The power of technology “exceeds any moment in our history,” kutsville, a silicon valley futurist, once pointed out. To do a good job in financial science and technology innovation, quickly occupying the highland of new technology applications such as “ABCD + 5g” has become the key to victory. Among them, building an AI technology platform has become an inevitable choice for financial institutions. What are the implications of these AI platforms for the banking industry? What is the story behind the landing of the platform and its partners? We take a bank as an example to deeply investigate and analyze the innovative practice of banks in artificial intelligence technology.
1.AI decisive battle of banking industry
In terms of R & D and application of new technologies, Dahang is building new technology innovation platforms such as artificial intelligence, blockchain, cloud computing, big data and Internet of things, so as to improve scientific and technological agility and iterative innovation ability. Among them, the disruptive impact of AI on the banking industry in the long term has been reflected in many aspects. According to a study by the Financial Research Institute of the central bank, AI is expected to become the next profit growth point of commercial banks; McKinsey estimates that AI technology can create up to $1 trillion of incremental value for the global banking industry every year.
An AI showdown has come.From the positive impact of AI, it can improve the bank’s profits, accelerate the innovation cycle, improve the operation efficiency, and provide customers with personalized, comprehensive and scenario based financial services in an all-round way; On the contrary, if the banking industry does not put AI in a strategic position, it will face the risk of being eliminated.
At present, large and medium-sized banks are vigorously developing their retail financial business, and customer experience and value mining are very important. Behind this, AI has great application potential. McKinsey found that more and more banking leaders have begun to deploy advanced artificial intelligence through a systematic approach and integrate it into the whole life cycle of digital operation through the front and back ends.
Although it has become a consensus to take artificial intelligence technology as an important breakthrough in financial services. However, in the banking industry, AI application innovation has some problems, such as high technical threshold and effective combination with financial business. At the same time, banks are also required to make overall planning and planning for various project applications, so as to avoid repeated construction in relevant capacity development and application.
Taking a bank as an example, building a unified artificial intelligence platform for the whole bank will not only help to meet the business needs of the whole bank in the field of artificial intelligence, but also help the bank to complete its own capacity-building and accumulation in artificial intelligence. However, it is not so easy for the artificial intelligence platform to really land in the banking industry.
2.Breakthrough of bank AI platform: cooperation and joint construction
Different from the previous information revolution, the financial competition in the digital era is not only the competition of new technological innovation platforms, but also the competition between ecology. The banking industry needs to break through a series of obstacles such as technologies and standards in order to quickly land and comprehensively improve the ability of new technology platforms.
A survey by the banking association pointed out that 78% of the research banks have applied artificial intelligence to business scenarios, but the standards and specifications for the application of emerging technologies in the financial field are still insufficient. For the banking industry, talents, delivery speed and delivery channels are also difficult problems faced by AI applications.
Where should the banking industry go? The above research suggests that small and medium-sized banks can cooperate with third-party institutions, and large banks can also improve the application and R & D capacity of cutting-edge financial technology through self-research or cooperative R & D.
In other words, no financial institution can independently build the ability and ecology of artificial intelligence to deal with digitization. In the process of accelerating the layout of financial science and technology and the construction of information system, it is inevitable to rely on external forces. What experiences can be used for reference in the cooperation with external institutions in the exploration of breaking the situation, artificial intelligence technology innovation and building the medium-sized capacity of financial technology in the banking industry?
Taking a bank as an example, in the process of increasing AI innovation, the primary demand is to ensure that the project can fully meet the situation and needs of the bank, complete the sorting of business system and data ecology in the bank, and solve the pain points of R & D and application of artificial intelligence technology. Considering the huge number of users, high standards, high security and other factors in the banking industry, banks have very strict requirements for partners.