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Key findings:
- The data dictionary — a “version 0” of what the mortgage industry data standards could look like — has 414 data elements on:
- borrower
- loan
- mortgage pool
- property
This dictionary was influenced by industry participants and regulators to ensure that it is aligned with existing data practices.
- The education stream focused on the materials needed to increase awareness around a set of mortgage industry data standards and their benefits. This stream also explored the resources needed to increase the desire to participate and support the change. This work:
- reviewed the target audiences
- reviewed key messages
- identified appropriate communication channels
- The recommendation is for the initial data standard to use XML as the initial data modeling language rather than other languages, such as JSON because XML:
- is well-adopted among mortgage industry players
- is queryable and supports namespace, therefore allowing data annotation and useful metadata attributes
Implications for the housing industry
There are currently no plans to implement mortgage industry data standards – including the data dictionary created in this research project. The materials created through this research would enable a reference model to be quickly created and adopted.
While this is our final research report on mortgage industry data standards, there are outstanding decisions regarding implementation. These decisions would need to be addressed if implementation were to be pursued. They include:
- identifying governance and sponsor organizations
- identifying pilot cases
- revising the data dictionary with the full input from the mortgage industry
Done!
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