Rakuten adopts AI-based chat support for credit card queries
The new service, which becomes available today, uses the Qlofune artificial intelligence engine developed by i Focus network co., ltd.
Rakuten Card, a subsidiary of Japan’s Rakuten Inc (TYO:4755), is seeking to improve its customer service by adopting an artificial intelligence (AI) solution. According to an announcement by the company, a new chat support service based on AI engine Qlofune, becomes available today.
The solution, developed by i Focus network co., ltd., is capable of answering various customer questions, ranging from card limits to instructions on what to do in case a card gets stolen. One of the advantages of the new service is that it is available 24/7 and takes a break only during system maintenance. Furthermore, the precision of answers is gradually improved thanks to the AI engine learning capabilities, that is, the ability to analyze queries in detail and adjust answers accordingly.
For the time being, the new chat support service is available on Rakuten Card’s website. One should activate the chat support function and enter the query. The engine will do the rest.
The launch adds to Rakuten’s efforts with regard to AI solutions adoption. In April this year, Rakuten announced its partnership with IBM Japan to create the “Rakuten AI Platform,” an internal Rakuten system aiming to introduce chatbots with automatic response functions into customer support. The system was built utilizing APIs provided by IBM Watson.
As a part of the development of the new AI platform, the two companies have this year founded a Center of Competency, a virtual organization in which employees from both companies develop and implement AI technologies and which provides training and education on the AI platform for Rakuten employees.
In addition, Rakuten Securities is reported to be testing AI software designed by NEC to detect market manipulation. The new system is set to be ready for launch within the current fiscal year.
The AI software works based on learning from past cases of illegal trading. It then flags suspicious activity. It scans the market for manipulators who use techniques such as spoofing that involves placing large orders that are canceled before they are executed.
