Whether desktop or mobile phones, videoconferencing platforms, or software-based trading systems are being employed, voice is still the primary source of communication for the financial markets.
As a result, audio and video data are crucial to the analysis of information by enterprises. Voice interactions are now subject to stricter compliance monitoring rules.
However, according to Nigel Cannings, founder and CTO of the U.K.-based business Intelligent Voice, obtaining, monitoring, and analyzing conversational data may be challenging and need modern speech infrastructure.
It becomes considerably more difficult in loud settings like trading floors, where anyone might enter or leave a conversation at any time and where traders speak quickly and over one another, flip between languages, and employ jargon unique to the trading industry. He said, “Some of the challenges that financial service players face when reviewing audio and video files with constrained human resources are that, as well as the capacity to precisely analyze emotion and sentiments.”
When people speak, Cannings said in an interview, “Humans leak a lot of emotion and data about themselves, whether it’s omitting certain types of pronouns or using distancing language to push themselves away from an event.”
It’s a gap that Intelligent Voice is attempting to fill with its speech and natural language processing (NLP) technologies powered by artificial intelligence (AI), which are available in 24 languages and dialects. According to him, these technologies can recognize behavioral cues and spot signs of fraud and suspicious activities in a matter of minutes.
Overall, according to Cannings, the objective is to alert surveillance teams to potential fraud indications that may have eluded them rather than to replace human searches.