The Monetary Authority of Singapore Notices 610/1003

The reporting requirements of MAS 610/1003 will see reporting obligations grow from 4,000 data points to more than 300,000 across 260 pages in 67 reports. A challenge that in many ways dwarfs both MiFID II and the Dodd-Frank Act. However, Solidatus offers the potential to turn this regulatory requirement into an operational asset.

Regulatory reporting of data attributes: Why use data lineage?

These reporting requirements cross multiple business units, demand meticulous execution and could consume significant resources to ensure all reporting is accurate. While the regulations themselves do not have explicit lineage requirements, reporting and record-keeping best practice, in addition to generating efficiencies and consistency within the report, does.

Lineage requirements

Audit control

The ability to demonstrate lineage and transparency helps to optimize audit processes
Solidatus can highlight where source systems are not mapped and where processes can be simplified. The mapping evolves as a living document of the regulatory lineage implementation, supporting both compliance audits and engineering projects.

Control and consistency

Data lineage demonstrates control and consistency – particularly where the same element is reported across multiple annexes
The collaborative design of Solidatus enables an organization to quickly and easily identify any gaps in trade reporting and validate attribute mappings at a logical and physical level.

Gap analysis

A typical approach to analysis duplicates effort across the various workstreams, leading to inconsistencies
Solidatus can model data attributes of the different annexes to identify similarities and differences across the reporting requirements and to map the implementation of MAS 610 and 1003 reports all the way from the golden source systems.

Solidatus for MAS 610/1003 mapping

Solidatus allows an organization to map the MAS 610/1003 regulatory requirements onto their reporting implementation and to easily visualize and understand the flow, usage and intended usage of data across complex processes spanning reference data systems, trading systems and reporting systems.

Key benefits

• Build effective controls around both process and data.
• Demonstrate transparency and optimal compliance to the regulators.
• Generate an operational data blueprint that can help reduce risk around system transformation.
• Encourage company-wide collaboration.
• Achieve a competitive advantage around areas such as data analytics and generate efficiencies to broader system transformation.
• Interrogate additional models to find solutions to similar problems elsewhere within an organization.
• Assist in good data governance practice, with the potential to expand models to managing user entitlements and data retention policies.

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