One of the biggest challenges asset managers are facing in the alternative data market is the scarcity of high cost data that only the biggest, most technical players with dedicated data science teams can access and put to use, according to Richard Lai, Global Head of Alternative Data in Bloomberg’s Office of the CTO.
To address this issue, on September 7, Bloomberg launched a new alternative data function on the Bloomberg Terminal, ALTD <GO>.
Lai said that with the launch of ALTD <GO>, Bloomberg is lowering the current barriers to entry, bringing more transparency and democratizing data so it is accessible and ready to use.
“Already, we have seen great demand among customers for ALTD <GO> and expect this to continue,” he said.
Lai added that thousands of clients signed up to participate in the function’s beta test, and major firms are updating their research reports based on the information available through ALTD <GO>.
“What’s really exciting is that we are seeing usage from new user types such as long-only investors and sell side research analysts. We are already seeing significantly increased adoption from where the market previously was,” he said.
Lai explained that the data available via ALTD <GO> enables investment analyst and portfolio manager clients to gain far more depth and speed of insight into how companies and economies are performing.
“We are bringing highly-demanded alternative datasets such as our Bloomberg Second Measure transaction dataset as well as Placer.ai’s market-leading mobile geolocation dataset to all Bloomberg Terminal clients,” he said.
“These datasets allow them to understand how key investment theses are playing out in near real-time, through billions of data points,” he added.
According to Lai, Bloomberg customers can gain insights from alternative data right alongside traditional market data, broker research, and estimates.
Bloomberg is democratizing historically inaccessible insights and creating one unified destination for alt data on the desktop, he said.
These are big and challenging datasets for clients to use, he said, adding that you typically need a strong data science team to make use of these datasets effectively in the context of an investment thesis.
“ALTD <GO> makes it far easier for our clients to utilize this data in their existing investment research workflows without the need for extensive data science capabilities,” he said.
Given this demand, Bloomberg plans to strategically add additional alternative data sources to expand the universe of high quality alternative datasets available via Bloomberg’s products, and enhance the unified data model that ties these datasets together, Lai said.
“This will enable us to create more powerful analytics to support our customers in finding differentiated investment opportunities through deeper levels of research than previously possible,” he said.
According to Lai, other providers offer alternative data solutions but the difference is that typically, this type of data could only be used by the most sophisticated quantitative investors and larger hedge funds who have the resources and data science expertise to do the time consuming and costly work of making the data usable.
ALTD <GO> supports equity analysts and portfolio managers with intra-quarter insights and can be easily incorporated into research workflows – alongside consensus estimates, company news, research, and guidance – well ahead of earnings announcements, Lai said.
Through the Bloomberg Second Measure acquisition completed in 2020, Bloomberg began offering an alternative data feed and analytical products that enable clients to gain highly valuable, near real-time insights into the performance of thousands of consumer-facing companies and consumer trends at an industry-leading 3 day lag.
Bloomberg Second Measure serves as the data analytics source for ALTD <GO>, Lai said.
Within the function, it uses aggregated analytics from billions of credit card and debit card purchases to provide near real-time consumer transaction insights on over 300 public tickers, with this list expected to grow rapidly in the coming months, Lai added.
ALTD <GO> also includes data from location analytics leader, Placer.ai, which analyzes foot traffic data.
Placer.ai utilizes a privacy by design approach to incorporate data from a panel of tens of millions of mobile devices, applying machine learning and AI algorithms to make estimations on visits to retail locations across the US.
Lai said that for the first time, alternative data and analytics are integrated right alongside Bloomberg’s market leading fundamental datasets on the Bloomberg Terminal, making it immediately usable for investors.
“The power of this offering is the fact that we can bring alternative data into the context of the many other sources of data that exist in a research workflow – ex. traditional fundamental data, pricing data, news, research, broker estimates etc.,” he stressed.
“No current solutions enable this deep integration and we believe our clients will be able to utilize alternative data far more effectively because of this seamless enhancement of existing research workflows,” he added.
Lai told Traders Magazine that the team is currently working on an update to the Bloomberg Desktop API that will allow analysts to export data from ALTD <GO> directly into Excel.
This will allow for better integration of alternative data into their existing workflows, he said.
“In addition we are working on bringing on additional datasets and building new functionality into ALTD such as a soon-to-be-launched quarter-to-date analytic which gives investors a far clearer view of how a company is performing intra quarter vs. consensus estimates,” he said.
Additionally, according to Lai, in collaboration with Bloomberg’s Terminal Alerts & Insights team, Bloomberg’s CTO Office plans to provide more robust distillations of the kinds of information that alternative data can help surface for investors alongside company financials in other Terminal functions, like MODL <GO>, and through news articles.
