Enterprise Data Provisioning Hub

February 13, 2020

In the Mortgage Banking Industry, data provisioning is a complex process that represents an operational vulnerability. Data is provided by disparate sources with distinctive agendas, resulting in non-standard formatting and definitions as it travels through and is at rest within the environment. How can information be accurate if everyone is essentially speaking a different language within a shared dataflow?

Using Open Source methodologies, Prolifics helps Mortgage Banking enterprises achieve optimum accuracy with their data via our innovative and peerless Enterprise Data Provisioning solution. We design the means by which your framework’s various operators and applications can talk to each other seamlessly and more efficiently under the same standards and definitions. With our solution, clients can enjoy previously unrealized data accuracy and cohesion regardless of where they need to push or pull data from within the scope of their framework.

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Information Standardization via Centralized Data Provisioning

Prolifics understands that people working within the scope of an enterprise’s Retail channel may use different terms from those in your Correspondent channel to describe the same thing. However, we also realize there’s no reason reporting and operational accuracy has to suffer because of these often necessary, systemic inconsistencies.

Our Enterprise Data Provisioning Hub solution employs a transformation process towards a shared standard. This is used to map your data so everyone in an enterprise’s framework is using the same definitions. The data is then pulled through the Hub at every point, forcing all systems and channels to provide the same information in their extracts to achieve environment-wide uniformity and conformity.

Evolve your Data Provisioning Capabilities

Take the next step towards a truly unified data provisioning solution. Contact solutions@prolifics.com to learn how our Enterprise Data Provisioning Hub solution may help your enterprise reach the level of data organization you expect.

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