Vendors push voice data across the trade lifecycle

Through partnerships and acquisitions, communications vendors are integrating voice data into different parts of the trade lifecycle to offer more sophisticated analytics and easier user interfaces.

Sound wave

Electronification has supplanted voice trading in some fixed-income markets, particularly in instruments like US Treasuries, though progress is uneven.

Rather than fading away, voice-based communications are adapting to new technology. Trading turrets are now available through touchscreen and in the cloud. But it is not just a shift away from physical, on-premises hardware. The harnessing of voice as a source of market data is now propelling an expansion of voice data into other stages of the trade lifecycle. 

IPC chief technology officer Tim Carmody says the communications technology vendor is bringing more data directly to the trader through IQ/Max Touch, a touchscreen-based device on the company’s flagship trading communications platform, Unigy.

IPC is integrating IQ/Max Touch with fixed-income solutions specialist BondWave’s Effi Market Calculator, a tool for increasing pre-trade price confidence before buying, selling or bidding a bond—including support for fair pricing and best execution. “The trader will see this application on the touch device, the turret, and then be able to select something on the touchscreen that automatically generates a call through Unigy,” Carmody says.

Currently, a user would first use the Effi Market Calculator to do any calculations to help with their bond purchases and then move to a turret to make calls. Carmody says once BondWave’s calculator is moved to the turret, the process will become automatic. 

The integration with BondWave will be available in six months.

IPC is also planning another integration with pre-trade pricing data provider BondCliq. The two vendors have integrated IPC’s voice communication through its Connexus Cloud platform into BondCliq’s electronic fixed-income platform. Users of BondCliq’s application are presented with multiple bids for a trade, and can choose from a number of options. ”If you want to trade via voice, it will enable that through the IPC network, and so through BondCliq’s platform you can execute a trade or show interest through a chat, an electronic trading platform or through voice connection,” says Ganesh Iyer, chief marketing and strategy officer at IPC.  

Taking voice into chat rooms

Other vendors have turned to acquisitions to grow their voice data capabilities. In June, Symphony acquired Cloud9, a voice analytics technology vendor. While Symphony is known for its one-to-one and multi-party chat solutions, as well as providing organized content around those offerings, the acquisition gave the vendor a capability it previously did not have: trader-voice telephony.   

Dietmar Fauser, chief information officer at Symphony, says a lot of valuable data is flowing through a trader’s voice. He says turrets—physical machines with buttons—do not work in the remote work environments that emerged during the Covid-19 pandemic. “The market is calling for deviceless, software-only solutions. This was a long-term trend anyway; it has just been accelerated,” Fauser says.  

He says it makes sense to offer voice data outside the trading space—for example, to staff in the middle and back office, so they can listen in to what is happening on the market floors and keep track of risk updates. 

One way the vendor plans to do this is by allowing voice data to be available in chat rooms, with control over who can access the data, and “use this data as one of the data sources for the global workflow of trade lifecycle management where voice is very important. Because very often in complex, highly unstructured markets, the final go for a trader is given through the voice channels, and then it’s keyed in manually and through order and execution management systems,” Fauser says.  

Being able to access voice data through chat is an initial step. “The activity for the next five to 10 years to come is to augment the humans by real-time assistance through artificial intelligence systems,” Fauser says. 

Fauser says Symphony aims to run voice flows in real time through “machine learning pipelines” such as Google’s Dialogflow, a tool that allows users to interact with AI-powered apps and bots. If there is any critical data flowing through, it can be made available to other applications in real time. 

The vendor recently entered into a partnership with Google, after making a decision to switch over from Amazon Web Services as its main cloud provider. 

Real-time transcription 

VoxSmart has also recently expanded its voice analytics capabilities through acquisition. The London-based surveillance provider acquired automated speech recognition and natural language processing specialist GreenKey in September. The deal offered VoxSmart real-time transcription and certain NLP capabilities that it previously did not have. 

“It is very synergistic for us because it adds capabilities that we didn’t have in terms of real-time transcription,” says Oliver Rooney, CTO at VoxSmart.  

He says the value proposition for GreenKey’s offering is that it can be integrated into front-office tools and turret systems. GreenKey and IPC previously built a blotter, a tool that allows clients of both firms to view and analyze audio conversations within their organizations.

The acquisition of GreenKey also allows VoxSmart to tap into new areas of the trade lifecycle beyond its core business of communications surveillance. Where previously it focused on building models to detect market abuse, through the acquisition it can leverage GreenKey’s capability to detect opportunities for a deal through speech analytics. 

“Compliance is not interested in maximizing revenue, they are interested in minimizing risk. And we previously focused on those risk minimization detection, rather than revenue maximization,” Rooney says.  

VoxSmart plans to integrate GreenKey’s capabilities into its compliance products. Rooney says his company wants to be able to offer multiple use cases from the same data using one system. For example, recorded data from a turret could be processed using NLP and then applied to two different use cases: for compliance purposes, and to help with front-office applications such as missed trade opportunities.   

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