It has been half a century since the birth of artificial intelligence. In 2019, after the efforts of several generations, we have ushered in a critical year for the large-scale application of artificial intelligence. Among all vertical industries, the most urgent application of innovation and technology enabling transformation and upgrading is the financial industry. Banks, insurance companies and other institutions are reducing capacity and enhancing efficiency through scientific and technological means, and integrating resources to improve their competitiveness.
On the one hand, the combination of science and technology and finance enriches the application scenarios of financial business and promotes the rapid development of financial business. On the other hand, due to the strong external attributes of finance, the characteristics of the industry under strong supervision are determined. The Banking and Insurance Regulatory Commission and China Securities Regulatory Commission frequently issue double-record policies and regulations, and the compliance audit workload of witness business is increasing.
Facing the urgency of competition and business development, a fintech competition has begun in the field of AI innovation and application, and the field of customer service quality inspection is one of the most extensive scenes of fintech landing in AI.
It is urgent for artificial intelligence technology to solve the problem of quality inspection
"After listening to recordings and reviewing documents for eight hours a day, I feel bad!"
When it comes to quality inspection, Guo, a quality inspector in an insurance institution, always says, "It usually takes at least 8 minutes to test a business file, and some recordings need to be listened to several times."
The main purpose of quality inspection in enterprise call center is to test the working quality and efficiency of customer service personnel and effectively improve the overall level and quality of customer service. However, a lot of repetitive phone work makes inspectors tired and the quality control results are not satisfactory.
The call center data volume is too large and can only be sampled. Quality inspector subjective judgment, the effect is not accurate enough; Tabular statistics of quality inspection results are not conducive to big data analysis......
This is the pain point of quality inspection in enterprise call centers, especially in finance and other industries with massive customer service business.
At the same time, enterprises gradually attach importance to customer service and the concept of customer success, which brings greater demand for customer service voice. When enterprises grow rapidly and the business volume of call center keeps rising, the contribution of traditional quality inspection to the improvement of customer service quality is a drop in the water, which can no longer meet the new needs of enterprises. Take the banking industry as an example, the current average quality inspection coverage rate of the customer service center of the banking industry is only 5%. Whether it is operational risk, customer dissatisfaction or even the number of complaints, it will result in an unpleasant result.
With the advent of artificial intelligence, ASR(automatic speech recognition) technology is gradually mature, which lays the foundation for automated voice quality inspection. ASR's ability is based on intelligent rules to analyze the dialogue content from the recording and text, and conduct the secondary verification of service data with man-machine cooperation to explore the problems and opportunities in the dialogue. So as to improve the quality inspection efficiency and accuracy of the enterprise, this is the service mission of the intelligent quality inspection solution.
News bird intelligent quality control innovation and compared with the traditional model advantages
As a leading provider of intelligent cloud customer service solutions, Inbird Software has always been customer-centered and pioneered innovation since its establishment 18 years ago, applying intelligent technology to intelligent electricity marketing, intelligent collection, intelligent quality inspection and other business scenarios. Its intelligent quality inspection has enabled the customer contact center of the first Internet insurance company in China, helping it realize intelligent upgrade of business system. At the same time, it is highly compatible with enterprise native systems and call centers, enabling a more secure and efficient upgrade from manual inspection to intelligent inspection.
By using ASR, NLU, keyword retrieval and matching, multi-condition deep recursion and judgment and other technologies, the intelligent quality control system of Infobiao carries out 100% full and fully automatic quality control monitoring on customer contact data, and uses data mining, knowledge graph and other technologies to conduct cluster analysis on the full data.
Through the comprehensive comparison with the traditional manual quality inspection energy efficiency and value, it can be seen that in terms of coverage, the average manual quality inspection rate is only about 2%, while the intelligent quality inspection can reach 100%. In terms of the cost of voice quality inspection, the average manual quality inspection is 1.1-1.5 yuan/minute, while the intelligent quality inspection can be reduced by 20 times to 0.05-0.09 yuan/minute; In addition, the fastest manual quality inspection found problems need to be inspected every other day, the corresponding speed is more than 24 hours, and the bird intelligent quality inspection can respond quickly in 10 minutes, efficiency is increased more than a hundred times; At the same time, in training cost, management cost, automation process and many other aspects, the intelligent quality control system has incomparable advantages.
Business module of intelligent quality inspection applied to quality inspection service of insurance companies:
(1) Quality inspection part: It includes defining the scoring system, creating the quality inspection model, and setting the rules of detection recording, including "service etiquette and norms", "compliance", "business norms", etc.
(2) Recording part: The quality inspection records the data display of the audio transfer text, the score of the quality inspection, the matching status of the quality inspection items and the location viewing.
(3) Statistical part: Statistical analysis of agent score distribution, agent group score distribution, statistical analysis of the number of quality inspection recordings over time, statistical analysis of score trigger times over time and other aspects of dozens of statistical analysis.
Application of the business quality inspection model of Shinebird software, in the process of the actual implementation of the business cycle, constantly add, modify and learn the quality inspection content, so that the machine can follow this set of continuous optimization and progressive mode, can adapt to the needs of large-scale business change and development in the long term, these new intelligent business application support systems and solutions, Not only will it improve risk screening, but it will also help reduce costs.
On the basis of the existing voice platform and all-media interactive customer service system, the intelligent voice semantic analysis platform can be built by using intelligent speech semantic analysis technology, which can support the in-depth analysis of enterprise customer service data. For example, data mining technology can be used to further analyze customer preferences and habits, and make customer portraits. Conduct in-depth research on customer attributes, needs, attitudes and other subareas to provide more comprehensive and in-depth data support and information feedback for product design and marketing. The semantic analysis technology is used to monitor the compliance of agents in handling risky traffic and to follow up possible risk situations or events to avoid risks.
Insurance companies are not the only ones actively upgrading fintech services
Through the application of innovative technologies such as intelligent quality inspection system, Newsbird software provides strong technical support for the digital transformation and upgrading of financial institutions, helps enterprises to rapidly improve rapid deployment, enhance business capacity, long-term adaptation ability, and free processing capacity of large traffic and high concurrency business, and improve the competitiveness of the ecosystem in which they are operating. Under the business opportunity of the new closed-loop data business mode, Achieve efficiency and cost reduction, business innovation including accurate flow realization and all-round performance growth.
At present, the commercialization process of underlying AI technology is obviously accelerating. Enterprises can consider using AI technology to create more value for themselves, and free up human resources to do work that can generate more value. The combination of human thinking ability and AI employees' executive ability can not only reduce costs and increase efficiency, but also improve the innovation ability of enterprises, so as to steadily enhance the value of enterprises. Supported by strong innovation in the field of AI, Shinebird Software is interpreting the connotation of intelligent finance enabled by innovation and technology with actions. At the same time, it can be expected that with numerous innovative technologies, Infobiao software will certainly deepen its efforts in more financial fields in the future, providing a positive boost to the innovation and development of the financial industry.
