Reducing the negative impact of unpredictable events is not just necessary for the businesses who are directly affected but for the economy as a whole. Risk assessment and mitigation with location analytics is an ideal solution for organizations to undermine disruptions due to various factors like weather, terrorist attacks or fraudulence.
Location intelligence has become increasingly important in risk mitigation as well as analyzing the risk concentration. Clean data can be enriched with various demographics information for analysis on risk concentration and customer intelligence. A report by DMTI Spatial, a leader in the field of location analytics, mentions financial organizations can generate risk concentration lists and apply risk mitigation/risk diversification strategies by infilling the addresses within specific territories that are not in their current database.
Taking another classic example is of chaos created by unpredictable weather. The report mentions that identifying the exact area affected by a natural disaster, which helps determine the amount of risk to insured properties and weed out claims that are filed from areas not located in the affected zone.
An insurance company can quickly pinpoint the exact geographic coordinates of the claim in real-time and overlay the storm’s path over that location. Was the claim location actually affected by the storm, or is it outside the boundaries (or marginal)?
In large loss events, insurance companies often experience claims ‘leakage’ – when claims payouts are more than the terms set out in the policy. Precise use of location intelligence can help stop the leakage of opportunistic claims, or ‘soft fraud’. Location intelligence can help with more than just catastrophic events. To get more indepth knowledge knowledge platforms like the Geospatial World Forum 2019 can be of great help..
Location intelligence improves data quality
Despite of constant technological change and growing demand of data analytics, organizations often face the challenge of ineffective and inefficient data governance. But there is a way to it. Financial institutions can now leverage location intelligence to increase data quality, streamline business processes, manage risks better, and increase operational efficiency.
To gain a competitive advantage in the market and mitigate operational risks, organizations are increasingly drawn towards combining business analytics and geo-data together. The report by DMTI Spatial reveals that most financial institutions use standard systems of identifying addresses, such as those based on municipal registries or postal addresses. Inherent nuances within those systems create ambiguities that, in turn, leave margin for errors, omissions, and confusion. Standard systems can be further compromised when municipal changes are implemented.
The problem doesn’t end here. Errors can easily creep in if streets have multiple names or cities being spelt differently by various people or using different abbreviations. Such inconsistent data and data definitions between the various systems affect data quality majorly which in turn reflect on the operations and performance of organizations.
A one-stop solution to resolve all these complexities is ‘geocoding’.
Role of geocoding
At the core of location analytics is geocoding. Location is just not a mere address. Geocoding is the process where it converts address into spatial data and associates the exact geographical coordinates for that address. It is used in geographical information systems to help find the coordinates of a place or address.
So, unlike the standard systems, geocoding identifies the precise location. This technology enables a financial institution to provide quick and accurate answers. Questions like where the property is located; does the property requires risk assessment; is everyone within the mortgage ecosystem referring to the same property, etc. can be answered with utmost accuracy and quickly.
Giving a new dimension to the where factor, geocoding gives a high degree of reliability. DMTI Spatial mentions geocoding with the help of location analytics provides clean data that can be analyzed for essential trends and patterns. With the results displayed on a map, it allows user visualization and interaction for better data profiling which not only ensures operational efficiency, but is a critical first step in risk management. This also enables financial institutions to realize seamless transitions between all stakeholders.
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