The report showcases Behavioral Signals' recent deployment with a European national bank as a commercial example that follows the 3 best practices product managers can implement to drive adoption of emotion AI technology. Behavioral Signals created a predictive model using conversational analytics and behavior traits to pair the customers with bank agents that best suited them in order to recover and restructure as many non-performing loans as possible through its in-house call center.
"The results from the live-data implementation point to a 20% increase in active debt restructuring applications with 7.6% fewer calls," said Rana Gujral, CEO at Behavioral Signals. "These results correspond to approximately $7.5M of additional restructured debt over the course of this implementation which extrapolates into a $1.5M upside per agent per year or a total of $300M annual upside for the bank."
The ability for Behavioral Signals' AI to predict intent by distinguishing pitch and tonal variance from the audio instead of the actual words being spoken makes their data exceptionally rich and accurate, which contributed to the technology adoption at the bank. As a result, advanced use cases such as Behavioral Profile Pairing are possible without ever converting the audio to text. This novel approach also delivers enhanced privacy. No other sensitive customer data, such as demographics and transactional data, had to be mined for this purpose.
About Behavioral Signals Founded in 2016, Behavioral Signals enhances communication between humans and human-to-machine by deducing intelligent and actionable insights from voice using deep learning and NLP. Behavioral Signals offers a new level of customer understanding and leverages its advanced acoustics engine to not only discover genuine emotion but also predict the speaker's intent via behavioral analysis. Offices are in Europe and Los Angeles, CA.https://behavioralsignals.com/