The increased focus on transparency by regulators has highlighted the need for robust risk systems capable of analyzing vast quantities of data.

“The focus of regulatory agencies on collecting and analyzing systemic risk, as well as SEC [Securities and Exchange Commission] examination priorities on alternative product managers, especially as it relates to valuation and pricing, are challenging investment firms in new and multiple directions regarding how they collect, store and manage data,” said Bruce Treff, managing director and U.S. product head of mutual fund servicing at Citi.

Although banks have systems in place for measuring market and credit risk, the credit crisis and the ensuing recession have called such traditional techniques as Value at Risk (VaR) into question.

“VaR worked well for many years, because it provided a simple measure of risk,” said Brian Sentance, chief executive of Xenomorph, a provider of analytics and data management technology. “But the world has changed, and regulators are demanding much greater granularity, so that they and risk managers at the institutions themselves can anticipate the problems that can occur when risk models break down.”

High-powered visual data analysis tools are empowering analysts, traders and risk managers to make sense out of the massive amounts of data at their disposal and make fact-based decisions.

The challenge is how to filter the increased noise that comes along with the more important data signals.

The addition of a visual interpretation landscape solution can help solve that challenge by giving the end user the ability to see more, in context and be able to act.

Data visualization technology supports rapid visual analysis of large data sets and real-time data in financial services and other data-intensive industries. Typical use cases are real-time analysis of profit and loss, risk exposures, transaction cost analysis and pre-trade basket analytics.

Xenomorph has enhanced the reporting and charting capabilities of its TimeScape system, and has introduced interactive heatmaps for visual data validation and decision support.

Through the enhancements, users will be able to configure default charts and analytical functions to be applied to each asset class, enabling better decision support and greater automation for assessing data quality.

“Risk managers are now able to look at large quantities of data, and pick up visually where there might be data problems, rather than just eyeballing a lot of numbers,” Sentance said.

TimeScape’s new heatmap capabilities enable custom analytics and validations to be integrated into a visual view of large datasets, allowing business users to zoom in on unusual regions of data quickly and focus on potential data exceptions and outliers.

In addition to standard time series charting, visualization of more complex objects, such as historical volatility surfaces, can be set up easily and quickly for all users.

“Time series data is not limited to just histories of numbers such as prices and yields, but rather can be any kind of data, however complex,” said Sentance.