Ubs Group Technology and Operations Case Challenge

2017 UBS Group Technology and Operations Case Challenge

Stage 1

Elite Bank is a globally renowned financial services company based in Switzerland. It is one of the top-class integrated banks, providing wealth management, asset management and investment banking services, to its clients which range from Ultra High Net Worth (UHNW) individuals to institutions. The Investment Banking Division of Elite Bank offers a wide variety of financial products & services, including: prime brokerage; securities dealing; and market making services in Equites, Fixed Income, Credit and FX products, Derivatives and Structured Products. The services are managed by experienced and professional analysts from discrete desks in Sales & Trading department.

After trading hours on a busy business day, Tiffany, a junior trader from an equity desk based in Hong Kong, was consolidating the day's trading activity, and manually estimating the Profit & Loss (P&L) of the trading portfolio she supports. The portfolio consists, primarily, of Hong Kong stocks and Hong Kong underlying* derivatives*. She was reconciling her estimation against the P&L generated from MoneyClip (refer to Appendix 4) and sent from Middle Office. She noted a USD1 million discrepancy which far exceeded her expectations.

In light of the detected discrepancy, the first thing that concerned her was about potential wrong trade bookings, undertaken by the Trade Support team, which would require immediate correction and re-booking. She hoped to figure out the causes and resolve the issue before end of trade day T0*, when the P&L consolidation report was due to be sent to desk heads and management levels. She asked a responsible Middle Office-analyst, Sherry, to investigate. Having reconciled the booking details of all recent trades in the Risk Management System RMS (refer to Appendix 4), Sherry confirmed that the bookings were accurate and error free.

Based on her experience, Sherry suspected that the P&L discrepancy was driven by internally-maintained incorrect market data*. Accordingly, she decided to validate the data with reliable external sources. Sherry manually analyzed the P&L breakdown of each stock and derivative, for all positions* held in the portfolio. She identified an abnormally large P&L coming from a number of products with underlying of a Hong Kong stock.

Logging into an external stock price system, Sherry looked for the underlying stock prices and extracted them onto an excel spreadsheet. After a line-by-line comparison of the external stock price with the internal price, she discovered the internal price quote for Stock A was different from the external data source. After manual re-calculation of P&L for the affected products* using external price quotes, Sherry succeeded in reconciling the USD1 million discrepancy, concluding that an incorrect internal price quote was the main driver of the abnormal P&L. Such an error has the potential to cause financial misstatements of million dollars not only in Tiffany's portfolio but also on other desks trading derivatives with the same underlying stock. If left unresolved, the error has the potential to draw attention from external stakeholders, including auditors and regulators.