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Front-Office Supervision for Unauthorised Trading

By 28 Feb, 2018June 14th, 2018Case Studies, Surveillance

Client

Swiss Investment Bank

Function

Front-office

Asset Class

Multi-asset

Geography

Global

Duration

12 months

The Ask

The client is taking steps to repair a hugely costly financial and reputational hit following an unauthorised trading incident.

GreySpark was asked to launch a project to prevent future unauthorised trading incidents from happening in the future. As regulators around the globe now require banks to monitor, report and provide supervision on trading risk across all assets, the client needs a next-generation supervision and control platform. The client wants a new Big Data algorithmic approach to identify changes in the behaviour of individual traders and between traders rather than monitoring individual trades.

Methodology

GreySpark deployed a team of consultants to approach the project from multiple angles to produce a best-fit program.

  • GreySpark engaged with FO users and COO’s across the bank to identify weaknesses and supplemented them with cross-product knowledge.
  • The consultants defined and prioritised the metrics to be tracked through a combination of business meetings, user surveys and desk visits.
  • Big Data tools were deployed to filter and monitor large amounts of trades from different trade capture systems. 
  • Consistent progress and status reports, including RAID logs, were provided to the steering committee.

Outcome

Final deliverables included:

  • A strategy document;
  • Business and systems architecture;
  • Data schemas;
  • Project plans;
  • Business requirements;
  • Functional requirements;
  • Process maps;
  • Training materials; and
  • New systems/infrastructure testing approach and methodology.

GreySpark Delivered Benefits

  • At every stage of the project and in all deliverables, GreySpark clearly outlined the benefits as well as the implications for user engagement. Management of the Big Data vendor deliverables.
  • Upon program implementation, the client registered a drop in the backlog of suspicious events requiring investigation and all unauthorised trading events were investigated within a day.
  • By providing the client with an in-depth review and recommendations on Big Data technology, the client was able to correctly and efficiently implement and use their new program.

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