabilities by overcoming some of the run time issues.

Jockle: And that’s more from an infrastructure as a server – burst to cloud?  

Marion: Sure. Right exactly.

Jockle: So one of the questions as a driver also the hedging programs themselves and the strategies being employed are becoming much more sophisticated.

Marion: Sure. For example in a variable annuity market, a lot of companies have been trying to move the hedging from the insurer back to the policy holder in the form of these risk managed funds. Whether they are managed vol strategies, or capital protection overlays, they’re farming out some of that risk, whether it’s vega risk, they’re moving into the funds. The funds are de-risking as the market goes down as volatility increases and that translates to a lower greek profile for some of the embedded guarantees, and a lower hedging cost. So, as part of the de-risking theme in the variable annuity market, this has been the central component of that is to move the guarantee derivative risk over to the policy holder in the form of these managed products.

Jockle: Well, Alex I’d like to thank you so much for your time today. And of course we’d like to talk about the topics that you’d like to talk about. So if you’re on twitter, please add us at @nxanalytics, or on LinkedIn to stay up to date for all the conversations that we have, whether it’s our webinar programs or events, or updates on our video blogs. So with that, I’m going to say thank you again Alex.

Marion: Thank you.

Jockle: And we’ll see you next time.

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