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“Analytics” is Plural for a Reason

The use of anlaytics to understand data is clearly a hot topic in the insurance community these days.  Those who have not taken steps to begin to use analytic tools are being warned that they are behind the curve already.  A recent white paper notes that successful implementation of an analytics program is a non-trivial exercise that involves multiple, interconnected activities, impacting most if not all parts of an insurance enterprise.

Our questions to you: Are you using or planning to use analytics and how will this impact your business?

What’s the big deal?

In the opening days of 2012, we identified data and analytics as a ‘megatrend’ for 2012,  writing: “As the soft market continues, leading insurance underwriters and distributors are pursuing intelligent data use as a high-priority competitive strategy.”

The significance of this trend was reinforced recently at the Insurance Brokers Association of Ontario (IBAO) Annual Convention, during the CEO panel.    As reported in CanadianUnderwriter.ca, Maurice Tulloch, CEO of Aviva Canada, said that other industries are “using analytics way more advanced than what we’re using, ” and added,  “I want everyone in this room to better compete. It (analytics) allows us to get proper pricing so that people actually get the right price for the right risk.”

 If analytics are so good, where to I get them?

You probably have a lot of the data, and can get access to the rest for an anlaytics implementation.  What you might be missing is how to get the information out of the data.

What Does Big Data Really Mean for Insurers?, a recent white paper authored by  SMA-Strategy Meets Action, and distributed by SAS,  notes that the use of analytics requires a disciplined approach that involves 3 interrelated  capabilities.

Two of the three components do not relate to technology, per se.  Some of the elements you can buy, some you have to develop.  All of the component need to be controlled. The white paper provides an excellent, business language description of each capability.  The following are excerpted from the white paper:

Master Data Management (MDM): “Data must be seen as the valuable corporate asset that it is, and be supported by comprehensive master data management (MDM). Good MDM consists of processes and tools to manage enterprise data, such that a high quality, consistent, and authoritative source of data exists. While MDM can be applied at the business unit level, the maximum benefit is gained when MDM is applied across the enterprise.”

Technology platform:  “What sets specialized high performance analytics platforms apart from the general- purpose systems is the ability to ingest billions of data records (representing terabytes of data), conduct sophisticated analytics, and produce a result in hours or minutes.”

Centre of excellence:  “The third leg of the stool is an analytics center of excellence, bringing together advanced technology skills and experience from inside and outside the organization. Insurers need to acquire, develop, and partner with individuals that have deep analytics talent. Understanding how to plan, implement, and interpret the results from high performance analytics programs is the key to success – and it requires experienced people.”

So, what’s your take?

SMA’s analysis suggests that proper implementation of analytics is a non-trivial, multi-faceted undertaking.  The CEO panel agreed, noting also that the sales agents (brokers) must be prepared to interpret the use of analytics to customers in everyday language.

Our specific questions to you are:  1) Do you see the need to use analytics in your business and 2) If so, what are your experiences, and 3) If not, what is your alternative?

Leave a comment below and make your voice count!

One Comment

Blair Currie

This is very interesting post because Big Data, Analytics and the subsequent Intelligence and Decision Making Ability are real competitive advantages for those who embrace them.

I’d like to return to the words of Maurice Tulloch, CEO of Aviva Canada who said other industries are using Analytics “way more advanced than we are using”. This is both an opportunity and a threat for the industry.

Opportunities of Analytics for the Insurance Industry
The opportunities include buying Analytics services from companies who are becoming adept at this art, to supplement their own actuarial skills and to ultimately bring this skill in-house. This is what Strategy Meets Action referred to in its comment about Centers of Excellence to bring together “advanced technology skills and experience from inside and outside the organization”.

Auto insurance example
Auto insurance is a big area where Analytics is entering the conversation because of the growing telematics and pay-as-you-go programs in the United States. There are also 4-5 companies in Canada seriously discussing telematics.

As more vehicles enter Usage based insurance (UBI) programs south of the border, the industry increases the overall repository of data and knowledge about actual driving behavior. This greatly enhances intelligence and decision making ability when this data is fused with the proxy norms used by most insurance companies.

By using Analytics, our company IMS, as a telematics services provider (www.intellimec.com) , is developing scoring systems on actual driving behavior that provides intelligence and allows our insurance partners to see the real risks their drivers produce.

This not only gives our insurance partners a better view of the risks than those with only traditional measures. But our behavior based analytics also potentially avoids some of the patent restrictions for business processes, now in place in the US – but not accepted by the courts in Canada.

Who owns the data and where does it have value?
This same behavioral data is also valuable to both the drivers who produce it and third parties who can use it. This is where we differ slightly from Strategy Meets Action who appear (in this blog post) who say that “Data must been seen as the valuable Corporate asset that it is”. Clearly actual driving data is a valuable corporate asset; however, it is even more valuable when it is returned to the driver (we believe that drivers ultimately own the data as they create it) and if it is sold to outside partners, as well.

If we feed back the data to drivers in the form of an on-going score or report, we can change the nature of the relationship with their insurance companies from being a supplier of capital to them, to being a trusted and valuable partner. The insurance company can help keep drivers and their families safer, smarter and greener while they drive – and even save lives. And this can increase the loyalty a driver has to his/her insurance company and in turn reduce the advertising and salesmanship costs related to retaining these users. So in this sense Analytics can help transform the entire business model of automotive insurance.

Similarly this data can be resold to the automotive industry for marketing programs, thus getting someone else to pay for the cost of telematics and the related analytics.

So far this has not happened but we are getting strong indications that it will happen as the pool of UBI data increases.

2. Threats of Analytics to the Insurance Industry
Analytics can also pose a threat to the insurance industry, and the automotive segment also provides a very good example of this. To understand this, consider the likely battle over customers that can between Insurance Companies and Automotive OEM’s that is starting to emerge over Analytics, Data and Risks.

As automotive manufacturers add more safety systems to their vehicles, they also take on more risk. While technological innovations such as Heads up displays (HUD) can make cars safer, they can also bring on the unexpected side effects of transferring more liability to the Automotive OEM. For if a HUD fails to identify a deer on the road ahead, and an accident occurs, there’s a fair chance that the OEM will be sued. Automotive OEM’s are thus being pushed to find ways to manage their risks.

Automotive OEM’s, such as GM are already financial institutions with their financing arms – GMAC. And they are best poised to install and analyze actual driving behavior because they can control what is added to the vehicle on the assembly line.

So it would be a short step for the Automotive OEM to buy either an insurance company or hire actuaries and take add Analytics. This could potentially lock out the current insurance industry from their vehicles. This potential threat is one of the reasons why State Farm insurance in the United States is working with Ford.

3. Conclusion
Clearly there are both opportunities and threats with Analytics. While it is costly to bring in or hire the skills needed to excel in Analytics, it will be more costly not to bring in these skills. It might even mean long term survival looking ten years out, because that’s when all vehicles should have built-in telematics solutions.

That said, the insurance company that can better interpret data – both from traditional sources and from telematics, social media, etc. – will have real power. And that power can lead to market advantages vs. competitors or even allow an outsider to disrupt the entire industry.

Technology has a tendency to disrupt industries. And in this case the technology around data Analytics and Visualization – is truly a disruptive force.

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