① The KPMG report points out that in directly providing investment advice to customers, AIGC still needs to be cautious due to unclear relevant regulations and issues such as data security and data privacy; ② The development of regulatory technology will increasingly rely on technological means to achieve more efficient and accurate supervision.
Financial Services Association, January 16 (Reporters Shen Shuhong and Zhou Xiaoya) Currently, the rapid penetration of next-generation information technology into various industries is the general trend, and the financial industry is the first priority. Financial services have gradually evolved in the innovation and development of fintech, have begun a new situation of digital transformation, and have gradually become a new engine for the transformation and upgrading of the entire industry and industry chain.
Recently, KPMG released the double 50 list of Chinese fintech companies and the annual trend report, showing that the development of the financial model will have a profound impact on the fintech industry paradigm. It is expected that with the maturity of AIGC technology, wealth management institutions will explore more application scenarios of the big model to improve efficiency and service upgrades. However, in directly providing investment advice to customers, AIGC still needs to be cautious due to unclear relevant regulations and issues such as data security and data privacy.
Regulatory technology is also expected to use big models to improve the efficiency of supervision. According to the report, the rapid development of emerging technologies such as AIGC provides room for imagination for the development of financial supervision technology, and the development of regulatory technology will increasingly rely on technological methods to achieve more efficient and accurate supervision. At the same time, the development of regulatory technology will also promote fintech innovation and empower the financial industry to further digital transformation.
“China's financial supervision system is undergoing large-scale upgrading. The more this is the case, the more it is necessary for enterprises to quickly follow up on risk events in their respective segments, deeply understand regulatory changes, anticipate and perceive regulatory companies' compliance pain points, quickly transform regulatory requirements and expert experience formed from case studies, and achieve iterative upgrading of products and services.” Wang Dapeng, KPMG's partner in charge of financial risk and regulatory technology in China, pointed out.
The big model is expected to improve the efficiency of financial supervision
Huang Aizhou, KPMG's leading partner in fintech in China, explained that in the process of digital transformation of the financial industry, the three pillars required to implement a large vertical model of the industry: algorithms, computing power, and data have unique advantages over other industries. He expects that as the underlying big model shifts from incremental to the inventory stage, competing for quality and land will become the focus of competition, and the competitive advantages of enterprises that drive the reasoning side of the model will be further revealed.
The above double 50 list of Chinese fintech companies and the annual trend report show that the development of the financial model will have a profound impact on the fintech industry paradigm, such as changes in AI perceptions and ideas, reshaping customer service processes and experiences, improving risk management, improving the efficiency of financial services, and innovating financial business forms.
Among them, the explosive development of AIGC since the end of 2022 has brought huge room for imagination to the financial industry. Fortune technology companies apply the data and experience they have accumulated in the field of AI applications to financial model training to provide support for wealth management business scenarios such as investment, investment research, and marketing. The report predicts that as AIGC technology matures, wealth management institutions will explore more application scenarios for large models to improve efficiency and service upgrades. However, in directly providing investment advice to customers, AIGC still needs to be cautious due to unclear relevant regulations and issues such as data security and data privacy. On the other hand, Fortune Technology companies are actively providing the latest technical solutions for large and medium-sized wealth management institutions, gradually improving the efficiency, stability and autonomy of core systems through the use of distributed technology such as modularity and decentralization.
Regulatory technology is also expected to use big models to improve the efficiency of supervision. According to the report, the rapid development of emerging technologies such as AIGC provides room for imagination for the development of financial supervision technology, and the development of regulatory technology will increasingly rely on technological methods to achieve more efficient and accurate supervision. At the same time, the development of regulatory technology will also promote fintech innovation and empower the financial industry to further digital transformation.
Wang Dapeng, KPMG's partner in charge of risk and regulatory technology in China, observed that at present, most of the more successful domestic regulatory technology applications are in horizontal, narrow and vertical fields. The root cause is that supervision and compliance are still based on expert knowledge and experience, and it is necessary to start from a deep understanding of the business to informatize and digitize experience.
“The number and degree of impact of risk incidents has increased in recent years. China's financial supervision system is undergoing large-scale upgrades. The more this is the case, the more enterprises need to stick to their original intentions. In their respective segments, they also need to quickly follow up on risk events, deeply understand regulatory changes, anticipate and perceive compliance pain points of supervised enterprises, and rapidly transform expert experience formed from regulatory requirements and case studies to achieve iterative upgrading of products and services.”
At the same time, he believes that in order to strengthen collaboration with other fintech companies or technology companies, regulatory technology companies also need enterprises in other fields to cross borders into the field of regulatory technology, so that new technologies can be explored and applied, and achieve more results in intelligence on the basis of maintaining the speed of informatization and digitalization.
The technical requirements behind behavioral regulation and penetrating regulation
The above report mentioned that the current financial system structure is becoming more and more complex, and financial supervision places more emphasis on behavioral supervision and penetrating supervision. In response, Wang Dapeng believes that the purpose of behavioral supervision and penetrating supervision is to ensure that regulatory requirements are effectively implemented, no matter how complex the transaction structure is or how microscopic the exhibition behavior is. Without drastically increasing the cost of compliance, this cannot be achieved by traditional means; this must be achieved through regulatory technology.
However, this places two demands on regulatory technology. On the one hand, it is necessary to build and make good use of a data asset system based on digitalization of the financial industry, effectively integrate data according to supervision and compliance, and achieve upward and downward information penetration, so as to establish effective supervision and compliance management, such as comprehensive compliance management from investors to lower-level assets in the field of asset management.
On the other hand, regulatory technology companies are strengthening in-depth capacity building in segmented fields and exploring how to use artificial intelligence (especially large model technology) to recognize, analyze, and interpret behavior based on text, images, sounds, etc., so as to establish technology application solutions for behavioral supervision and compliance.
According to Wang Dapeng, regulatory technology achieved phased results in 2023, but supervision and compliance is a highly complex systematic project, and changes are deepening and deepening, and need to be based on expert understanding and experience. He believes that most of the current successful regulatory technology practices are applications generated by the informatization and digitization of artificial actions and processes based on expert experience. However, intelligent applications mainly focus on application fields such as identification, prediction, and judgment using small models, and the development of small models is also inseparable from expert knowledge.
“We look forward to future big model applications that can read regulatory requirements, compare and analyze corporate compliance, and even generate compliance recommendations, and enable machines to assist experts or even replace experts on specific tasks. On the basis of machine understanding of regulatory requirements, it is also possible to greatly improve the speed of development and iterative upgrading of regulatory technology applications.” Wang Dapeng said.