When making a choice in our personal lives, we relate many -- if not most -- things to location. From the proximity of our houses to a destination, to the decision to walk, drive, or fly on our next vacation, everything revolves around location.
Today, we’re beginning to see that intrinsic relationship translate over to the enterprise. Businesses are now using systems known as Geographic Information Systems (GIS) to manage location-based data differently and uncover insights that help geo-target sales, manage supply chains, and evaluate risk. These systems allow companies to capture, store, analyze, and visualize location data in such a way that it enables informed decision-making and new business possibilities.
In insurance, nearly every data point has some relationship to location. While some of these relationships are more distinct than others -- think P&C insurance relationships -- the care for all relationships will benefit from greater access and insight into the location of the insured. The reason for this is twofold:
1. Given the increased complexity of, and time compression associated with, risk scenarios (e.g., 100-year storms becoming 10-year storms), insurers need a better way to model and visualize risk.
2. Insurers need new ways to connect and engage with their customers.
Using location to model risk
To unravel all this, let’s start by looking at the need for enhanced risk modeling tools. At the heart of insurance is the ability to assess and manage risk. For many years, this has been done on spreadsheets and calculators. Now, with GIS, it can be done through advanced modeling tools that overlay location-based information onto models of buildings, cars, roadways, etc. Let me provide you with an example.
An underwriter is developing a proposal for a jewelry store owner. That owner is sending the underwriter images of the current security system. The underwriter is not only able to review these images, but also tag them with date, time, and location information. To take it one step further, these details are then cross-referenced with other location-based data, including neighboring stores, past losses that occurred in the area, risks associated with natural disasters, etc.
All of this information combined allows the underwriter to capture the risk as accurately as possible and tailor the service to the customer’s needs. In addition, it adds new capabilities for risk aggregation and visualization. With this information in hand, insurers can assess and price the risk more effectively by looking at the aggregate risk profile in a specific geography. This process can be replicated across any commercial insurer -- from large to small -- and can also be tailored for P&C insurance.
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This type of modeling and risk assessment is a new, but incredibly valuable, tool for underwriters. When the data is being analyzed within the context of location, the underwriter, risk inspector, and even the actuary are able to make smart, informed decisions about the potential risk a customer faces, the type and amount of coverage to offer, and the rate at which to sell it. It’s a smarter way of doing business and it helps protect customers to the fullest extent possible.
Faster, smarter, better
Now that we understand how location-based data factors into the underwriting process, let’s focus on how it can help transform the traditional customer-insurer relationship by expediting claims and facilitating greater communication between the insurer and insured. Here’s how:
The jewelry store mentioned above has bought the policy that the underwriter provided and has been assigned to a claims manager. That claims manager watched a storm roll into the area where the jewelry store is located. Using GIS data, the manager was able to assess where the storm would hit and how badly. With enough time to spare, the store owner was alerted to the impending threat and able to prepare as best as possible. However, there was still roof damage done to the building during the storm.
Once a claim is submitted for the damage, the claims manager can align the images of the roof damage with the path of the storm and the images that the underwriter gathered in the appraisal process. Combined, these two validations provide ample proof of an accurate claim and allow the claims manager to issue the payment quickly.
In this instance, real-time location-based data helped the jewelry store mitigate potential risks associated with a natural disaster and expedite the claims process. This fully digital customer experience is the new way in which insurers will begin to engage with their insureds, and it’s being facilitated by location-based data, mobile devices, and always-on connections.
That said, the use of location-based data and GIS systems is still very much evolving and hasn’t been integrated fully into all elements of the insurance ecosystem. However, it does pose an immense opportunity. I foresee that this will become an area of differentiation and clear competition for insurers across all lines of business as all eyes turn to focus on “location, location, and location.”
Vinod Kashroo has over 26 years of experience in the financial services industry, and held executive roles of increasing responsibility. He has worked in high scale and complex environments at AIG, Prudential and MetLife, driving business and IT transformations. Vinod ... View Full Bio