New Project announcement: TRAC Data & Analytics Platform is now Open Source in FINOS

[Traverse, Martin]

Dear FINOS Community,

I am delighted to announce that TRAC D.A.P. was successfully contributed to FINOS and is now hosted at https://github.com/finos/tracdap.

TRAC is a next-generation data and analytics platform for use in highly regulated environments. Most financial institutions have similar pain-points in Risk and Finance - fragmented data architectures, high cost of change, lack of model insight, poor traceability and difficultly reproducing results to name a few. TRAC solves these problems by re-drawing the boundary between business and technology, to bring a step change in power, flexibility and control.

We are arranging demo sessions to showcase TRAC to FINOS members which will be included in the FINOS weekly newsletter and community calendar nearer the time.

What can TRAC do for me?

Model development

Modellers can easily develop and run models against real production data, without change risk or any need for technology integration. The same models can be automatically productionised and taken through an approval workflow, at which point all the data inputs stored in TRAC are instantly made available for users to use.

Model execution

In TRAC, everything is live all the time. Run alternate scenarios, champion/challenger models, what-if analysis, waterfalls and more with zero change risk. Any job can be repeated at any point in the future with no IT effort and produce identical results, or load and alter a previous job to re-run with new parameters and inputs. Overlays can be inserted at any point in a workflow and are included in the same repeatability guarantee.

Audit, control, lineage

Everything that happens in TRAC is recorded automatically, in a from that is both human- and machine-readable. Requests for audit and regulatory documentation can be answered in a single click, with all the relevant metadata assembled in a PDF report. Users can self-serve data lineage which can be traced back across workflows and data versions.

Analytics

TRAC provides a query interface that allows data in the platform to be interrogated using standard SQL. Dashboards and reports can be saved as templates and applied to the outputs of individual jobs. For more full-featured reporting, data can be explored using 3rd party BI tools.

Technology abstraction

Underlying data and compute capabilities are abstracted and can be swapped out by a simple configuration change. Models and applications are insulated from the underlying technology stack. Use any of the big three cloud providers, Hadoop (on-prem or managed) or a local backend to run the same models on a laptop. Additional back ends can be implemented as plugins. TRAC requires only a few core technology capabilities, to maximise portability and minimise deployment headaches.

How mature is the TRAC platform?

A closed-source version of TRAC is live at one of the UK’s leading retail banks where it has gained significant traction and is now the strategic platform for all analytic workflows across Risk and Finance.

The most current open-source release is version 0.4.0, which contains the core components needed to build an end-to-end workflow. The following resources are available:

Documentation: https://tracdap.finos.org/

Model runtime package: https://pypi.org/project/tracdap-runtime/

Web API package: https://www.npmjs.com/package/@finos/tracdap-web-api

How can I get involved?

Your feedback, issues, and contributions are very welcome. See CONTRIBUTING.md for more information on how to contribute, you can also raise an issue or see some areas where we could use help. Or just leave us a GitHub star – because we all love stickers!

Thanks to the FINOS Community for a warm welcome!

Martin Traverse

Greg Wiltshire

 

 

 

 

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[Gabriele Columbro]

Exciting stuff!!! 

Thanks Martin, Greg and the whole TRAC maintainers team. Looking forward to working together to grow the community and adoption!

Gab

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Gabriele Columbro | Executive Director | FINOS

📱 +1 (404) 432-7652 | 🕊 @mindthegabz

   

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