In today’s “time is money” economy, companies require a sophisticated solution to reduce the huge amount of human capital employed to answer the basic end-customer queries without hampering customer service. Operating a call center with a large technical support team always increases the cost incurred by a company and call waiting oftentimes reduces customer satisfaction. This market predicament marked the genesis of MoneyBrain. Eric Se-young Jang established MoneyBrain to bring forth deep-learning-based conversational AI chatbot technology that supports multiple languages and increases the query response rate of client companies. Our chatbot helps in generating more revenue than traditional marketing activities such as incentives and product promotions. MoneyBrain increases user growth by an average of 63 percent, a metric that exponentially increases over time.
The Core Technology
MoneyBrain analyzes the intent, emotion, speech, sentiments, and other entities used by the speaker to deduce the mood changes in a conversation for the chatbot to tailor the right answers similar to that of humans. The core technology can be differentiated into static and dynamic solution. Under the Static Deep Learning Dialog Analysis solution, MoneyBrain uses Convolutional Neural Networks architecture to analyze emotion and intention behind every single sentence as well as measures customer satisfaction by analyzing multiple sentences. With the Dynamic DL Dialog Analysis solution, we provide real-time dialog analysis and bring forth concurrent recommendation of optimal counseling script during a time crunch. MoneyBrain provides a preconceived platform that can be tailored according to a client’s specific instructions. The conversation AI of MoneyBrain uses recurrent neural networks such as long and short-term memory neural network and gated recurrent units. Additionally, the flexible technology interlocks with existing systems of the clients to provide seamless customer experience.
MoneyBrain’s conversational AI introduced under the brand name PlayChat focuses on conversational analysis and serves various platforms and uses machine learning to create and train bots based on the client-specific information. The unique computing capability of PlayChat service is available in four languages including English, Korean, Chinese, and Japanese. Furthermore, the customer service chatbot provides 24/7 response and if the conversational AI fails to generate the right answers, then the customers are automatically redirected to a counselor.
The Team at the Helm
As an upcoming company, MoneyBrain employs a diverse team of highly-experienced and AI-trained personnel to provide the best chatbot technology. Each team member has a collective experience of over a decade in the R&D departments of leading companies alongside sound educational background from the best universities of South Korea such as the Seoul National University, Korea University, and KAIST. The combined knowledge of the team not only makes MoneyBrain a successful developer in the AI field but also helps them to understand the nature of human psychology and the best way to harness that for the benefit of creating a sophisticated human-like technology. The team of MoneyBrain has created a suite of advanced technologies—such as sentiment and emotion analysis, dialog engine, power and knowledge management, and optimum conversation analysis—to cater to each and every requirement of their customers.
The conversation AI of MoneyBrain uses recurrent neural networks such as long short-term memory neural network and gated recurrent units
Potential of Chatbots in the Market
MoneyBrain has created a niche in the financial sector and serves significant clients such as the Nonghyup Bank, a leading bank and Shinhan cards, a large credit card company based in South Korea. MoneyBrain utilizes deep learning and machine learning for knowledge management to enhance customer service quality by training the chatbot with datasets from the existing clients in the financial sector. This helps the chatbots to create better responses to the end consumer’s queries. With the help of MoneyBrain’s chatbot technology and the PlayChat platform, these financial institutions were able to increase their revenue, marketing activities, online presence, and cut down call center costs. They were able to free personnel from conducting the time-consuming act of answering each customer query and providing technical assistance on a daily basis. After serving the largest financial institutions in South Korea, MoneyBrain understands the problems associated with heavy cyber traffic and has trained the chatbots to handle the pressure and serve clients efficiently even under time constraints. Having experienced exponential success in the financial field, MoneyBrain is looking forward to expanding their services to the medical, retail, delivery, and other essential sectors.
Reconstructing the Future of Conversational AI
MoneyBrain plans to introduce a new line of technology— Speech Recognition/Synthesis, which will utilize voice recognition technology to bring conversational AI into the realm of voiceover call center and use natural language speech technology to address customers in multiple languages. At MoneyBrain, we are aiming to capture the global market as well as introduce Spanish and other languages to enhance the core capabilities and provide wider ranges of services to our clients. We are developing new technologies to create a paradigm shift in the market and are applying for patents to protect our core technology. Furthermore, we will soon unveil a new line of core technology specifically aimed at enhancing customer experience.