PnL monitoring


The problem

Complex models are used to compute the value of derivatives, determining the profit and loss of trading desks, ultimately deciding on the fate of financial institutions. The output of the models is hard to monitor due to the large number of valuations as well as the overall complexity of the problem. However, every time an unexpected PnL jump has been detected, risk managers, traders and quants have to spend considerable time and effort on tracing back the source of this problem, hopefully leading to more stable models.

Our solution

When using Yields to monitor your PnL, we detect automatically any anomalous behavior. We moreover apply advanced mathematical tools to the data to automatically discover the root causes. The end result is a set of alarms and reports identifying the problematic trades and models, together with datasets to reproduce the problem and possible suggestions for their remediation.

pnl back

Interested in a demo?

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