Author Archives: EXPOSURE magazine

About EXPOSURE magazine

EXPOSURE magazine from RMS is an essential briefing for catastrophe and risk management professionals who want to explore the latest opinions from the industry, new opportunities, and best practice to help their organization thrive in an increasingly competitive and disruptive market.

EXPOSURE Magazine Snapshots: Water Security – Managing the Next Financial Shock

This is a taster of an article published by RMS in the second edition of EXPOSURE magazine.  Click here and download your full copy now.

18 Apr 2017 Exposure Drought image

 

EXPOSURE magazine reported on how a pilot project to stress test banks’ exposure to drought could hold the key to future economic resilience, as recognition grows that environmental stress testing is a crucial instrument to ensure a sustainable financial system.

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EXPOSURE Magazine Snapshots: A New Way of Learning

This is a taster of an article published by RMS in the second edition of EXPOSURE magazine.  Click here and download your full copy now.

7 Apr 2017 - Machine Learning blog - Exposure banner image 720 x 168

 

In EXPOSURE magazine, we delved into the algorithmic depths of machine learning to better understand the data potential that it offers the insurance industry.  In the article, Peter Hahn, head of predictive analytics at Zurich North America illustrated how pattern recognition sits at the core of current machine learning. How do machines learn?  Peter compares it to how a child is taught to differentiate between similar animals; a machine would “learn” by viewing numerous different pictures of the animals, which are clearly tagged, again and again.

Hahn comments “Over time, the machine intuitively forms a pattern recognition that allows them to tell a tiger from, say, a leopard. You can’t predefine a set of rules to categorize every animal, but through pattern recognition you learn what the differences are.”

Hahn adds that pattern recognition is already a part of how underwriters assess a risk. “A decision-making process will obviously involve traditional, codified analytical processes, but it will also include sophisticated pattern recognition based on their experiences of similar companies operating in similar fields with similar constraints. They essentially know what this type of risk ‘looks like’ intuitively.”

The Potential of Machine Learning

EXPOSURE magazine asked Christos Mitas, vice president of model development at RMS, on how he sees machine learning being used.  Mitas opened the discussion saying “We are now operating in a world where that data is expanding exponentially, and machine learning is one tool that will help us to harness that.”

Here are three areas where Mitas believes machine learning will make an impact:

Cyber Risk Modeling: Mitas adds “Where machine learning can play an important role here is in helping us tackle the complexity of this risk. Being able to collect and digest more effectively the immense volumes of data which have been harvested from numerous online sources and datasets will yield a significant advantage.”

Image Processing: “With developments in machine learning, for example, we might be able to introduce new data sources into our processing capabilities and make it a faster and more automated data management process to access images in the aftermath of a disaster. Further, we might be able to apply machine learning algorithms to analyze building damage post event to support speedier loss assessment processes.”

Natural Language Processing: “Advances here could also help tremendously in claims processing and exposure management,” Mitas adds, “where you have to consume reams of reports, images and facts rather than structured data. That is where algorithms can really deliver a different scale of potential solutions.”

For the full article and more insight for the insurance industry, click here and download your full copy of EXPOSURE magazine now.

For more information on RMS(one)®, a big data and analytics platform built from the ground-up for the insurance industry, and solutions such as Risk Modeler and Exposure Manager, please click here.

EXPOSURE Magazine Snapshots: Evolution of the Insurer DNA

This is a taster of an article published in the second edition of EXPOSURE magazine.  Click here and download your full copy now.

6 Apr 2017 - Evolution of Insurer DNA blog image banner 720 x 168Many in (re)insurance recognize that the industry is at a tipping point. Rapid technological change, disruption through new, more efficient forms of capital, and an evolving risk landscape are challenging industry incumbents like never before. EXPOSURE magazine reported that inevitably the winners will be those who find ways to harmonize analytics, technology, industry innovation, and modeling.

“Disruptive innovation” is increasingly obvious in areas such as personal lines insurance, with disintermediation, the rise of aggregator websites and the Internet of Things (IoT).  In the commercial insurance and reinsurance space, disruptive technological change has been less obvious, but behind the scenes the industry is undergoing some fundamental changes.

The tipping point, the “Uber” moment has yet to arrive in reinsurance, according to Michael Steel, global head of solutions at RMS. “­The change we’re seeing in the industry is constant. We’re seeing disruption throughout the entire insurance journey. It’s not the case that the industry is suffering from a short-term correction and then the market will go back to the way it has done business previously. ­ The industry is under huge competitive pressures and the change we’re seeing is permanent and it will be continuous over time.”

While it is impossible to predict exactly how the industry will evolve going forward, it is evident that tomorrow’s leading (re)insurance companies will share certain attributes. ­ This includes a strong appetite to harness data and invest in new technology and analytics capabilities, the drive to differentiate and design new products and services, and the ability to collaborate. According to Eric Yau, general manager of software at RMS, the goal of an analytic-driven organization is to leverage the right technologies to bring data, workflow and business analytics together to continuously drive more informed, timely and collaborative decision making across the enterprise.

“New technologies play a key role and while there are many choices with the rise of insurtech firms, history shows us that success is achieved only when the proper due diligence is done to really understand and assess how these technologies enable the longer-term business strategy, goals and objectives.” says Yau. Yau also believes that one of the most important ingredients to success is the ability to effectively blend the right team of technologists, data scientists and domain experts who can work together to understand and deliver upon these key objectives.

Looking for Success in this New World

Which factors will help companies stand out and compete in the future?  EXPOSURE asked industry experts for their views on the attributes that winning companies will share:

The Race for Millennial Talent:  The most successful companies will look to attract and retain the best talent, says Rupert Swallow, co-founder and CEO of Capsicum Re, with succession planning that puts a strong emphasis on bringing Millennials up through the ranks. “­There is a huge difference between the way Millennials look at the workplace and live their lives, versus industry professionals born in the 1960s or 1970s — the two generations are completely different,” says Swallow. “­ Those guys [Millennials] would no sooner write a check to pay for something than fly to the moon.”

Collaboration is the Key: There are numerous examples of tie-ups between (re)insurance industry incumbents and tech firms, to leverage technology – or insurtech – expertise, to get closer to the original risk. ­ One example of a strategic collaboration is MGA Attune, set up last year by AIG, Hamilton Insurance Group, and affiliates of Two Sigma Investments. ­ Through the partnership, AIG gained access to Two Sigma’s vast technology and data-science capabilities to grow its market share in the U.S. small to mid-sized commercial insurance space.

Blockchain:  Blockchain offers huge potential to reduce some of the significant administrative burdens in the industry, thinks Kurt Karl, chief economist at Swiss Re. “Blockchain for the reinsurance space is an efficiency tool. And if we all get more efficient, you are able to increase insurability because your prices come down, and you can have more affordable reinsurance and therefore more affordable insurance. So I think we all win if it’s a cost saving for the industry.”

“­The challenge for the industry is to remain relevant to our customers,” says RMS’ Michael Steel. “­Those that fail to adapt will get left behind. To succeed you’re going to need greater information about the underlying risk, the ability to package the risk in a different way, to select the appropriate risks, differentiate more, and construct better portfolios.”

For the full article and more insight for the insurance industry, click here and download your full copy of EXPOSURE magazine now.

Watch Video: Eric Yau – Managing Risk is an Interconnected Process

Eric Yau, general manager, software business unit at RMS, said those managing risk should keep in mind that risk selection is part of an overall process that affects capacity and portfolio strategy. Yau spoke with A.M. BestTV at the Exceedance 2017 conference.

For more information on RMS(one)®, a big data and analytics platform built from the ground-up for the insurance industry, and solutions such as Risk Modeler and Exposure Manager, please click here.

EXPOSURE Magazine Snapshots: The Analytics Driven Organization

This is a taster of an article published in the second edition of EXPOSURE magazine.  Click here and download your full copy now.5 Apr 2017 - Exposure Analytics Org image with Exposure masthead

Farhana Alarakhiya, vice president, products at RMS, writes… In my recent article in EXPOSURE magazine, I was interested in exploring how firms in the insurance sector can move towards building a more analytics-driven organization.  Being analytics-driven translates to being an agile business, and in a turbulent market landscape, building underwriting agility is becoming critical to business survival.

There is no doubt we have seen revolutionary technological advances and an explosion of new digital data sources, which has reinvented the core disciplines of insurers over the past 15 years.  Many (re)insurers also see big data and analytics (BD&A) as a “silver bullet” to provide competitive advantage and address their current market challenges.

Similar to other industries who continue to invest heavily in BD&A to secure their position and open a new chapter of growth, the insurance sector is also ramping up investment, in open BD&A platforms such as RMS(one)®, which is purpose-built for the insurance industry.  But although there is a real buzz around BD&A, what may be lacking is a big data strategy specifically for evolving pricing, underwriting and risk selection, areas which provide huge potential gains for firms.

With the opportunity for our industry to gain transformational agility in analytics now within reach, we need to be conscious of how to avoid DRIP, being data rich, but information poor, with too much focus being on data capture, management, and structures, at the expense of creating useable insights that can be fed to the people at the point of impact.  Regulation is not the barrier to success either, many other regulated business areas have transformed their business and gained agility through effective analytics.

Please read the full article in EXPOSURE magazine to discover more about the three main lessons insurers can learn from other businesses who have their BD&A recipe just right, but here’s a short summary:

Lesson #1 – Delivering Analytics to the Point of Impact

Being reliant on back office processes for analytics is common for insurers, but doesn’t work for a frontline healthcare worker, for example.  Data analysts are rare in this sector, because a healthcare worker has analytics designed around their role, to support their delivery.  If you look at a portfolio manager in the insurance sector, they typically work in tandem with an analyst to get relevant data, let alone insight, which compromises their ability to perform effectively.

Lesson #2 – Ensuring Usability

Recognizing the workflow of an analytics user and giving due consideration to the veracity of the data provided to reduce uncertainty is vital. Looking at our healthcare example, analytics tools used by doctors to diagnose a patient’s condition use standardized information – age, sex, weight, height, ethnicity, address – and the patient’s symptoms.

They are provided not with a defined prognosis but a set of potential diagnoses accompanied by a probability score and the sources. Imagine this level of analytical capability provided in real-time at the point of underwriting, where the underwriter not only has access to the right set of analytics, they also have a clear understanding of other options and underlying assumptions.

Lesson #3 – Integration into the Common Workflow

To achieve data nirvana, BD&A output needs to integrate naturally into daily business-as-usual operations. When analytics are embedded directly into the daily workflow, there is a far higher success rate of it being put to effective use.  With customer service technology, all the required systems are directly integrated into the customer agents’ software for a holistic view of the customer.  Using platforms built and designed with open architecture allows legacy systems or your specific intellectual property-intensive processes to be integrated, for access to analytics that allow them to derive insights as part of the daily workflow for every risk they write.

This is a taster of an article published in the second edition of EXPOSURE magazine.  Click here and download your full copy now.

Watch Video: Farhana Alarakhiya – The Data Challenge Is Getting It to the Right People

Farhana Alarakhiya, vice president, products at RMS, said insurers are responding to the allure of big data, but must focus on turning voluminous data into meaningful insights. Alarakhiya spoke with A.M. BestTV at the Exceedance 2017 conference.

For more information of RMS(one)®, a big data and analytics platform built from the ground-up for the insurance industry, and solutions such as Risk Modeler and Exposure Manager, please click here.