In order to cater to the increasing needs for regulatory compliance, mortgage banks must adopt a wide-ranging method to compliance risk management (interfacing regulatory analysis, determining contesting regulations, incorporating operational process controls, managing data quality, and planning documents management).
Mortgage banking stakeholders comprehend the challenges, while adhering to transforming regulations and requirements from government regulators, government-sponsored enterprises (GSEs) and investors. Regulatory compliances impact the complete life cycle of originating and servicing a mortgage loan. The emphasis is on data quality related to decision-making, calculations, and analytics.
An organization cannot be looked upon as being compliant with a procedure unless it delivers proof of the functions, procedures and data represented by the rule. In order to prove “evidence of compliance”, an organization must record the connection between compliance rules, calculations conducted, and data derived.
There exist five critical components of managing a compliance program that delivers evidence needed to reduce compliance risk:
Compliance is related to a comprehensive documentation of regulatory, investor, state and corporate needs. It is directly connected to the operational processes, data, and reports impacted by a distinct requirement. The process is handled by a team of stakeholders to bridge the gap between business and technology. The stakeholders collaborate with business, legal, IT and compliance personnel to interpret and record regulatory needs.
It facilitates the interpretation of regulations being translated into related business processes. It needs a comprehensive process design, control, and management. Efficient process controls also need a robust elucidation of the process, an effective understanding of the key points of control and proper reporting that particularly addresses the key control points.
An effective process control and monitoring system would result in business process exceptions being reduced.
The effective execution of the previous three components would have a major impact on data quality. It is structured to facilitate the veracity and flexibility of data across the life cycle. The data quality is validated by the integrity of the source.
At the time of origination, servicing and default management, a loan transits via multiple stages and critical processing outcomes. It is vital for the data to be documented at the same time as the occurrence of the event to ensure compliance afterward. For instance, during the origination process, a distinct fee is modified in excess of an elucidated ceiling, the modified values along with the event are managed and used in compliance reporting.
Identify the perfect source system for specific elements and effectively transfer the data elements to a centralized repository. The lack of accuracy during the data transfer process is a vital reason for bad data quality. It needs inefficient initiatives to integrate the data later on.