About Model Drivers

Model Drivers technology enables banks to integrate their data and the regulations that govern them.

Unlike current approaches Model Drivers integrates the semantics of data and regulations before building data managing systems supporting the regulation. Systems means trading platforms to data warehouses. Regulations means English language obligations as well as reports, such as for Dodd Frank and MiFID.

With richer, model driven semantics comes automated understanding, improved management and auto generation of code. In this way the systems development process is far faster and regulatory compliance costs far lower. Systems changes becomes easier and management control greater.

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.

Model Drivers works with industry regulators, consultants and banks. We are a start-up based in London and Melbourne, Australia.


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

Contact us for a demonstration of a case study in your area of interest. Contact us

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.

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 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.


One element of the Model Drivers strategy is to industrialise the regulations themselves. What does it mean to industrialise regulations? Some clients have called it “WikiReg”.

  • Access for the common man: We are publishing semantic wiki versions of the regulations in the public domain for easy access to otherwise hard to find information.
  • Simplification: We publish regulations in a simplified, common, human understandable form.
  • Access tools: We provide end user query tools, APIs for machine access and downloads into sophisticated analytic and reporting tools.
  • Social collaboration: By publishing in a wiki, the community can collaborate, learn and improve financial regulations.

Contact us for a short demonstration of a working WikiReg. Contact us

  • FpML, the Financial products Markup Language by ISDA, the standard for processing derivatives instruments.
  • FCA Handbook, the regulations published by the Financial Conduct Authority in London.
  • The EBA datapoint model for FINREP and COREP.
  • Operational Resilience as defined by the Bank Of England.


Greg Soulsby

Greg specialises in data and enterprise architectures and systems for the finance industry.  His focus is on delivering innovative data solutions for clients through best practice design and tooling.

He has developed products to support XBRL regulatory reporting, model driven testing and data point modelling.

Greg can be reached at +44 (0) 7717 831 854 and on LinkedIn https://uk.linkedin.com/in/gregsoulsby

Simon Roberts

Simon is a financial markets specialist with extensive  experience  and understanding of capital markets and financial derivatives. Simon was most recently Head of Commodities, Europe & America for ANZ Bank.

He specialises in derivative structuring, financial regulation, new business development, bank system change management and technology delivery solutions.

Simon can be reached at: +61 (0) 499 577 245 and on LinkedIn https://au.linkedin.com/in/simon-roberts-721083102.

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