Canada Embraces More Analytics for Insurance Industry Growth

The Canadian insurance industry has reached a tipping point, where carriers who use data effectively across the enterprise are seeing strong gains and putting pressure on stragglers to follow suit. The use of analytics has shifted from innovative experimentation to becoming table stakes and an operational and competitive necessity. FC Business Intelligence asked speakers from the Analytics for Insurance Canada conference to share insights on trends on insurance analytics in Canada.

Toronto, Canada, April 16, 2015 --( Most insurance companies didn’t mature with a data culture, and the demand for change management in this area is where the industry must now put much of its focus.

“The companies that use analytics most effectively are companies where leadership including the CEO and the rest of the C-suite are promoting, communicating and leading change management around data cultures in their companies,” said Stephen Applebaum, Managing Partner of Insurance Solutions Group. “If the CEO isn’t on board with the change management around an analytics culture, it’s going to fail.”

Beyond just simple adoption, companies who want to succeed must also develop cultural habits that stimulate and encourage innovative uses of data around collaboration and new modeling techniques.

Collaboration Is Key
“All insurers have limited resources to fight fraud so a key to success is focusing these resources on the highest value claims. Collaboration, coupled with network analytics is a leading practice that can greatly improve fraud detection,” said Ben Kosic, President and CEO of Canatics.

Pooling data, across organizations, is providing new opportunities for insurers to manage their fraud risk portfolios because it can increase the ability to flag and detect possible organized fraud. No matter how big an insurer is, they’re essentially looking at fraud through a keyhole and potentially missing the severity of underlying crime rings. By collaborating through participation in a consortium insurers can work together to identify suspicious activity that is indicative of organized and premeditated fraud. Once these leads are available to individual insurers they can then compete and/or differentiate themselves by how they investigate and handled the potentially fraudulent claims. Kosic noted that any industry group looking to pool data for this type of detection could have a growth strategy that includes:
· Adding new members to increase available data.
· Adding new sets of data to improve detection.
· Expanding to new geographies to tackle existing or anticipated fraud.

“With respect to organized and premeditated fraud, there’s really no such thing as an ‘auto insurance fraudster in Ontario.’ They are Fraudsters and they engage in various schemes across different industries and lines of business. There is an opportunity to further improve detection abilities by thinking outside these traditional narrow definitions,” said Kosic.

Using Data Collection in New Areas
The expansion of data must be in new uses, collection and analytical modeling to find insights.

OPTA Information Intelligence has focused its innovation in analysis on by-peril ratings. This allows it to categorize and identify concerns on a risk-by-risk basis that determines the frequency and severity of a loss by geo-coded address.

“We work to allow customers to understand where they will suffer their worst losses, allowing them to alter their pricing and risk selection basis. This information can also help insurers understand where they should try to market new business activities, such as the most profitable homes or commercial properties,” said Greg McCutcheon, President at OPTA Information Intelligence.

This capability is due to the company’s ability to collect information across many different touch points – it’s among the largest property data aggregators in the country – and to serve its analytics platform as an addition to an insurance company’s strategy, instead of a replacement. OPTA’s analytics can be incorporated into existing general linear models, a new pattern that is emerging in the world of analytics.

McCutcheon sees the Canadian market in a period of swift evolution that’s adopting analytics on a large scale, and sees innovative uses of modeling such as OPTA’s by-peril approach as a key to successful differentiation.

“I believe the Canadian insurance industry will change dramatically in the next 5 years. Organizations that have not already put together a strategy for predictive analytics should speed up this process. There is a significant risk that their business will become uncompetitive in a quickly evolving marketplace,” warned McCutcheon.

Where Do Insurers Start?
The upheaval in the marketplace is separating the wheat from the chaff along the lines of analytics and advanced modeling. Today, insurers must begin to force a cultural change to adopt analytics.

That starts with the CIO and information technology departments seeing their roles as a sales job to convince CEOs and Boards with small wins. These provide the best ways to evangelize a change as they relate to business objectives.

“For a piece of practical advice, make sure your HR department is looking for a data scientist with broad experience in the insurance industry,” suggests Applebaum. “Get yourself a champion who knows how to communicate analytics’ value. They’re very hard to find but they’re critical to success.”

Ben Kosic, Greg McCutcheon and Stephen Applebaum are speaking at FC Business Intelligence’s Analytics for Insurance Canada in Toronto, May 11-12. For more information visit website:
FC Business Intelligence
Alesia Siuchykava