Automation and technology-enabled data management are critical elements of an agile, robust reporting function that will allow organisations to be more proactive as new requirements arise.
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Versioned rules which provide for changes in business logic without the need for code changes in applications (such as a new parameter for a regulatory requirement).
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ALFA focus on both data and data exchange format to enable organisations realise a flexible and validated regulatory reporting framework.
ALFA Advantage for Regulatory Reporting
Low-code, highly flexible, consistent, validated, cost-effective framework that focuses on both data (rules) and data exchange format to allow organisation meet their regulatory data requirements.
Consistent data format
Clear definition of published data by multiple sources, and guarantee data quality at source.
Consistency with single model boosts faster, more accurate insights, as well as increased speed and agility to change.
Reduces cost
Reusable code libraries used across the cross-asset-class system. Duplication of work. Too often, applications that use the same or similar data require bespoke development effort due to each application-specific approach to handling data
Accelerate IT delivery
The platform accelerates application delivery times by allowing an enterprise to create applications through model configuration rather than by coding those objects and functions. Introducing data attributes or new datasets required by the user (business or regulator) takes minutes not ages.
Common format
Regulatory Technology write a common, version-controlled, re-usable model and rules used across cross-asset. For example out 65 data attributes needed for MIFID II reporting 56 are common across the assets classes.
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ALFA model and rules are expressed in an easy to understand, declarative and functional style language.
Flexibility
Support for new/updated feeds and data can be made available in a matter of days, not months.
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ALFA is designed for Service oriented Architecture, and allows Architect to review the model and extend some features such as adding APIs and model metadata.
Business rules and validation
Express complex rules in an intuitive and concise syntax such as decision tables or bucketing rules.
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These are generated into highly optimised parallel executions.
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Support writing model tests and for quality assurance, produce rule test coverage reports.
