Knowledge Power: Beyond Intuition
The new crystal ball in risk prediction is data analysis, and our XL wizards help businesses project their vision to protect their properties all over the world.
The Sprinkler Revolutionized Fire Fighting
To protect his piano factory in New Haven, Connecticut, Henry Parmalee invented the automatic fire-sprinkler system in 1874.
It was a huge step forward for fire suppression, sparing countless human lives, and minimizing the intervention of firefighters.
A railway president and shrewd businessman, Mr. Parmalee immediately set out to market the sprinkler system to insurance companies throughout the US and England.
Insurers were thrilled. Automatic fire suppression resulted in far more effective fire protection standards, leading to the development of Highly Protected Risk (HPR) property insurance.
A few insurers decided to focus exclusively on offering this new HPR property insurance at low, mass-market premiums. Other carriers simply offered substantial rebates to clients who took advantage of the automatic sprinklers.
The HPR business model now includes thousands of well-known risks and remains highly successful in protecting properties.
Nobody expects multinational firms, with offices and factories all over the world, to be intimate with the array of potential hazards to individual properties in each and every country or province.
Companies can generally afford to provide preliminary risk analyses of their high-value properties. Insurance loss prevention consultants then audit those principal properties and advise clients on optimal risk-prevention measures.
Seamless, fast-paced business service is the global standard. Yet the flames of a factory fire in rural India, even where the workers manage to escape unscathed, can temporarily disrupt the supply chain. Millions are lost in an instant, shares plummet, and it is a long road to recovery.
It is easy to skim over smaller properties in remote destinations, but low property value does not necessarily correspond to low supply-chain value. On the contrary, such properties often comprise critical segments in the supply chain, and they merit closer attention.
Intuition as the Chief Deciding Factor is Obsolete
“Having a head for business” used to mean possessing an intuitive savvy, a “gut feeling” for how to strike a deal. It was an evolved skill.
The Hominidae (great apes) appeared on the earth 20 million years ago, and 2.3 million years ago, the homo genus branched off, but the modern human (homo sapiens) only emerged 200,000 years ago.
This means that 20 million years of instinctual survival, pattern recognition, and split-second decision making have been hardwired into the human brain. In comparison, humans have enjoyed the higher cognitive aptitude for complex calculations and long-term planning for a mere 200,000 years.
Now technology is rocketing past our capacity to absorb and process information, as mounting layers of data are heaped onto our desks.
We can no longer make superior decisions based solely on intuition or experience, the result of slowly evolved pattern recognition. There are too many patterns to follow, and a single human, even a team of humans, cannot be relied on to sift through thousands of data points in the few seconds or minutes required by a computer.
That is why data wizards are taking center stage in assessing and pricing risk.
The Data Crystal Ball
Today’s wizards don’t gaze into crystal balls to see far and wide.
Instead they project their sight beyond human bounds by amassing gargantuan piles of data, and then processing them with ever more sophisticated computational systems.
Multinational manufacturers need to know about more than just fixed fire protection and non-combustion construction. Severe weather events, complex supply chains, and a continuously evolving business environment converge to form a property risk data maelstrom.
Our property loss-prevention service organization, XL GAPS, has developed an online reporting tool which offers clients a full overview of the property risks across an entire portfolio.
If data could be weighted, the XL Gaps crystal ball would contain virtual tons of data, exponentially increasing each year.
Where Do We Get It?
First, we encourage clients to glean data from every possible internal source, including Environment, Health, and Safety (EHS), purchasing, HR, production, and so on. Of course the next level of data is supplied by our property auditors.
Our customers and visiting risk engineers are also beginning to add another layer of data, using smart phones and other mobile devices to collect information on the spot, instantly updating data for ongoing risk calculation.
The XL Group companies have funneled this data, along with an in-depth, quantified knowledge of specific property risks, into the development of meticulous analytical methodologies, enhanced and accelerated by technological advances.
Our data models unearth correlations between risk factors and isolate loss drivers, so that we can craft a custom loss-prevention plan and accurately price the risk safety net for each client.
In the words of Greg Hendrick, CEO of the XL Group insurance operations: “These days we collect vast amounts of data from all over the world and from every conceivable source, including clients and third-party specialists. As technology evolves, we use the data to fuel increasingly precise analytics.
“This data structuring has enabled us to build predictive models to help identify patterns, trends and future scenarios more accurately. The insights we gain help our clients overcome the challenge of operating in a global theater.”
Still Wanted: The Human Factor
Are we at another historical turning point in the way property insurers define their risk quality? When the HPR market was founded, the focus shifted from human intervention to automatic fire suppression.
Is it time to take the human factor out of the underwriting process altogether, and simply run available data through tools to develop premiums for complex industrial risks? Certainly not!
Humans collect the data, for one, and human intuition is indispensable to interpreting it.
But the face of underwriting is transforming. The underwriters of the future will have to be more data-minded, as constantly changing global data requires agile and exact analysis, and the risk picture evolves more rapidly.
Underwriting Intuition will provide the clues to hunting and collecting data, and the experiential filters to apply data insights for the greatest benefit.