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Winning the data ‘arms race’

Four essential analytics strategies for insurance CIOs

John Knowles, Director, IT & Off-Shore Operations for Allianz InsuranceIf you ask our executives how we use analytics to improve the business, you are likely to be met by a quizzical look. Analytics isn’t a term we tend to use much internally. Ask our executives how we use data to drive pricing decisions, analyze risk – even assess the impact of the Japanese tsunami on the cost to repair cars in the United Kingdom – now that will get a response.

Our core business is the assessment of risk and that assessment is based on a deep understanding of the information we collect about our policyholder, about the things that we’re insuring and our claims experience. We’re not like a manufacturer that needs to get the supply chain just right to make money. Instead, we earn income by understanding risk and pricing accordingly, so data mastery is essential.

Insurers are data-driven organizations and to stay competitive, we have to make sure we are using the best data sources, work collaboratively with our business units to analyze those sources and continually refine the way we search out and integrate new sources.

My role as the CIO is to build a collaborative relationship with the business units, ensuring that the units have what they need when they need it. To that end, there are four strategies I employ:

Everyone works off the same core set of data

The actuaries and underwriters work from the same data sets, although we do allow the data to be placed in separate warehouses and data marts for particular specialist purposes. The core data includes all of our internal data, plus information in the public domain (such as demographic data), credit rating data and information from government agencies. Having the same base data is critical, as increasingly the different groups are working more collaboratively then they have in the past. It’s a huge waste of time when the actuaries have a different set of numbers than the underwriters. My team’s role is to bring the platforms and databases together, but at the same time allow different business units to take out data and do the analysis in the way they find most efficient.

IT doesn’t drive the analytics – it provides the collaborative framework

This doesn’t mean that we just let the business units, the actuaries and underwriters tell us what to do. Instead, we provide the framework, secure the integrity of the data, set guidelines and help business units select and use tools. We approach this role with a great deal of collaboration and an attitude of support.

There is a whole world of new information out there; our job is to figure out how to use it

Many people can now shop for insurance via aggregator sites where customers input details what kind of insurance they want and all the companies signed up with the aggregation service offer a quote. This is a rich data vein. For the first time, we now know what virtually half the UK market has asked for. In the past, we only knew a fraction of this information since people had to call individual companies or agents for policy quotes. We’re doing more than 100,000 quotes a day, so this is a vast amount of data about the industry, what product and coverages are asked for, and how it’s being asked for – providing a whole new world of potential analysis.

But the information that needs to be analyzed doesn’t just come from our customers

One of our jobs is to understand market conditions that affect the suppliers of the parts that fix the homes and cars that we insure. If regulations require damaged cars or homes to be rebuilt with new and pricier products, it affects the cost of our policies. If you haven’t factored in the shifting cost of supplies and others have, your risk is not properly covered and you’ll lose money.

With data, it’s a bit of an arms race. My team’s job is to arm our business units to win that race.

NOTE: Originally published on the Business Analytics Knowledge Exchange.

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