Q&A with Alastair Speare-Cole, President of Insurance at QOMPLX

Media 7 | August 20, 2021

Alastair Speare-Cole, President and General Manager of the Insurance Division at QOMPLX, leads the overall strategy for the business unit, the development of QOMPLX’s underwriting-as-a-service platform, the management of the company’s Managing General Agent (MGA), as well as setting the direction for the company’s next-generation insurance decision platform that leverages a wide variety of data and advanced analytics to provide advanced risk and portfolio management solutions. Prior to joining QOMPLX, he served as Chief Underwriting Officer at Qatar, and he served as the CEO of JLT Towers from 2012 to 2015. He was also COO at Aon Re for ten years and has also held board appointments at reinsurance and banking subsidiaries in the United Kingdom.

Over the span of my career, I have seen this industry move from crude and manual deterministic models to stochastic models, SAAS actuarial tools, catastrophe modeling, and entity-level capital modeling.



MEDIA 7: Can you please tell us a little bit about yourself and your professional career?
ALASTAIR SPEARE-COLE:
I have spent much of my career involved in reinsurance where portfolios of risk are analyzed and traded. Over the span of my career, I have seen this industry move from crude and manual deterministic models to stochastic models, SAAS actuarial tools, catastrophe modeling, and entity-level capital modeling. And so, my career has shadowed this trajectory. Especially in the eighties, when I was involved in designing and building some of the early models.


M7: QOMPLX has recently partnered with COMBUS. What does this partnership bring to the table?
ASC:
I have long been a fan of COMBUS and Will Gardner, whom I have worked with in the past. The insurance industry has become reliant on too few dominant models. Models as we have seen in recent months over COVID-19 approximate reality but are always just that, an approximation. And it should be no surprise that their limitations show differences between what is predicted and what actually happens. One strategy to combat this is to have multiple ways of modeling the same thing. The insight gained from different views is key to developing a better understanding. The success of COMBUS and other independent modeling companies is vital to creating a diversity of views and our aim is to try to make them more easily accessible and integrable into insurers’ and reinsurers’ platforms.


Models as we have seen in recent months over COVID-19 approximate reality but are always just that, an approximation. And it should be no surprise that their limitations show differences between what is predicted and what actually happens.



M7: How do QOMPLX’s Insurance products help businesses overcome the problems in the insurance value chain?
ASC:
There has been an arms race going on within the insurance industry around gathering and using data for risk selection, risk pricing, and getting clients through the front door. Everyone wants faster insight and the ability to make faster decisions. Our concept is to provide people with a Lego kit of enterprise-grade software that will help them link everything together- from ingestion, organization, storage, and analysis for structured and unstructured data, co-integrated with insurance-specific workflow solutions built on a common underlying data fabric to delivering an edge in decision making, risk selection, and loss control.


M7: What are some of the challenges in risk management in the post-COVID-19 era?
ASC:
Business interruption has been an increasing concern for all risk managers, not just those who worry about the ‘just-in-time’ process and supply chain. COVID-19 has demonstrated that the business interruption coverage offered by insurers is often poorly constructed, not tailored to a world where intangible assets are as valuable as tangible and where there are some risks that are so systemic that only governments can cope with the accumulation of tail risk.


There has been an arms race going on within the insurance industry around gathering and using data for risk selection, risk pricing, and getting clients through the front door. Everyone wants faster insight and the ability to make faster decisions.



M7: What do you see as the future of InsurTech? How is QOMPLX contributing to its growth?
ASC:
There is a huge wave of investment in InsurTech. Whilst the ideas these startups encapsulate may inspire permanent evolution of insurance, as individual businesses many will fail. Tackling a small slice on an insured’s risk, however originally done, is not going to work if the results in insured having to buy dozens of niche products that still leave gaps. Insurers will not continue to support InsurTechs that cannot build scale and scaling means distribution which is expensive. And most InsurTechs like to build their own software when they could adapt off-the-shelf products. And this means that much of their seed money goes on this which is inessential, rather than distribution which is crucial. We are looking hard at ways of working with other partners to allow people who have a great idea to take it to market, rather than trying to build a standalone business which may saddle the idea with costs that it cannot afford.


M7: What is the best advice you’ve received?
ASC:
I think it is encapsulated by Kipling’s poem “If.”

ABOUT QOMPLX

QOMPLX helps organizations make intelligent business decisions and better manage risk through our advanced, proprietary risk cloud. We are the leaders at rapidly ingesting, transforming, and contextualizing large, complex, and disparate data sources through our cloud-native data factory in order to help organizations better quantify, model, and predict risk. Our specialized experts and technology solutions in cybersecurity, insurance, and finance power leading global corporations and mission-critical public sector agencies.

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QOMPLX helps organizations make intelligent business decisions and better manage risk through our advanced, proprietary risk cloud. We are the leaders at rapidly ingesting, transforming, and contextualizing large, complex, and disparate data sources through our cloud-native data factory in order to ...

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