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Underwriters DMTI Spatial CanMap Canadian GIS Data

Top 3 Ways Location Intelligence Empowers Underwriters

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Today, modern location intelligence solutions are transforming the underwriting process. They give front line underwriters the ability to quickly and intuitively understand the exposures associated with one address – or an entire portfolio. Geospatial analysis has evolved from a back-office, ‘after the-fact’ function to a leading role in real-time underwriting decisions. Below are the top 3 ways Location Intelligence empowers Underwriting.

1) Individual Risk Assessment and Pricing 

True location intelligence solutions allows underwriters to more accurately assess risk at the individual property level, resulting in higher quality underwriting, more profitable business and cost savings through reduced claims.

Proper risk assessment starts at the point of sale. In the case of personal and commercial properties, that involves the validation and cleansing of addresses. Location intelligence solutions allow insurers to quickly validate the accuracy of new addresses or addresses currently on file for existing policyholders.

2) Risk Accumulation and Portfolio Management 

Accumulation or concentration of risk is an ongoing concern for insurance companies. An accumulation of risk occurs when a portfolio of business contains a concentration of risks that might give rise to exceptionally large losses from a single event. Such an accumulation might occur by location (property insurance) or occupation (employers’ liability insurance), for example.

Insurance underwriters require real-time visibility into their policy accumulations, perils risk data and claims history across their book of business. With an aggregated view of risk (perils and accumulations), underwriters can better manage their overall exposure across their entire portfolio.

Location intelligence solutions offer an accumulation and perils management tool to analyze various risk levels against individual addresses, street levels and postal codes to produce hazard ratings. This means underwriters can make decisions using up to-date data, such as flood or earthquake risk, contaminated land or proximity to potential risk sites, such as gas or propane storage facilities

3)  Segmentation 

A powerful result of location intelligence technology for underwriters is segmentation. Instead of looking at risks on a “blanket” basis, they have new tools to slice individual exposures by specific rooftop locations. In the example of a flood-prone region, insurers can identify which specific properties are at risk, instead of relying on broad postal code or FSA boundaries.

By assessing risk at the property level, insurers have the ability to underwrite business they may have previously declined, based on an inaccurate assessment of the risk location. With a better understanding of geographical risk (peril and accumulations) insurers can be more aggressive with rates in low-risk areas. Underwriters can identify under-exposed areas and target those areas with marketing efforts and competitive premium. Using a location intelligence capability, the insurer can hone in on a given region’s hot and cold spots

Conclusion 

Location-based technology has become an invaluable strategic tool to many leading insurers. Precise mapping and geocoding allow underwriters to quickly access information, recognize patterns and drill down into data for detailed analysis and sound decision-making. The real danger for those carriers not adopting location intelligence is adverse selection – the writing of poor risks without accurate or detailed information.

Understanding where a property is in relation to risk elements is a key decision affecting an insurance carrier’s profitability. Using location intelligence is a simple solution to a complex, real-world problem for the insurance industry. Insurers depend on geographic and demographic information to assess underwriting risk, develop appropriate pricing models, match coverage, expand markets, serve existing customers and develop new or niche business

To learn more download our Property & Casualty Insurance: Getting Risk Right White Paper

IoT and Location Intelligence

5 Industries Being Transformed by IoT and Location Intelligence

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Read to learn how the fusion of location data with the Internet of Things (IoT) is making organizations smarter and more efficient across industries

So many devices around us have steadily gotten connected to the Internet that we hardly even notice how extensive the Internet of Things (IoT) ecosystem has become. Our computers and smartphones may be the most obvious IoT players, but today, everything from household items to manufacturing machinery has been embedded with sensors which are generating and streaming data without any kind of human intervention.

Given this pace of proliferation, Gartner says we should expect to see more than 20 billion Internet-connected devices by 2020. And McKinsey maintains that IoT applications could have a global economic impact to the tune of $3.9 trillion to $11.1 trillion per year by 2025. These incredible figures start to sound all too plausible when you look at the developments closer home.

According to IDC Canada, over 45% of Canadian organizations today have dipped their toes in the IoT pool and the IoT market in the Great White North alone is predicted to reach a value of $13.5 billion by 2019. When you consider how IoT is giving businesses access to knowledge they could never tap into before, the optimism for IoT applications gets more than justified.

IoT sensors generate a massive amount of data every day. To both increase revenue and decrease costs, all companies need to do is know how to extract actionable insights from the information at their disposal. Many industries have discovered that the best way to do that is to tie disparate information streams together using an easy-to-recognize context called location.

By using precise location data, organizations can easily visualize what is happening where. And by analyzing historical data bound by spatial awareness, they can map trends and use these insights to optimize business processes.

Let’s dig a little deeper into how various industries are becoming smarter and more efficient by fusing IoT with location intelligence:

Smart Cities

Urban analytics is an essential component of smart city development. IoT and location intelligence are allowing governments and municipal agencies to quickly gather regional insights to identify inefficiencies as well as environmental impacts and risks. For instance, smart sensors on wheels can not only identify most congested areas, they can also provide a telling picture of pollution hotspots. Further, IoT and location intelligence are also creating ladders of opportunities for businesses. For example, the Canadian city of Mississauga publishes its real-time bus locations as a live open data set. A gallery can easily use that information to tell a commuter about an art exhibit they could visit at the next stop.

Supply Chain and Logistics

The marriage of IoT with location intelligence is bringing greater levels of transparency and efficiency in the supply chain, and changing the playing field for organizations that deal with logistics. Embedding tags in cargos is leading to an unprecedented ease in asset tracking and tracing – both during in-freight operations and at the time of inventory management in a warehouse. Distribution centres are also able to manage their yards more effectively by providing up-to-the-minute directions to truckers based on the type of goods they are carrying. And businesses even have an opportunity to provide early intervention in case an asset goes missing or is out-of-place.

Consumer Retail

A study undertaken by Deloitte and the Retail Council of Canada has found that retailers are using smartphone-based traffic analysis to understand the foot traffic outside and inside stores during different times of the day. This data is helping retailers to implement strategies to grow in-store traffic at preferred times. But that’s not the only way how location intelligence and IoT are transforming consumer retail in Canada. Retailers are also using these technologies to execute everything from offering in-store navigation to identifying profitable locations for new stores.

Insurance Companies

According to PWC Canada, 63% of insurance CEOs are convinced that IoT will be strategically important for their organization. And location intelligence is a natural fit for this bundle. Sensor data backed by spatial awareness can give insurance providers first-hand information about what happened, improving their ability to proactively address claims. Insurance companies can also use the location-backed data to improve their risk rating, detect fraud, and improve customer loyalty. For instance, a car insurance provider can offer discounts on premiums to its customers based on their real-time driving data.

Energy and Utilities

Providing reliable, high-quality and uninterrupted service requires a great amount of visibility and control across the entire utility network. IoT and location intelligence make that possible in ways more than one. Peterborough Utilities Group in Ontario, Canada efficiently manages outages and voltage discrepancies in its distribution network by using IoT to capture multiple data points like temperature, board status, etc., every few minutes from its metering points. Meanwhile, BC Hydro, the chief electric utility for British Columbia, has found that it can restore power faster and isolate faults to the smallest possible area leveraging an IoT-based smart grid system.

Clearly, location awareness is indispensable for an effective IoT network. Location intelligence can provide both context and relevance to an organization’s decisions supported by sensor data and open up a wealth of opportunities for smarter growth.

To know more about how you can benefit from adding precise location data to your IoT setup, contact us.

Additional Reading:

5 Ways Canadian Retailers Should Be Using Location Data and Technology

Predictive Analytics Data

Gone fishin’… in a data lake? Predictive Analytics Launch!

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Our new Predictive Analytics product launches in less than 2 weeks! As we approach this exciting milestone, we anxiously anticipate the loud ‘splash’ when LEADS (the codename for the product) finally hits the market. I use splash somewhat literally and quite purposefully, as we reside in the era of the “data lake.”

What is a Data Lake?

 The buzz term data lake is progressively used to describe “a state in which all data resides in one environment and can be explored and interpreted without imposing a schema”. Martin Willcox of Teradata eloquently describes the data lake as promoting three big ideas:

  1. Captures data in a centralized Hadoop-based repository
  2. Stores data in a raw form
  3. Enables the breakdown of barriers that inhibit analytics

Picture yourself fishing in a small canoe in a vast open body of peaceful water. As you peer over the side of the canoe you can see clearly beneath the surface into a limitless sea. Within the waters you can see hundreds, if not thousands, of fish swimming carefree. Each fish is a different color and each fish carelessly brushes against your line. As each fish passes your fishing rod tremors, but it is not until the right fish decides to take the bait that you begin the experience of fighting for your prize.

New Insights are Coming from DMTI

Welcome to the data lake. Each fish is a new variable or piece of data you may or may not have seen before. This intelligence you have been exposed to will allow you to gain the valuable insight from a sea of information that is seemingly too difficult or disparate to collect yourself.

This is what LEADS will do. Stay Tuned!

Click here to see DMTI’s GIS Mapping software solution.

Location Intelligence for Enterprise

Challenges, Drivers and the Need for Location Intelligence

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Even organizations that understand the value of location intelligence struggle to translate that understanding into meaningful profit-generating activities.

Much of the difficulty stems from the challenges of marrying enterprise data, which is typically housed in relational databases, to fully spatial-enabled information. New solutions that provide access to a platform of technology and crucial data building blocks that are integrated into an enterprise’s information processing cycle are available.

The result is a clean, current and consolidated view of enterprise information revealing new opportunities to enhance profitability.

3 drivers of location intelligence in the enterprise market are:

  1. The availability of high quality, current and complete data: Commercial geographic content providers are getting more sophisticated in the data offerings made available (e.g. to the building units in apartment buildings) allowing for a hyper-local perspective in business applications not previously available. Full service providers of location intelligence include subscriptions to geographic data that is maintained and developed on an on-going basis.
  2. Growing awareness of location-enabled services: Location intelligence has been popularized by business to consumer (B2C) applications from Internet search portals and personal navigation device (PND) vendors; and this increased awareness is moving into the Enterprise segment of the market.
  3. The rise of web services as a better-faster-cheaper deployment model: Software as a Service (SaaS) is now recognized as an agent that transforms how companies do business and is one of the most compelling innovations allowing for deployments of location intelligence that are cost effective. Solutions and delivery models are maturing and can be adopted without any disruption to existing IT structures or data modeling applications, reducing the attendant risk and expense.

More and more, the value of location intelligence is being linked to strategic and operational success at an enterprise level. As a means of generating revenues and controlling expenditures, location intelligence can directly impact profitability. Click here to learn more about how DMTI can help you leverage location intelligence.

Risk management for earthquakes

The Importance of Managing Earthquake Risk

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Do your risk management processes consider the risk of Earthquake?

October 16th marked the 7th annual ShakeOut where over 24 million participants worldwide will practice how to drop, cover and hold on at 10:16 a.m. during Great ShakeOut Earthquake Drills.

“ShakeOut BC Day” started in 2011 and this year over 660,000 participants in British Columbia will participate in drills.  The Charlevoix region in Quebec started participating in 2013 and the entire province has joined in for 2014 with over 80,000 participants registered.

Canadian Regions at Risk for Earthquake

Most people would initially think that British Columbia is most at risk when thinking about the risk of earthquakes in Canada.  However, parts of Quebec and Eastern Ontario are also at risk for earthquakes.  At a recent earthquake response seminar held in Toronto by the Catastrophe Response Unit (CRU), Dr. Kristy Tiampo, professor of geophysical modeling methods at Western University’s department of earth sciences in London, Ont. who also works with the Institute for Catastrophic Loss Reduction (ICLR) stated that “Montreal and Ottawa are both at significant risk of ground shaking” and noted that both cities have seen earthquakes that have measured around 6 on the Richter scale.

In an October 2013 report commissioned by the Insurance Bureau of Canada titled “Study of Impact and the Insurance and Economic Cost of a Major Earthquake in British Columbia and Ontario/Québec” two hypothetical earthquakes were modeled by AIR Worldwide.  One off the west coast of British Columbia measuring 9.0 on the Richter scale and one northeast of Quebec City measuring 7.1.  These two hypothetical scenarios would result in a combined estimated total insured losses of over $30 billion.

It is imperative for insurance companies to have a complete and accurate picture of the location of the property that they are insuring in context to the risks that surround that property.  This will allow them to rate the policy correctly and also to determine whether or not they want to assume the risk.  Understanding where the property is in relation to an earthquake zone is very important.  But not only is it important to know if the property itself is at risk, but also knowing where that property is in relation to other items that could be impacted by an earthquake.  For example, what if the property was close to a natural gas pipeline or propane processing facility?  Knowing about these potential risks in isolation is important to the underwriting and rating decision. But, what about when you also factor in earthquake?  An earthquake of a small magnitude may not be enough to cause much damage the property.  But what if it was enough to cause a gas leak, that then lead to a fire and an explosion?  Having this level of information could mean a big difference.

Disaster Risk Management for Insurance Companies

Another factor to consider for insurance companies is the accumulation of risk.  While the risk for the single property may be acceptable, knowing where all your existing policyholders are at the time you underwrite a mortgage and their relation to risks such as earthquake zones will be critical in determining whether you are willing to assume this additional risk or if your exposure is too high.  If there are two major events in a given year, would your exposure be too high and you wouldn’t be able to pay out on all the claims?

In Canada, various forms of location such as postal code boundaries, municipalities and Catastrophe Risk Evaluating and Standardizing Target Accumulations (CRESTA) zones (for earthquakes) are used to determine the accumulation of risk.

As per the ICLR, Canadian reinsurers, insurers and regulators use Catastrophe Risk Evaluating and Standardizing Target Accumulations (CRESTA) zones as the minimum standard for the capture of data and first level of calculation of probable maximum loss (PML).  PML evaluations can influence underwriting decisions, and the amount of reinsurance allowed on a risk can be predicated on the PML valuation.

The original CRESTA zones were established in 1981 and introduced in Canada in 1986.  They have been recently re-worked globally and have been re-launched to the market for 2012/2013.

All businesses can use this information to help define their contingency plans in event of an earthquake. Which of my existing store or branch locations might be impacted?  Where are my employees situated?  How would I deploy resources to help my customers most efficiently?  Where would I situate them?Insurance underwriting and exposure analysis is only one area where this information can be used.  Other examples include:

  • Public Safety departments within governments can use this to build contingency plans for their citizens, determine where they would locate remote relief sites, sites for temporary housing or medical facilities.
  • Telecommunication companies could use this to gain a better understanding of the risks associated with building out infrastructure in various parts of the country

Click here to see how DMTI’s disaster risk management tools help insurance companies effectively plan for every possibility.

Santa Uses Big Data

How does Santa use Big Data?

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As we all know, Santa is very busy this time of the year as Christmas is fast approaching! We sometimes take what jolly old Saint Nick does for granted and how much work it takes to visit all of those houses in one night. BUT, what if Santa used location and Big Data to make the process more efficient?

Here’s How Big Data Can Help Santa

What if Santa could:

  • Determine where changes have occurred since last year?

A lot can happen in a year, especially in Canada.  10,000 postal codes were added last year and the latest census showed significant variety of changes happened within Canada.

If Santa used his list, location and neighbourhood level data – he could do the following:

  • Identify the new addresses and postal codes that were added since last December
  • Understand the age of neighbourhoods – who has a new roof vs. an old roof so he can safely land his sleigh
  • Use neighbourhood projections for population changes to efficiently plan for future Christmas’ that have yet to come
  • Double check who is on the naughty/nice list?

Santa after making his list and checking it twice to find out who is naughty or nice now has a problem before he comes to town! Santa with his large list of names and addresses can now:

  • Confirm names with addresses and institute elf approved data quality standards
  • Identify business addresses that he doesn’t need to visit because everyone is at home nestled snug in their beds with visions of sugarplums dancing in their heads
  • Ensure the best flight path?

“Santa Claus is coming to town!”  “Santa Claus is coming to town!”  “Santa…Claus….is coming to…”
Wait – can Santa optimize his route to town?

Santa has decided to upgrade his sleigh navigation system to include address points so that he can see everybody and check them off his list as he delivers his parcels and goodies.

Merry Christmas and Happy Holidays from everyone at DMTI Spatial!

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