P&L Attribution Engine

Trusted by financial services clients all over the globe

Our P&L Attribution engine is a flexible, modular platform which can be rapidly deployed across complex data environments

P&L attribution analysis and reporting provides users with a coherent breakdown of the drivers of P&L movements between two points in time with reference to a select number of easily understandable pricing factors.

Why do it?

Engineered control infrastructure for trading activities

P&L attribution processes are an essential element of the control infrastructure for financial services firms' trading activities.

By analysing the variance between actual booked P&L and the theoretical risk based P&L, the attribution process ties together the risk and finance controls into a single centralised check.

In addition to it being a risk control, it also provides a valuable operational control of trade amendments and cancellations by highlighting their effects within the explain

Meeting regulatory demands

Global Financial Regulators have become increasingly focused on enhancing the control environment within financial services firms.
P&L attribution has been a key process in implementing that environment, by bringing together disparate risk and finance processes into a single overarching control.
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

The dangers of unexplained P&L

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.

Analysing data intelligently

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

P&L Attribution Delivered

Successful implementation of P&L attribution processes requires the ability to bring together data from both risk management and finance sources. Our combined financial markets expertise and use of enhanced data analytics technologies have supported a number of our clients in successfully implementing P&L attribution solutions.

Successful P&L Solution Delivery

Designed by risk professionals for risk professionals

We offer clients a pre-defined but customisable 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.

Get the information you want – now

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.

Pinpoint problems by drilling down from high to low level information

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.

The Data Analytics Advantage

Easily access disparate sources of data

Whether it is legacy COBOL files, batch csv files, xml messages, big data repositories or databases, we can connect and acquire data from existing sources; no need for the expense or complexity of building a data warehouse. Light touch approach which greatly reduces the demands on IT teams.

Visual data model and processing

In spite of complex pathways, it's easy to see where data comes from, where it's cleaned, and where it's joined. Having a living data picture facilitates decision-making and understanding.

Modular Libraries

Standardisation of data requires standard processes, eliminating duplication and ensuring central control. With modular libraries, we can repeat, adjust, and deploy logic quickly.

Rapid and accurate

Our approach is highly iterative from the beginning: we get data, examine and validate, so we don't have to wait until waterfall testing to find the problems. It is robust and can be automated at the end of the process.

P&L Attribution dynamic reporting

There are always issues with data quality - it’s never as clean as you would like. Having data from different sources exacerbates that problem. In order to address all these data issues, P&L Attribution requires a single, consolidated report.

P&L movement indicators

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.

Large quantities of historical information at your fingertips

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.

Draw visual comparisons fast

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.

P&L Attribution Case Study

P&L Attribution

Access the P&L Attribution data sheet

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