‘Location element is critical in insurance sector’

‘Location element is critical in insurance sector’

Tony Boobier , Insurance Leader EMEA, IBM Business Analytics, United Kingdom
Tony Boobier , Insurance Leader EMEA, IBM Business Analytics, United Kingdom

GIS is an important element in analytics, says Tony Boobier, Insurance Leader EMEA, IBM Business Analytics, as he goes on to explain how location and analytics are needed at each and every step of the insurance industry lifecycle.

Tell us about the IBM business analytics solution. How does geospatial technology play a role?

The amount of data available to business users is increasing exponentially. ‘Big Data’ as it‘s now commonly known, is defined by its volume, variety, velocity and veracity. But data by itself has limitations, and analytics are critical to extract value from that data, and to give insight.

In 2008, IBM laid down a marker through the acquisition of Cognos to become an analytical leader and since then, we’ve made investments of $17 billion in over 30 analytical acquisitions, coupled with $7 billion in organic development. IBM’s analytical journey started in the business intelligence space, and extended into predictive analytics (the technological ability to anticipate what might happen in the future) and I’ve been lucky to have been part of that journey over the past 6 years. When I look back, this has definitely been one of the high spots of my 35 year career in the industry.

So as we’re continuing to push the analytical boundaries yet further, we have to find new ways to help the business user. IBM’s vision is to place analytics in the hands of decision makers at every level of the business, for maximum impact in their decision making. One way we are doing this is through coupling analytics with natural language. This means the business user can ask the computer a question in ordinary language, and get an answer without needing to depend on specialists, and have direct access to the entire ‘Big Data’ sea of information, in both its structured and unstructured forms. This isn’t like an advanced search engine, but something much cleverer.

Having just passed IBM’s 100th birthday in 2011, we’ve also remembered our roots by naming this new capability after IBM’s founder, Thomas Watson, so this new capability is known as ‘Watson Analytics’.

Our interest in location through geospatial technology is a key component of our thinking. IBM works closely with the GIS community and has special partnerships with the major GIS vendors – although we have the flexibility to deal with smaller specialists. We support events and professional bodies, and IBM even have an internal GIS Forum within our organisation where we share news and new ideas.

Everywhere means something to someone, and for that reason alone GIS has to be an important element in our thinking.

Insurance companies deal with a tremendous amount of data. How can they integrate Big Data analytics into their workflow?

The strategy of an insurance company should help them to think about the insights and outputs they need from the data – and from this they can start to prioritise their data needs, both in terms of quality and organisation.

An insurer primarily focussing on risk will have quite different needs to one focusing on customer growth. Similarly, the strategy of one of the major retail insurers will be quite different from a specialist insurer. However, the golden thread which connects all these different insurers and different needs is that location is critical to all of them.

In the insurance sector, risk management and Solvency II Regulation is a key issue. It’s all about ensuring that insurance companies have enough financial capital to meet its obligations. The location element to this area is mainly around excessive accumulation of risk by one insurer in one particular location, say a major city or port.

Another area is in the space of Customer Analytics where we use predictive customer intelligence to help us understand the demographics of the customer and also the risks associated with a particular location of the customer. For example, if you live in a flood zone then that would influence the decision of an insurance company whether it would make an offer of insurance or not, and at what price.

Analytics also helps in handling claims and in the supply chain management. Location intelligence helps the insurance company to understand which can be the best place to locate an auto bodyshop, where best to locate inspectors etc. Predictive analysis also helps in anticipating where claims are likely to appear. So you see, all these things have an analytical component and they all interact and interrelate with each other with a theme of location running through all of them.

With regards to embedding GIS in workflow, we are seeing analytics increasingly fuelling automatic processes, which improve accuracy, reduce cost, provide consistency and enhance customer service.

In the last few years, geoinformation systems have established themselves in the insurance industry more quickly than was anticipated a few years ago. Initially, these systems were largely used by reinsurers and modelling firms in the handling of property insurance risks. Today, geo-based solutions are used for a much broader spectrum, including primary insurers. Your comments?

Insurers increasingly understand not only the importance of analytics but also the importance of location. What’s changed is their understanding that they can effectively and successfully bring these two technologies together so that they are greater than the sum of the parts.

For many, the challenge has been that of implementation, but with insurers now have better understanding of how to embed these capabilities in an organisation, including GIS initiatives.

Location is becoming much more mainstream. Think telematics, for example. Think targeted marketing.

They are also looking for more expertise and want to hire more engineers and geographers in the insurance industry. Do you think this is needed?

One of the issues that we face is that analytics is growing quickly because of the growing amount of data. There is a skill shortage of analytics at a global level and companies are recognising the need to develop the talent. IBM is, for example, working with key universities to develop analytical qualifications and skills.

I spoke recently to a university, asking them to encourage their students to remember that GIS, or geo-analytics, is not the destination but rather as a way of providing insight to business users, and from which the business user can think about strategy and tactics. My bet is that we are soon to see a new breed of GIS expert, typically one that is also an expert in marketing, claims, or risk management. When GIS meets specialism with an industrial context, it becomes a very potent mix.

Do you see insurance companies increasing their investments related to data management?

Yes, traditionally insurance companies, and all organisations, have historically depended upon return on investment to prove the need to develop. But I think we’re at a turning point. Analytics is so pervasive and important to all organisations that I sense they are now making emotional decisions to invest in analytics rather than looking solely at a return on investment calculation to justify a decision. It’s a bit like buying a pair of shoes – most people have already decided that you need the shoes before going into the shoe shop, and I’m beginning to think analytics is reaching that point.

People are increasingly open to the need for analytics, and it’s still important for them to understand where the benefits will be. We see savings occurring through more effective capital management, better customer retention, reduction in claims fraud and other areas.

What is IBM’s strategy to educate insurance companies about the importance of Big Data analytics?

We are always talking to the insurance companies and sharing our insights. In the coming months I will be taking part in an insurance road show where I will speak to their younger members about big data and analytics. Professional bodies recognise the need to add to traditional learning by understanding the impact of new technology. At IBM we are constantly running events, both virtual and face-to-face, and publishing papers which give deep insight about the topic, and were delighted to recently host a major Association of Geographical Intelligence event attended by over 100 people.

At a personal level, beyond meeting and talking to people, I always try to have a point of view which – if anything – at least invites people to stop and think about what they are doing for a moment. I even recently suggested that GIS should reinvent itself as ‘Greater Information Solutions’ to get away from the purely geographical orientation. GIS is much more than geography nowadays.

Looking ahead, which according to you are the future application areas of Big Data analytics in insurance industry?

It’s staggering to think that very soon, an insurance executive will have the everyday ability to ask a question to a computer in natural language and for the computer to search all available information, and all databases globally and offer a suggested answer. Location is bound to feature in that answer. We’re already working with healthcare providers and are already trialling this with a major insurer in the States, and the results are looking good.

The intention is not to replace experience and intuition with technology, but to supplement it. There’s so much information available today that it’s beginning to be a problem where to look to find answers. Technology has always been a great enabler, it was never a threat. It has continued to transform the insurance industry and will carry on doing so. As an industry, insurers have no choice but to absorb those changes and to work with them.