SoFi Integrates Galileo’s Conversational AI Into Personal Finance App

SoFi Technologies app

SoFi Technologies has integrated Galileo Financial Technologies’ conversational artificial intelligence (AI) engine into its personal finance app.

The intelligent digital assistant (IDA), Cyberbank Konecta, has increased member satisfaction, improved response time by 65%, and freed up agents to solve more complex and higher-touch problems, the companies said in a Tuesday (Aug. 8) press release.

“Cyberbank Konecta’s ability to efficiently manage conversations is enormously beneficial for increasing member satisfaction and building loyalty,” Aaron J. Webster, SoFi chief risk officer and global head of operations, said in the release.

Designed for use by banks, credit unions, FinTechs and non-financial brands, Cyberbank Konecta delivers a human-like experience that eliminates the friction caused by legacy chatbot solutions, according to the press release.

The IDA is implemented via Galileo’s flexible application programming interfaces (APIs) and AI-driven technology, the release said.

“Legacy chatbots lack a deep understanding of human emotions and sentiment, whereas intelligent digital assistants use advanced natural language processing to analyze and interact in a more human-like way,” Galileo Chief Product Officer David Feuer said in the release. “Cyberbank Konecta is a conversational AI-powered IDA that improves customer engagement and loyalty by tailoring each customer interaction in real-time and infusing a human touch when needed.”

Galileo launched Cyberbank Konecta in March, saying the conversational AI engine can handle 80% of common inquiries for banks, credit unions, FinTechs and nonfinancial brands, including customer onboarding, support and other interactions.

The IDA works across any digital channel, recognizes voice and text, understands any language and learns from each customer interaction.

Today’s AI tools have the ability to learn from and adapt to circumstances on their own by activating high dimensional data sets in what is called “deep learning,” rather than requiring a manual intervention when a process speed bump occurs, Galileo Head of Product Strategy Michael Haney told PYMNTS in an interview posted in March.

These capabilities fix one of the bigger historical problems with rules engines and represent an evolution from earlier chatbots that tended to follow more binary “press 1 or press 2” pathways, Haney said at the time.

“We have this deep learning technology called sentiment analysis that allows us to understand if the customer is getting frustrated,” Haney said. “It flags things like, are they getting angry? How are they feeling? And allows us to shift them to a human interaction that might be able to help the situation without leaving the channel or losing all the chat history.”