Bloomberg’s Compliance Solutions unit, which includes Bloomberg Vault, has made a strategic investment in London-based Insightful Technology and will integrate with Insightful’s Soteria compliance and surveillance system. This pairing comes as firms have seen an expansion in remote work and accompanying complexity in data from a growing suite of communication channels, says Nader Shwayhat, global head of compliance, voice, and directory solutions at Bloomberg.
“Our ability to monitor, surveil, analyze, and reconstruct corporate channels has been in existence for some time, however it is clear that over the last couple of years, the explosion of channels requires a lot more breadth of coverage and particularly on some of the more difficult and technically sophisticated channels such as video, voice, and secure mobile,” he says.
As a result of the pandemic, video conferencing platforms like Zoom and Microsoft Teams, as well as web messaging outlets like WhatsApp, have become an everyday part of the job, whether working from home or working in the office but still communicating with someone remote. Today, as long as someone has a computer and internet access, they can connect with clients and colleagues around the world at any time. While this connectivity allows easier collaboration and communication, it means more data now must be parsed through and trading firms need to make sure their employees are staying in compliance.
Following the 2008 financial crisis, regulations including the Dodd-Frank Act in the United States and Mifid II in Europe required more stringent surveillance of trading personnel, including the recording and archiving of all conversations related to trades. Dodd-Frank stipulates that all information related to an executed trade must be retained for up to five years in secure storage. Mifid II requires records to be kept and made easily accessible for up to seven years at the request of regulators. This was an expansion on the original requirement of six months in the EU.
Insightful Technology, which Bloomberg is also taking a strategic investment in for an undisclosed amount, brings to the table a data management system with a flexible data model that can capture, normalize, aggregate, and analyze datasets from voice, video, chat, and trade. Those datasets can come from either direct files or APIs.
“This collaboration gives both the Bloomberg Vault system and Bloomberg as a whole a much larger data capture capability and breadth of coverage,” Shwayhat says.
Bloomberg Vault is a compliance and surveillance system that enables firms to capture, control, archive, reconstruct, and analyze their e-communication, trade, and voice data across the entire trading life cycle on a real-time or historical basis. It sits within Bloomberg’s compliance solutions along with other surveillance systems and preventative controls.
Robert Houghton, chief technology officer and founder of Insightful, says financial institutions’ challenges in keeping up with compliance come from multiple changes across the industry.
“The challenge that customers have been facing over the last 10 years is the rules have changed, people’s working habits changed, and customers end up having a plethora of suppliers to meet those requirements,” he says.
A firm could end up using multiple different data stores or suppliers to keep up with regulatory requirements, but Houghton says the combination of Bloomberg and Soteria can consolidate that.
“What we’re bringing to Bloomberg is the ability to actually glue 120 different channels and over 40 different datasets into one holistic system into Vault, so the simplification of compliance and risk management is massively reduced from day one,” he says. “We’re trying to look 5-10 years into the future so that when the regulations change again or we have to meet XYZ requirements, you have the system already built.”
As firms are inundated with more datasets to make sense of, artificial intelligence technology tools that can weed through the noise have emerged as part of the solution. For compliance, Bloomberg is applying AI at multiple levels to structure data and then analyze it for patterns.
“The way we break down the challenge is in three ways. The first is to focus on the data itself, by taking unstructured data and transforming it into structured data, like a transcript,” Shwayhat says.
Both Soteria and Bloomberg’s transcription and translation engines leverage AI for this ability with Soteria’s capabilities including access to 70 languages and dialects. While the companies have deep experience in taking text-based information and structuring it around financial workflows and datasets, the next level is at the surveillance and analytics level where the structured information can then have rules, triggers, events, and insights applied to it for the generation of alerts, Shwayhat says.
“We’re looking for the behavioral patterns that may or may not change over time based on various risks as well as internal and external events that may change the risk profile of a particular trade, employee and/or counterparty.” This level is referred to as behavioral analytics, pattern recognition, and trade reconstruction.
As a hypothetical example, information could leak that a firm is looking to shut down a trading desk unbeknownst to its employees. That event could have an impact on an employee’s psyche and impact job performance. A firm could look at patterns and changes in behavior over time to determine whether there has been a change in performance and adjust their surveillance efforts accordingly. Pre-pandemic, a manager would be able to see their employees every day in the office but the world of remote work has changed that and added to the challenge of compliance and surveillance.
“With this integration,” Houghton says, “we want to bring various levels of automation using AI and ML, which means it’s not the horrendous job of picking needles in the haystack.”