With technology taking us so far, it is easy to forget about what makes us humans… Before Skynet takes over. Emotions, feelings, a range of things that are not easily replicable or understandable by machines. Or can they? It is not obvious to associate emotion with artificial intelligence, but maybe it should be. Fintech Review asked a few questions to Rana Gujral, CEO of Behavioral Signals.
Tell us more about Behavioral Signals. What is your elevator pitch?
Behavioral Signals bridge the communication gap between humans and machines by introducing emotional intelligence, from speech, into conversations with AI. For example, AI-Mediated Conversations (AIMC), one of our two flagship products, uses artificial intelligence and tone of voice to create this perfect match between a customer and an agent who can best handle the customer’s needs. This matching is built using algorithms developed over years of research. As well as our deep understanding of Natural Language Processing (NLP) and Behavioral Signal Processing.
This technology is useful in sales calls, revenue recovery calls, or in any other conversation where customer satisfaction is paramount. Whatever the objective, there is always a catalyst that allows the negotiating parties to reach the desired result. That contributing factor is usually a simple and naturally occurring human process: the affinity or rapport developed between people. It’s always the actual interaction between real humans that matters. Regardless of the type of business communication (sales call, support, collection).
Additionally, our Oliver ΑPI offering, offers a rich variety of emotional and behavioural metrics. Both via real-time and batch audio processing.
What is your background and what is the story behind the company?
I’m an entrepreneur and have been very fortunate to be a part of a few amazing journeys. In 2014, I founded TiZE, an ML-based SaaS for specialty chemicals vertical, which was acquired by Alchemy Cloud in 2016. Prior to TiZE, I led the turnaround for private-equity-backed Cricut Inc. It is a creative technology platform company dedicated to encouraging new ways for people to experience making at home to millions of users worldwide. At Cricut, I affected the turnaround from bankruptcy to profitability. I cured Cricut’s $300 million debt and shifting EBITDA from -$100 million to +$12 million. Cricut closed its IPO at a $4.2 billion valuation in March 2021. Previously, I’ve held leadership positions at Logitech S.A. and Kronos Inc.. There I was responsible for the development of best-in-class products generating billions in revenue. I also contributed towards several award-winning engineering innovations.
Behavioral Signals was founded in 2016 as a spin-off from the University of Southern California, LA. The company has been a leader in extracting emotion and behavioural patterns from speech and translating them into meaningful KPIs for businesses. We’ve pioneered a field, Behavioral Signal Processing, based on over a decade’s worth of award-winning and patented research. It can automatically detect information from audio and measure the quality of human interaction. We’ve won numerous international engineering competitions. This has highlighted that our methods are cutting-edge and state-of-the-art, and we hold several patents in the field.
What is Emotion AI and what are the applications in financial services?
Emotional artificial intelligence, also called Emotion AI or affective computing, is being used to develop machines that are capable of reading, interpreting, responding to, and imitating human affect—the way we, as humans, experience and express emotions.
Our flagship product, AIMC, can elevate the conversation between customers and financiers. Every fiduciary interaction involves data and a human component, so AIMC is uniquely positioned to enhance the banking interface. By understanding the opportunities and challenges of integrating AIMC into banking systems, managers can unlock a vault full of possibilities.
The vast majority of banking transactions are performed without uttering a word. But when an issue appears, the customer will most definitely need to speak with somebody. AIMC is an essential tool in matching each customer with the right representative. This person will not only resolve the issue at hand but also build a good rapport between them leading to a very satisfied customer. Concern, distress, frustration, can register in our voice. A fact that an intelligent call routing technology like AIMC can detect and assist with. It can map the vocal pattern of a particular caller and match them with a representative who can best address their problem.
This process is called AI-Mediated Conversations and it is a great tool in diagnosing a customer’s demeanour. AIMC’s Emotion AI can pair you with a bank representative who is equipped to handle your complaint. without making you manoeuvre a tedious chain of messages and menu options.
According to our case studies, banks can enjoy up to an 18% increase in revenue, and 10% in customer satisfaction, by implementing AIMC. That is why Gartner Research includes AI-Mediated Conversations as a prime example in their report on three essential practices needed for the adoption of Emotion AI.
What are the main challenges faced by FIs when deploying AI?
Implementing AI isn’t just a forward-thinking way to approach finances; it is a smart way to save money. The finance industry can streamline its operations and salvage over $440 billion by the year 2023 with the help of artificial intelligence technology.
But automation does not need to be heartless. On the contrary, AI can sound the alarm and stave off a financial crisis before it consumes us. The 2008 economic meltdown took the world by surprise, but AI could foresee another recession well before it strikes. By assessing non-performing loans (NPLs) and warning bankers before they reach a “point of no return,” AI can mitigate impending doom and secure smart lending practices.
The financial sector is still hesitant in deploying novel technologies like Emotion AI. While it’s easier to consume the use of machine learning in business intelligence, because the results are perceived as quantifiable, human emotions can also be measured, quantified, and utilized to lead to better interactions and higher customer satisfaction.
Any innovation in fintech more broadly that you are really excited about?
Decentralized finance (DeFi) has been a hot topic ever since Bitcoin introduced blockchain in the early 2010s. While digital money is the obvious application for decentralized finance, it’s only a tiny part of it. DeFi is a revolution that can impact every sector of finance, from stock trading to insurance. Indeed, with $40 billion of assets currently locked in DeFi, it’s a trend that is likely to impact every aspect of finance.
Any plans for the future or product roadmap you want people to know about?
We’ve taken notice that most of our existing customers, and the market in general, are demanding a focus on customer satisfaction and experience. It is interesting that these value adds are considered as a higher priority, than improving revenue recovery or selling more products. We’ve listened and are further enabling our flagship products with an empathy model, insightful agent alerts, customer churn predictor, and a customer satisfaction score.
Meanwhile, all of these conversational outputs are used to constantly update our machine learning models, continuously improving our engine with each interaction, thus providing a better experience for our client’s customers and representatives.