In a business setting such as finance, where product and price are becoming more and more differentiating elements, factors such as the Digital Transformation, Big Data or Business Intelligence are acquiring greater importance, allowing these businesses to be much more efficient. These premises base their success on the Quality and Data Enrichment.

An adequate Data Quality strategy helps improve the image of the company, it favours costs savings, contributes to preventing fraud, increases the efficiency of the direct marketing actions and supports the loyalty and acquisition of customers, without also forgetting that the tools that later use the standardised and corrected data such as MDMs, BI or Geographic Information Systems will return more precise results.

Whereas, the companies that continue managing the information on their customers in different information silos, characterised by duplicate, incomplete or invalid data, find themselves at a disadvantage. In its report “Measuring the Business Value of Data Quality”, Gartner indicates that “poor Data Quality is the main reason why 40% of business initiatives do not reach their goals”, furthermore, “it affects the overall work productivity by 20%”.

Towards an adequate management of Information

Until a short time ago, banks do not need to apply advanced intelligence to their data. However, the growth of the volume of information, as well as the significant restructuring that this sector has undergone at a worldwide level, has resulted in a process of unification of different sources and databases as well as the updating of their data.
Having good geographic and social demographic data is essential to be able to carry out effective business and marketing campaigns. However, in the majority of countries with a high volume of inhabitants and a large number of companies, the databases of customers usually contain a significant number of errors (addresses that cannot be located, hard to identify names, duplicate or incomplete information). These errors impede these organisations from obtaining business intelligence.

Likewise, the Global Data Quality solutions that almost all financial entities apply do not think in “local” (neither in Mexico, nor in the Spanish language) which is a handicap when optimising their databases and developing their business in a satisfactory manner.

Data Enrichment: the solution for obtaining multiple advantages

In order to alleviate this problem, it is necessary to have a standardisation/deduplication solution that ensures that the registries within the databases are correct, thereby preventing errors in important fields such as customer names, postal addresses or emails and telephone numbers.

The combination of this knowledge with Geolocalisation services provides multiple advantages associated to creating customer loyalty. When automatically sharing the location, this itself creates great common knowledge. Similarly, with Data Quality techniques focusing on Geocodification projects, one-to-one marketing campaigns can be carried out which are centred on the maximum understanding of the customer, thus permitting the analysis of these data in real-time. Geomarketing, understood as a social economic analysis technique from a geographic point of view and using mapping and spatial tools, has also become an essential discipline when designing business strategies.
The financial sector must make the most of the competitive advantage granted by the value information that it has on its customers. By using MyDataQ, a tool fully adapted to the local situation and which facilitates the efficacy of the data for the financial entities , DEYDE provides data standardisation, deduplication and enrichment services. With the above, DEYDE improves the business intelligence processes and offers a unique view of the customer, causing projects that incorporate Data Quality to have an immediate ROI.


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