It is here now providing convenient solutions for us. That's why more and more industries are investing in artificial intelligence to improve business operations and maximize revenues. The financial market industry is one of them. Automation is doing, while AI is thinking. It seems like a long time ago when only high net worth individuals could own stock shares over back-and-forth calls with their personal stockbrokers.
Artificial Intelligence is no new concept. The phrase was first coined by John McCarthy in 1956, when he invited a group of researchers to discuss the notion of'thinking machines' during a conference at Dartmouth College. Since then, it has been a point of fascination for scientists, academics, software developers, and moviemakers alike. Fast-forward to today where you'll find lots of examples hiding in plain sight. From digital assistants like Amazon's Alexa or Apple's Siri, who use AI to learn from user interactions, to automated email responses and search engines predicting what you're looking for.
Customer service, while likened to back-office or desk jobs, has long been outsourced to third parties (call centres) for resolving customer queries. Over the years, outsourcing customer support services has hampered organizational flexibility, brand value, and privacy. With some automation, the digital revolution shifted businesses toward adopting Interactive Voice Response (IVR) technology for handling and prioritizing high volume of calls, simplifying customer service processes, and cutting overhead expenses. Although IVR allowed companies to automate their customer support and increase professionalism, the complex routing mechanism and inflexibility resulted in customers dissatisfaction towards an organization or a brand. In today's highly connected and personalized world, customers demand instant resolution of grievances and high-quality customer service at anytime, anywhere.
Artificial Intelligence (AI) has come a long way since 2016, when AlphaGO, a computer program, first defeated an 18-time world champion at the game of GO. Artificial intelligence is profoundly increasing value across a range of industries. The banking and finance industry is no exception. There is a transformative impact to fully adopting AI in banking and finance. According to a study by Mckinsey, AI can add up to $1 Trillion of additional value to the global banking industry annually.
Natural language processing (NLP) is a subfield of AI and linguistics which enables computers to understand, interpret and manipulate human language. Although NLP faces different challenges due to the difficulty of human language, this did not become an obstacle in the face of its growth. The global NLP market was estimated at $5B in 2018 and is expected to reach $43B by 2025, and this exponential growth can mostly be attributed to the vast use cases of NLP in every industry today. You may already be familiar with many NLP applications such as autocorrection, translation, or chatbots. However, NLP is the cornerstone of numerous applications we use every day without even noticing.
Our platform predicts user intentions by systematically analysing conversations and predictably interpreting not just what enquirers say, but why they say it. 'INTNT-ENGINE has turned our bot around. Our escalation to live-chat has dropped from 21% to 6% while customer satisfaction has increased from 1 to 4 out of 5 star.' Andy Leong, Senior Product Manager, FWD Insurance. Our INTNT-ENGINE picks up conversational tells to interpret the enquirer need. It brings empathy and intelligence to bot dialogue.
Level AI, an early-stage startup from a former member of the Alexa product team, wants to help companies process customer service calls faster by understanding the interactions they're having with customers in real time. Today the company launched publicly, while announcing a $13 million Series A led by Battery Ventures, with help from seed investors Eniac and Village Global as well as some unnamed angels. Battery's Neeraj Agrawal will be joining the startup's board under the terms of the agreement. The company reports it has now raised $15 million, including an earlier $2 million seed. Company founder Ashish Nagar helped run product for the Amazon Alexa team, working on an experimental project to get Alexa to have an extended human conversation.
Imagine your sales agent pitching a credit card to a student with no income to pay back! According to a survey, 85% of sales agents have committed mistakes due to incorrect user data. You can integrate one of the finest Customer Relationship Management(CRM) software; sales goals will look like Everest. Fortunately, there is a solution- "chatbot." They can help aggregate valuable user data, enhance the entire customer support system, and offer more extraordinary customer journeys.
All the sessions from Transform 2021 are available on-demand now. Deepbrain AI (formerly Moneybrain), a conversational AI startup based in Seoul, South Korea, has raised $44 million in a series B round led by Korea Development Bank at a post-money valuation of $180 million. The capital will be used to expand the company's customer base and operations globally, CEO Eric Jang said in a statement, with a particular emphasis on the U.S. Deepbrain provides a range of AI-powered customer service products, but its focus is on "synthetic humans," or human-like avatars that respond to natural language questions. Because the pandemic makes online meetups a regular occurrence, the concept of "virtual people" is gaining steam. Startups including Soul Machines, Brud, Wave, Samsung-backed STAR Labs, the AI Foundation, and Deepbrain aim to will a sort of "metaverse" into existence by pursuing AI techniques that can mimic the experience of speaking with a human being (for example, a support agent).
Do you ever ask Siri if it's going to rain tomorrow? Or ask Alexa to play your favourite song? For millions of us, having conversational interactions with technology has quickly become second nature. This presents a real challenge for many financial institutions, whose traditional, interactive voice response (IVR) systems often fall far below the expectations set by the voice-enabled virtual assistants of their customers' smartphones and smart speakers. Even as banks race to deliver intelligent, conversational self-service over the telephone, they must also work to keep pace with the digital services of online banks and fintech pioneers.