Seeing multiple attributions of both performance and risk is increasingly important for asset managers to make the right decisions and add value.
On the one hand, a clear understanding of risk is an integral part of the decision making process to help asset managers assess the potential cost of their investments. On the other hand, a clear view of the performance of existing assets helps managers to learn from their past decisions and make better ones in the future.
As Damian Handzy, Global Head of Risk, StatPro says in The maturation of risk services:
“Managers and investors have come to value a robust risk analysis on the same portfolios. Since before the global financial crisis, managers and asset owners have sought a single source of performance/risk analysis but until recently, they’ve had no choice but to use different systems and reports for these two very closely related analyses.”
Seeing an aligned and aggregated picture of the two together drives performance through greater visibility and also makes for better, more granular reporting to investors and shareholders. It’s a fundamental shift, with both audiences placing increased demands on the industry to demonstrate what happened, why investments performed the way they did, how conditions might change in the future and why.
As State Street reported recently, decision-support for the front office has become a priority and for this to happen, there is a need to move as close to real-time information as possible. To illustrate the point, two thirds of respondents in the firm’s 2013 Data and Analytics Survey conducted by the Economist Intelligence Unit believed that data will be a key source of competitive advantage in the future.
A blurred narrative
But getting a handle on the data is no easy task, especially for the larger asset management firms grappling with more sources of information in greater volumes.
It is not just volume that presents a challenge either. Data is also highly complex and relates to a broad array of asset classes, each with its own set of data, parameters and variables.
Making matters more complicated is the fact that data has historically been siloed – held in different streams even if the source was initially the same. As a result there is often no single record of the analytics and calculations applied to data and no normalization or aggregation applied at output level.
The outcome is that a single data set can go through any number of distinct processes and look entirely different at the output stage. This limits the value that can be extracted and the people that can access it.
This whole situation does not bode well for comparing like with like, with a single picture on which to base risk and performance data analytics.
Even when it comes to comparing data over a historical period there can be a disjoint. Making that work when complex performance and risk calculations are required – often with many variables in the definitions alone – makes for something of a headache, to say the least.
Integration – so important
As the State Street report highlights, institutional investors often need to integrate hundreds of external data sources and data providers need to deliver an integrated view on risk and performance.
The question now is how to address the data deluge in its many forms and to create a starting point where there is a single set of definitions and calculation methodology. The holy grail for the 21st century asset manager is to arrive at a point where the analytics can be applied to give a meaningful and comparable outcome.
The authors of a PwC report on managing risk and performance are emphatic about the need for this, saying “an integrated approach offers a new view of the old balance sheet.”
The role of technology
Clearly this is a real challenge, but with the right tools and technology it is becoming more achievable.
In its 2016 Global Asset Management & Administration Survey, Linedata found that cutting costs and managing data was one of three main challenges within the asset management community. IT spending priorities were around improving legacy systems, risk and compliance solutions and data management.
Within the context of making sense of data, then having a system that can untangle the data web in the first place and then apply a governed set of analytics to it results in a user friendly end result that adds significant value.
When it comes to the front end, a dashboard presenting performance and risk attribution relies on the ability to consolidate data and control where the data is coming from. This means reducing the sources of information so that for each parameter there is a single data set. At the outset, this means identifying those data sources that represent the truest, most reliable picture.
Once the data has been analyzed, then governance comes to the fore with a need for consistent formats so that the core data underneath that dashboard stays the same. Users then need to be able to dip into that underlying pool of data to get the information they require and decide who needs it. Often this is a visual issue requiring customizable reporting capability for different stakeholders, but pulling from the same underlying data pool.
Effectively this is about reducing data output and working towards a centralized processing and management workflow.
In summary, Damian Handzy defines the clear line of sight to this:
“Imagine a report that shows multiple attributions simultaneously: attribution of returns and risk into the same underlying causal factors for each set of investments in a portfolio. Simultaneously learning where you made your money and how much risk it cost you to make that money would be instantaneous.
“Such insight is not far away.”
- Risk and attribution go hand in hand but seeing them together means de- siloing, normalizing and aggregating data.
- Untangling the data web and applying a governed set of analytics on it results in a user friendly end result which adds value
- Presenting a customizable front end relying in accessing a consolidated and controlled back end
- Good governance over process provides the consistency that the front end needs.
- Reducing the forms of the output and working towards a centralized processing and management workflow is the holy grail for risk and attribution