Data Governance – Gaining Accuracy with Geocoding
In today’s technology-driven, customer-centric world, the competitive edge for financial institutions lies in providing answers quickly – essentially getting to the yes or no – while mitigating and managing their risk. Location intelligence helps to more quickly determine the answers to questions such as – does the property exist? Is it accurately identified? Is everyone within the mortgage ecosystem referring to the same property? Is the property subject to any environmental or demographic factors that require further risk assessment or result in a greater assumption of risk?
Location intelligence provides specific location identification, ensuring its accuracy, and facilitating the current, historical, and predictive multi-faceted environmental and demographic data for that location.
Another hurdle in data analytics that most organizations currently find challenging, is ensuring data quality. For instance, a city name could be spelled in multiple ways, or users enter different abbreviations for the same data. As organizations grow inorganically – by mergers and acquisitions, this problem is compounded due to inconsistent data and data definitions between the various systems.
At the core of location analytics is geocoding, an identification method through which data becomes geo-enabled. Unlike the standard systems, geocoding is the identification of a precise location through geographic coordinates (latitude/longitude), with rooftop level precision. That location is further verified through various external inputs, thereby providing a high degree of reliability. One location intelligence system, DMTI Spatial’s Location Hub assigns what is known as a UAID™ (Unique Address Identifier) to each individual address. The self-service data analytics engine leverages Canada’s most robust, accurate, and up-to-date location-based data, to cleanse, validate, and geocode the organizational address database. The company covers 94.8 percent of all possible Canadian addresses and realizes a high precision coverage of 95 to 99 percent in urban areas.
With the reliability provided by such a high precision coverage address system, financial institutions realize seamless transitions between all stakeholders. This provides for such things as ensuring that a given location is one and the same property being referenced by the vendors within the property based lending ecosystem, or providing 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.