How Munich Re uses AI to Minimize Risk from Global Disasters

How Munich Re uses AI to Minimize Risk from Global Disasters
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Technology has proven to be highly useful when it is used in solving big problems. The occurrence of disasters including epidemics, natural disasters or even catastrophic events makes up one of the biggest problems affecting this world.

It is only in reaction to seismic events that prompt actions can alleviate a potentially bigger disaster and help severe conditions. This was the case witnessed in the emergence of the Hurricane Florence, which occurred recently.

The catastrophic event is known for its huge regional impact after striking the continental US as well as devastating the Carolinas not only with widespread damage and severe flooding.

Munich Reinsurance Company or otherwise known as Munich Re came to the rescue of business owners and devastated homeowners in the aftermath of Hurricane Florence.

The company has always done so in past disasters. For those not well verse with the reinsurance business, the role of reinsurance companies appears to be a mystery.

Munich Re was established back in 1880 and operates from its headquarters in Munich, Germany. Warren Buffet, among the richest individuals in the world, was one of the biggest shareholder of the company for many years and to date, he remains a considerable shareholder.

Being among the biggest reinsurance companies globally, Munich Re delivers insurance commodities to insurance entities in a bid to assist in mitigating the risk of high impact calamities.

These catastrophes produce acute capital demands on insurers to cover property losses and payouts in a responsive and timely manner. Reinsurers such as Munich Re can aid key insurers during periods of crisis by assisting insuring part of the risk.

Wolfgang Hauner, the Munich Re Chief Data Officer, said: “For the average person, you only value insurance when you have a loss”. He also added that it is the event of the largest losses whereby Munich Re shows its true might.

Also, it is during such a period where data innovation and technology come into play. In fact, Munich Re has been striving to create and improve its data analytics and data engineering capabilities in expectation of calamities.

These endeavors have comprised the use of image classification algorithms that depend on AI for assessing the severity of damage, generate automated and immediate damage estimates, and expedite eagerly needed damage payouts.

Munich Re applies remote sensing gadgets for capturing high-resolution images, particularly those of property damage, which are included into an artificial intelligence engine that is backed by sophisticated Machine Learning algorithms.

In turn, the company can assist clients through catastrophes with a fast response to damage evaluation that converts what was previously a complete manual process into an automated one that boosts efficiency and productivity, minimizes cost as well as leads to improved customer loyalty and satisfaction.

Munich Re has also ventured into projects that include image classification using artificial intelligence. The company’s Chief Data Officer Hauner describes Munich Re ’s journey to use analytics and data in a facilitating business innovation.

According to him, the journey marks an evolutionary process, which has been ongoing for some years now. Back in 2015, Munich Re rolled out an Advanced Analytics team to build a central hub of both analytics and data capabilities and skills.

At the start of 2016, the role of chief data officer was created under Hunter’s leadership. Currently, the officer of the CDO has key responsibility for three main operations:

  1. Artificial intelligence (AI), this is where top edge technologies are used in text analytics, image classification among other unstructured data problems.
  2. Data engineering, it includes data governance, ownership for the global data and analytics platform and management of the data lake.
  3. Analytics, it mainly focuses on the development of complex analytics, most of which are applied for one-time use, while the others result in analytical software products.

Hauner described a fourth area that is currently under development in a bid to concentrate on Analytics Operations. This area is expected to be the process by which models will be maintained by their lifespan.

The function of Analytics Operations will be to maintain and run such models in a highly operational manner that is based outside Munich.

As a global enterprise, Munich Re is well aware of the importance of decentralization. To avert business challenges, the company is on track to offer larger regional proximity, particularly to its customers.

For instance, Munich Re is involved in parallel hiring endeavors for both data science and analytics specialists in the regional market.

The company is doing this in recognition that it is easier to compete and recruit limited analytic talent, particularly in a decentralized manner, as opposed to hiring many individuals in one market.

Reinsurance is a sophisticated and extremely impactful enterprise. Hauner describes the features of Munich Re customers as well as the levels of servicing needed for meeting their requirements.

High-frequency, high-value clients gain from Munich Re ’s artificial intelligence (AI) image classification project because the magnitude is widespread, the timeframe is immediate and the need is great.

In turn, the recovery process, particularly for property owners, reduces from months to several days.

Munich Re is also seeking to bring similar advanced AI capabilities in a bid to allow smaller insurers to reach the same positive client impact without the need for financing and developing these complex AI and data capabilities.

The company offers this functionality primarily to insurers in a services model.

Finally, Munich Re backs high-frequency, low-value projects such as compensating and identifying clients for flight delays, via detecting weather patterns, which correlate to the probability and risk of flight delay.

An example of this is Munich Re’s flight delay insurance, which is offered by the company’s customer in China. The insurance product is assisting in the insurance of nearly 50 million air travels out of almost 500 million annual air travels in China only at an average premium of 20 Yuan or less than $3 for a single policy.

Moreover, AI weather patterns predictability is expected to become increasingly important, especially looking at the rapid climate change today.

Munich Re is moving forward with its innovation and data journey. However, it is aware that additional progress is needed. Hauner said, “We are so far perhaps 40% of the way there”.

Munich Re has developed a data ecosystem backed by software tools like those offered by Alation for managing the data lake. The Alation tools allow the company to move their data lake to allow data scientists and analysts to work together with their data.

What’s more, the tools offer a central point for searching for and accessing data. Hauner stated, “This helps us break down organizational silos. We are able to think differently. Data sources provide value across the organization. We are able to understand who is using data, in addition to our own units”.

It is undeniable that Munich Re is leveraging artificial intelligence and data in an attempt to meet the requirements of an ever-changing world while assuming the risks.

In conclusion, Hauner said, “Catastrophic events tend to be cyclical. We and our customers are encountering more frequent and evolving risks. These risks require great solutions. We look to leverage great technologies, while we focus on what we do best – the management of risk-taking and providing policy solutions”.

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