ModelDR (Model Driven Regulation) is a new approach to implementing regulatory requirements for banks. Some have called it “RobReg”.
Current approaches use traditional system development lifecycles – understand the regulation, find where it impacts systems, write specifications and send into the IT development process. Labour intensive, error prone and slow.
ModelDR brings automation and industrialisation to what is otherwise a costly, valueless overhead.
Automate the hard stuff of regulation
Simplify and de-duplicate: Typically, different regulations are implemented using different processes and systems. By integrating the semantics of the regulations and firms systems ModelDR identifies and re-uses common elements across all regulations. The volume of solution goes down, consistency goes up.
Case study: See how we present European Banking Authority (EBA) COREP And FINREP reports for powerful queries to find and analyse impacts. Query a regulation for impact analysis
Run regulations as code: ModelDR understands the semantics of both regulations and the firms systems. This structured, granular data enables the generation of, for example, code and documentation. Changes in the regulations or systems can be quickly implemented by automatically re-generating this code.
Case study: Reverse engineer legacy systems to understand their semantics. Use this capability to automate the regulatory reporting process. Automate a reporting pipeline
Automate testing: ModelDR uses its knowledge of both rules and data structures to define test cases and auto generate test data. ModelDR creates both positive and negative test data – being data that should pass and data that should fail with a known error message. This automation drives down time and cost while increasing test coverage and quality.
Case study: See how we automate complex and comprehensive regulatory reporting system testing challenges. We use the BearingPoint reg reporting platform Abacus in this case. Test_automation_at_BearingPoint_regulatory_reporting
In what way is ModelDR technology different?
ModelDR is built on semantic technology: While other approaches use data and information technology ModelDR works in a more human like way, managing intent first and implementation second.
ModelDR is model driven: Traditional thinking means working in the implementation layer directly. For example, ModelDR ingests and generates databases, spreadsheets and Word documents, it does no manipulate directly.
ModelDR has a meta meta model: Meta Meta Modelling is technical talk for being able to integrate any number of domains. ModelDR can, for example, integrate a regulators English language regulations and a firms databases.
Contact Model Drivers for a 10 minute demonstration of a working use case.
Blog on creating value from complaince: Create-value-from-assurance-and-compliance/