Twitter Facebook LinkedIn Flipboard 0 This article features excerpts from my recent interview with Krish Gopalan, the founder of the AI-Powered Digital experience platform Flaist. Krish has over 15 years of experience in the technology industry working with multiple startups and multi-billion dollar organizations, including Citibank, Mastercard, HPE, ArcSight, and Oracle. Artificial intelligence has just made a giant leap forward, and it’s unlike anything you have ever seen. Retail banks and payment solution companies like Visa are now testing artificial intelligence that can detect anger, frustration, and other human emotions over the phone and online. So, if your customer is melting down, the AI agent can quickly transfer him or her to a more experienced human customer service agent. The AI-enabled agent is also equipped with a vocabulary that reduces tension in these situations by using popular “emotionally intelligent” phrases with the customer. It’s also smart enough to detect accents, dialects, and linguistics. So if you’re calling from India or the UK, Texas or New York, the AI can detect the different pronunciations and respond in a more familiar voice. This technology is extremely valuable in the Middle East where the culture gap among countries and regions is crucial to making personal connections. And unlike older generations of AI chatbots, this latest customer service technology can identify which gender the customer prefers to speak with and respond with that gender’s voice. All of this takes place without the customers even knowing they’re speaking with an AI agent. AI learns this information from previous customer interactions that are maintained in the financial institution’s customer databases, continuously improving so that any future interactions can be handled more accurately and efficiently. How the Technology Works The AI technology developed by San Francisco-based fintech startup, Flaist, uses a “plug and play” framework that allows for quick and easy integration within the enterprise applications such as websites, mobile apps, and social communication platforms (e.g. Facebook Messenger and Whatsapp). It is also customizable, allowing banks and financial institutions to rebrand it under their own name and color schemes. According to Founder, Krish Gopalan, “early pilot programs have shown the AI customer service platform can cut IT costs by up to 25 percent, while providing the bank with new opportunities to sell existing services and increase customer loyalty.” AI-enabled customer service can cut IT costs by up to 25 percent – Krish Gopalan AI can also generate new revenue by upselling existing services based on the customer’s questions. For example, if the bank knows the customer is a business client, the AI can offer advice on Small Business Administration loans. Or if the customer has bad credit, the AI can offer measures to improve their current credit score. The new technology allows customers to share their private data over a secure platform, with a personal finance management tool that helps them with their financial planning, as well as budgeting. The Takeaway In the past, smaller financial institutions such as credit unions, community, and regional banks have not had the resources to access cutting edge AI and machine learning technologies. As a result, they struggled to compete with the larger global financial institutions that can afford to experiment and readily adopt the latest technology. New AI technologies are helping to level the playing field within the financial services industry. – Krish Gopalan The availability of this new AI is democratizing the digital transformation process, allowing financial institutions regardless of size and resources to provide quality customer service interactions. The technology is also helping to free up human customer service representatives, allowing these financial institutions to reallocate their resources to other areas where human interaction will have greater impact. While the customer service function is ripe for the application of AI and machine learning, there will always be winners, losers, hype and hoax. Twitter Tweet Facebook Share Email This article originally appeared on TopRight Partners and has been republished with permission.Find out how to syndicate your content with B2C Author: Dave SuttonView full profile ›More by this author:What Are Marketplace Analytics?SSO: What It Is and Why You Need ItPrint is Not Dead, Long Live Brochures!