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Location intelligence aids insurance decision-making

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Location intelligence is a common dimension of almost all business information, and understanding its relevance is fundamental when deciding on marketing campaigns, sales territories and routes, site locations and customer services.

As such, location intelligence enables insurers to measure, compare, assess and analyse data, helping them to plan and make better, more informed business decisions.
“New and more valuable insights can be gained by adding location capabilities to an insurance company’s existing business intelligence (BI) platforms,” says Alan Ellis, CEO of local Johannesburg-based Location Intelligence specialists, the ST Group.
“Through dynamic geographic visualisation, organisations can harness the power of location Intelligence to understand where their most valuable assets are located, and predict and respond faster to the impact of external market forces,” Ellis maintains.
He explains: “By combining the spatial analysis capabilities of ST Group and Pitney Bowes MapInfo’s location intelligence technology, with the analytical capabilities of Business Intelligence solutions, businesses are able to gain several benefits from using location-enhanced business intelligence.”
According to Ellis, a location intelligence solution, integrated with an existing customer database, enables an organisation to visually identify its most valuable customers, see how demographics correlate with sales, and then to target where new customers with similar demographic characteristics are located.
“People often think it’s just about maps, but that’s only the beginning,” says Ellis. “Rather, it’s the layers of data underpinning the maps – and the interpretation thereof – that are crucial. Thematic mapping with a location intelligence solution like Pitney Bowes MapInfo allows for the interpretation of this data.”
Location intelligence can be used in a variety of ways to assess insurers’ policy and portfolio risk. Using its geographical visualisation capabilities, risk analysts can accurately identify and analyse the accumulation of risk by geographic area, using a combination of policyholder data and external reference data – such as weather and climate information. A visualisation in the form of a map can be explored, manipulated and analysed to gain valuable risk insights.
“Maps reveal trends, patterns and insights that are not as easily detected in other data presentation formats,” continues Ellis. “For insurance purposes, a map can clearly expose the inherent relationship between people, property and risks associated with a specific geography.
"For example, via a geographical representation, insurance companies can zoom in on a particular location to identify policyholders who live in the path of a storm or flood plain. This is achieved by using both existing customer information, which has been geo-coded to a position on a map, together with third-party data on weather and climate changes.
"Using this type of location-predictive analysis, the user can then locate those policyholders which are most exposed to the risk of a storm or flood. This gives insurance companies the option to precisely target specific addresses and pre-warn policyholders about imminent risks and ways to lessen those risks, thereby saving the insurance company substantial amounts of money, while creating better relationships with policyholders.
"In addition, location intelligence technology can be used in a pre-emptive manner by tracking the path of a storm and then determining which buildings and properties are likely to sustain the most damage by severe weather,” he notes.
Predictive analytics also include a variety of techniques from statistics and data-mining that process current and historical data in order to forecast possible future events. The insurance industry uses predictive analytics to predict how long policyholders will live, or even their likelihood of being involved in a car accident.
Another area in which location intelligence can help insurers – and one of particular relevance in South Africa today – is crime.
“Using crime data such as that collected by local marketing insights company, Knowledge Factory, a location intelligence solution can track crime-related insurance claims, thus identifying high-risk areas for car theft or burglary,” Ellis states.
“For example, by using geographic representations of crime information and modelling suburb crime patterns, Knowledge Factory recently ascertained that affluent neighbourhoods are the least likely suburbs to be affected by arson,” he points out.
Insurers can therefore use location intelligence to better visualise risk exposures – such as the historical trend of crime prevalence in a certain area – and then mitigate those risks.
“ST Group’s location intelligence can help insurers to manage risks by providing a visual representation that clearly illustrates risk exposure in order to calculate loss potential.
Insurers can then determine the appropriate amount of reinsurance coverage they need to purchase. The risk analysis results can be displayed and communicated to clients in a way that makes sense to everyone.
“In summary, Location Intelligence can truly be said to be the key to unlocking better business value and better-informed decision-making for the insurance industry today,” concludes Ellis.