P&L attribution approach

P&L Attribution requires alignment of risk and finance data to validate P&L performance versus the interaction of observed position and price changes.

Within many financial services firms this data is often stored in separate repositories. In addition, market data is often sourced from disparate feeds for finance and risk purposes.

The use of data analytics technology allows us to source, normalise and combine data sources, allowing risk and finance data to be aligned and attribution calculation logic to be built and executed.

Within many financial services firms this data is often stored in separate repositories. In addition, market data is often sourced from disparate feeds for finance and risk purposes.

P&L attribution offers an important control, the decomposition and analysis of actual booked P&L and its variance to that of a risk based theoretical P&L provides a daily test of the models. In addition to a risk control it also provides a valuable operational control of trade amendments and cancellations by highlighting their effects within the explain.

Regulators are increasingly focused on enhancing the control environment within financial services firms. The linkage of risk sensitivities (“Greeks”) to the real world profit and loss figures provides an additional control framework. The Basel Committee has directly linked the ability to calculate effective P&L attribution metrics with the ability of trading desks to use the internal model method for calculating capital requirements. Given the increasing demands on Bank capital, a solid P&L attribution framework will continue to be a key driver of organisational capital efficiency.

Large unexplained P&L balances, i.e. where sensitivities multiplied by market movement fail to reconcile closely with reported P&L, should provide internal control functions with warning signs as to the validity of risk and P&L methodologies. This can be a further challenge where traded instruments are illiquid and little or no market observable pricing exists.

Our optimised P&L Attribution reporting allows users to quickly identify the primary factors causing movements in P&L through a simple and easy to understand interface incorporating both numerical and graphical data representations.

Reports incorporate graphical visualisations of each identified attribute at report date and also historically through time with changes.

The graphical view allows easy comparison of information and data can be accessed with just one click

Our streamlined report interface allows for the historical performance of all P&L Attribution factors to be tracked through time and the ongoing monitoring of current and historical unattributed P&L and unexplained risk factors.

We offer clients a pre-defined but customizable P&L Attribution reporting interface that incorporates numerical and graphical representations and offers a consolidated view of all key risk factors relevant to the products under consideration.

Users can define the combination of P&L Attribution factors they wish to interrogate depending on the purpose of the analysis, and sort values to identify largest relative or absolute exposures using just a couple of mouse clicks.

Our solution allows P&L Attribution to be viewed at all levels of aggregation, from country or enterprise level down to division and desk and ultimately each individual trade, moving between levels with a single click.