Best Data Analytics Provider—Bloomberg

 

Bloomberg won four categories at this year’s Inside Market Data & Inside Reference Data Awards, including best data analytics provider and best overall data provider for 2022, announced at the New York-hosted ceremony on the evening of May 17. The firm’s Risk & Investment Analytics offering was responsible for delivering the win in the data analytics category, arguably the most closely contested of all 26 categories in this year’s edition.

Zane Van Dusen, head of risk and investment analytics products at Bloomberg, explains that the firm provides users with granularity, transparency and quantitatively-based risk measures that support the views of both the front and back office from a risk perspective, allowing them to work more collaboratively. “What’s unique about Bloomberg’s data and analytics is that we bridge the gap between front-office and back-office risk management,” Van Dusen says. “These groups don’t always see eye to eye, because the front office relies on what they’re seeing in the markets and their intuition, which often is reality, while the back office needs data that is scalable and defendable. These groups end up going back and forth, poking holes in each other’s methodologies.”

Bloomberg’s ability to address risk challenges for both the front and back office lies in its vast database of market data that it leverages to quantitatively calculate different risk metrics to satisfy both constituents. “We offer the best of both worlds because you’re now getting the latest market data in a standardized risk metric that you can use across your portfolio so that everyone can have the same conversation when looking at market risk, liquidity, credit risk or even drilling down into fund analysis,” Van Dusen explains. “Everyone’s looking at the same data so they can agree on the numbers and actually manage risks rather than simply reporting on them.”

Liquidity in the Spotlight

A crucial component of Bloomberg’s Risk & Investment Analytics offering is its Liquidity Assessment (LQA) solution, which, according to Van Dusen, allows users to accurately and transparently assess the liquidity of the securities they hold, a perennial thorn in the side of most market participants—especially when it comes to thinly traded fixed-income securities.

“The challenge that our clients are facing is that they’re under increased pressure from investors, senior management and regulators to prove that they have sufficient liquidity in their portfolios under numerous scenarios,” Van Dusen explains. “Unfortunately, assessing liquidity on an asset you’re not actively trying to sell is really difficult, especially in the fixed-income space where most securities trade over the counter. As a result, firms end up having gaps in their liquidity analysis and, in many cases, they underestimate the true liquidity available for bonds and are not able to capture the impact of the latest market events.”

Bloomberg’s LQA addresses the problem by way of financial models fed by large volumes of trade, market, reference and security data. “When we train a model in our database of executed trades, we use different sources from around the world, and we’re able to update it on a daily basis to capture changing market conditions so that it’s not a static perception of liquidity,” Van Dusen says.

Credit on the Radar

Throughout 2021, liquidity was the main area of focus for Bloomberg’s clients from an analytics perspective. However, that focus started shifting to credit risk in the first few months of this year, a trend accelerated by the economic and political uncertainty emanating from eastern Europe since February. It’s a scenario that Van Dusen believes has all the makings of a significant credit event. “We’re in a perfect storm when it comes to credit risk: we’ve got the lingering impacts of the Covid-19 pandemic, increased volatility, inflation and interest rates, and now geopolitical turmoil,” he explains. “This is all the stuff that drives a heavy credit risk environment we haven’t seen in over a decade. Most people sitting in seats today haven’t had to deal with an environment that is not being artificially propped up by central banks.”

The current market and economic double whammy has exposed gaps in firms’ credit monitoring tools, which haven’t been properly tested in the past decade or so. What Bloomberg is hearing from the market is that a lot of existing credit analytics tools are either slow to react, have limited coverage or are manually intensive, driving firms to seek out alternative credit metrics to capture the latest market insights. “We’ve been focusing on our MIPD [Market-Implied Probability of Default] product because that provides a daily credit risk metric based on the latest market sentiment we’re able to derive from the fixed-income market,” Van Dusen explains. “This allows us to cover pretty much any company or government that issues bonds.”

For even deeper coverage, Bloomberg has continued to invest in its Default Risk (DRSK) model, an early warning tool that leverages market and fundamental information to analyze the credit health of a company. Today, DRSK has a 92% accuracy rate for more than 519,000 public and private companies and millions of bonds and loans.

Looking Ahead

While LQA and MIPD are key components of Bloomberg’s Risk & Investment Analytics offering, the firm is also working on a similar data-driven approach to address environmental, social and governance (ESG) considerations. Bloomberg’s new ESG Fund Analytics offering uses fund-level ESG metrics on areas such as company policies, carbon emissions and diversity so that clients can compare funds and invest according to their objectives without having to rely exclusively on funds’ self-reported ESG metrics. “While we cannot predict the future,” says Van Dusen. “Our risk analytics actively assess what is happening in the market and quantify that sentiment into actionable insights, enabling our clients to be the first to know about emerging risks and opportunities.” 

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