Karen White joined RMS as CEO in March 2018, followed closely by Moe Khosravy, general manager of software and platform activities. EXPOSURE talks to both, along with Mohsen Rahnama, chief risk modeling officer and one of the firm’s most long-standing team members, about their collective vision for the company, innovation, transformation and technology in risk management
Karen and Moe, what was it that sparked your interest in joining RMS?
Karen: What initially got me excited was the strength of the hand we have to play here and the fact that the insurance sector is at a very interesting time in its evolution. The team is fantastic — one of the most extraordinary groups of talent I have come across. At our core, we have hundreds of Ph.D.s, superb modelers and scientists, surrounded by top engineers, and computer and data scientists.
I firmly believe no other modeling firm holds a candle to the quality of leadership and depth and breadth of intellectual property at RMS. We are years ahead of our competitors in terms of the products we deliver.
Moe: For me, what can I say? When Karen calls with an idea it’s very hard to say no! However, when she called about the RMS opportunity, I hadn’t ever considered working in the insurance sector.
My eureka moment came when I looked at the industry’s challenges and the technology available to tackle them. I realized that this wasn’t simply a cat modeling property insurance play, but was much more expansive. If you generalize the notion of risk and loss, the potential of what we are working on and the value to the insurance sector becomes much greater.
I thought about the technologies entering the sector and how new developments on the AI [artificial intelligence] and machine learning front could vastly expand current analytical capabilities. I also began to consider how such technologies could transform the sector’s cost base. In the end, the decision to join RMS was pretty straightforward.
“Developments such as AI and machine learning are not fairy dust to sprinkle on the industry’s problems”
Karen: The industry itself is reaching a eureka moment, which is precisely where I love to be. It is at a transformational tipping point — the technology is available to enable this transformation and the industry is compelled to undertake it.
I’ve always sought to enter markets at this critical point. When I joined Oracle in the 1990s, the business world was at a transformational point — moving from client-server computing to Internet computing. This has brought about many of the huge changes we have seen in business infrastructure since, so I had a bird’s-eye view of what was a truly extraordinary market shift coupled with a technology shift.
That experience made me realize how an architectural shift coupled with a market shift can create immense forward momentum. If the technology can’t support the vision, or if the challenges or opportunities aren’t compelling enough, then you won’t see that level of change occur.
Do (re)insurers recognize the need to change and are they willing to make the digital transition required?
Karen: I absolutely think so. There are incredible market pressures to become more efficient, assess risks more effectively, improve loss ratios, achieve better business outcomes and introduce more beneficial ways of capitalizing risk.
You also have numerous new opportunities emerging. New perils, new products and new ways of delivering those products that have huge potential to fuel growth. These can be accelerated not just by market dynamics but also by a smart embrace of new technologies and digital transformation.
Mohsen: Twenty-five years ago when we began building models at RMS, practitioners simply had no effective means of assessing risk. So, the adoption of model technology was a relatively simple step. Today, the extreme levels of competition are making the ability to differentiate risk at a much more granular level a critical factor, and our model advances are enabling that.
In tandem, many of the Silicon Valley technologies have the potential to greatly enhance efficiency, improve processing power, minimize cost, boost speed to market, enable the development of new products, and positively impact every part of the insurance workflow.
Data is the primary asset of our industry — it is the source of every risk decision, and every risk is itself an opportunity. The amount of data is increasing exponentially, and we can now capture more information much faster than ever before, and analyze it with much greater accuracy to enable better decisions. It is clear that the potential is there to change our industry in a positive way.
The industry is renowned for being risk averse. Is it ready to adopt the new technologies that this transformation requires?
Karen: The risk of doing nothing given current market and technology developments is far greater than that of embracing emerging tech to enable new opportunities and improve cost structures, even though there are bound to be some bumps in the road.
I understand the change management can be daunting. But many of the technologies RMS is leveraging to help clients improve price performance and model execution are not new. AI, the Cloud and machine learning are already tried and trusted, and the insurance market will benefit from the lessons other industries have learned as it integrates these technologies.
“The sector is not yet attracting the kind of talent that is attracted to firms such as Google, Microsoft or Amazon — and it needs to”
EVP, Software and Platform, RMS
Moe: Making the necessary changes will challenge the perceived risk-averse nature of the insurance market as it will require new ground to be broken. However, if we can clearly show how these capabilities can help companies be measurably more productive and achieve demonstrable business gains, then the market will be more receptive to new user experiences.
Mohsen: The performance gains that technology is introducing are immense. A few years ago, we were using computation fluid dynamics to model storm surge. We were conducting the analysis through CPU [central processing unit] microprocessors, which was taking weeks. With the advent of GPU [graphics processing unit] microprocessors, we can carry out the same level of analysis in hours.
When you add the supercomputing capabilities possible in the Cloud, which has enabled us to deliver HD-resolution models to our clients — in particular for flood, which requires a high-gradient hazard model to differentiate risk effectively — it has enhanced productivity significantly and in tandem price performance.
Is an industry used to incremental change able to accept the stepwise change technology can introduce?
Karen: Radical change often happens in increments. The change from client-server to Internet computing did not happen overnight, but was an incremental change that came in waves and enabled powerful market shifts.
Amazon is a good example of market leadership out of digital transformation. It launched in 1994 as an online bookstore in a mature, relatively sleepy industry. It evolved into broad e-commerce and again with the introduction of Cloud services when it launched AWS [Amazon Web Services] 12 years ago — now a US$17 billion business that has disrupted the computer industry and is a huge portion of its profit. Amazon has total revenue of US$178 billion from nothing over 25 years, having disrupted the retail sector.
Retail consumption has changed dramatically, but I can still go shopping on London’s Oxford Street and about 90 percent of retail is still offline. My point is, things do change incrementally but standing still is not a great option when technology-fueled market dynamics are underway. Getting out in front can be enormously rewarding and create new leadership.
However, we must recognize that how we introduce technology must be driven by the challenges it is being introduced to address. I am already hearing people talk about developments such as AI, machine learning and neural networks as if they are fairy dust to sprinkle on the industry’s problems. That is not how this transformation process works.
How are you approaching the challenges that this transformation poses?
Karen: At RMS, we start by understanding the challenges and opportunities from our customers’ perspectives and then look at what value we can bring that we have not brought before. Only then can we look at how we deliver the required solution.
Moe: It’s about having an “outward-in” perspective. We have amazing technology expertise across modeling, computer science and data science, but to deploy that effectively we must listen to what the market wants.
We know that many companies are operating multiple disparate systems within their networks that have simply been built upon again and again. So, we must look at harnessing technology to change that, because where you have islands of data, applications and analysis, you lose fidelity, time and insight and costs rise.
Moe: While there is a commonality of purpose spanning insurers, reinsurers and brokers, every organization is different. At RMS, we must incorporate that into our software and our platforms. There is no one-size-fits-all and we can’t force everyone to go down the same analytical path.
That’s why we are adopting a more modular approach in terms of our software. Whether the focus is portfolio management or underwriting decision-making, it’s about choosing those modules that best meet your needs.
“Data is the primary asset of our industry — it is the source of every risk decision, and every risk is itself an opportunity”
Mohsen Rahmana, PhD
Chief Risk Modeling Officer, RMS
Mohsen: When constructing models, we focus on how we can bring the right technology to solve the specific problems our clients have. This requires a huge amount of critical thinking to bring the best solution to market.
How strong is the talent base that is helping to deliver this level of capability?
Mohsen: RMS is extremely fortunate to have such a fantastic array of talent. This caliber of expertise is what helps set us apart from competitors, enabling us to push boundaries and advance our modeling capabilities at the speed we are.
Recently, we have set up teams of modelers and data and computer scientists tasked with developing a range of innovations. It’s fantastic having this depth of talent, and when you create an environment in which innovative minds can thrive you quickly reap the rewards — and that is what we are seeing. In fact, I have seen more innovation at RMS in the last six months than over the past several years.
Moe: I would add though that the sector is not yet attracting the kind of talent seen at firms such as Google, Microsoft or Amazon, and it needs to. These companies are either large-scale customer-service providers capitalizing on big data platforms and leading-edge machine-learning techniques to achieve the scale, simplicity and flexibility their customers demand, or enterprises actually building these core platforms themselves.
When you bring new blood into an organization or industry, you generate new ideas that challenge current thinking and practices, from the user interface to the underlying platform or the cost of performance. We need to do a better PR job as a technology sector. The best and brightest people in most cases just want the greatest problems to tackle — and we have a ton of those in our industry.
Karen: The critical component of any successful team is a balance of complementary skills and capabilities focused on having a high impact on an interesting set of challenges. If you get that dynamic right, then that combination of different lenses correctly aligned brings real clarity to what you are trying to achieve and how to achieve it.
I firmly believe at RMS we have that balance. If you look at the skills, experience and backgrounds of Moe, Mohsen and myself, for example, they couldn’t be more different. Bringing Moe and Mohsen together, however, has quickly sparked great and different thinking. They work incredibly well together despite their vastly different technical focus and career paths. In fact, we refer to them as the “Moe-Moes” and made them matching inscribed giant chain necklaces and presented them at an all-hands meeting recently.
Moe: Some of the ideas we generate during our discussions and with other members of the modeling team are incredibly powerful. What’s possible here at RMS we would never have been able to even consider before we started working together.
Mohsen: Moe’s vast experience of building platforms at companies such as HP, Intel and Microsoft is a great addition to our capabilities. Karen brings a history of innovation and building market platforms with the discipline and the focus we need to deliver on the vision we are creating. If you look at the huge amount we have been able to achieve in the months that she has been at RMS, that is a testament to the clear direction we now have.
Karen: While we do come from very different backgrounds, we share a very well-defined culture. We care deeply about our clients and their needs. We challenge ourselves every day to innovate to meet those needs, while at the same time maintaining a hell-bent pragmatism to ensure we deliver.
Mohsen: To achieve what we have set out to achieve requires harmony. It requires a clear vision, the scientific know-how, the drive to learn more, the ability to innovate and the technology to deliver — all working in harmony.
Karen White is an accomplished leader in the technology industry, with a 25-year track record of leading, innovating and scaling global technology businesses. She started her career in Silicon Valley in 1993 as a senior executive at Oracle. Most recently, Karen was president and COO at Addepar, a leading fintech company serving the investment management industry with data and analytics solutions.
Moe Khosravy (center) has over 20 years of software innovation experience delivering enterprise-grade products and platforms differentiated by data science, powerful analytics and applied machine learning to help transform industries. Most recently he was vice president of software at HP Inc., supporting hundreds of millions of connected devices and clients.
Mohsen Rahnama leads a global team of accomplished scientists, engineers and product managers responsible for the development and delivery of all RMS catastrophe models and data. During his 20 years at RMS, he has been a dedicated, hands-on leader of the largest team of catastrophe modeling professionals in the industry.