On March 26, at the "Data Intelligence Reshaping Entities: 2022 Smart Data Forum" hosted by China Times, the "Financial Digital Transformation under Data Intelligence 2022 Annual Report" ( hereinafter referred to as the "Report") is officially released.
Following the first year of compliance in 2021 and the three data methods in place, this is the first panoramic report in China based on first-hand research on "data intelligence + finance" cases. Based on the perspective of compliance, it deeply analyzes credit risk control, financial marketing, and Five scenarios of three-party payment, supply chain finance, and insurance technology, explaining how the dual elements of "data and technology" drive the digital transformation of the scenario, asking for directions, and offering two dry goods for the majority of enterprises that are struggling with digital transformation. :
A map - a detailed review of the industry map and representative companies of the smart data + financial track.
A handbook—describes in detail the demonstration cases of intelligent data in financial vertical scenarios.
In the era of intelligent finance,
data mining and governance capabilities are the core competitiveness
In recent years, with the application of technologies such as big data, cloud computing, artificial intelligence and blockchain to the financial industry, the financial industry has undergone profound changes. On January 26, 2022, the China Banking and Insurance Regulatory Commission issued the "Guiding Opinions on the Digital Transformation of the Banking and Insurance Industry", stating that it is necessary to "comprehensively promote the digital transformation of the banking and insurance industries and promote high-quality financial development." Among them, "digitalization of business operation and management" is put forward as a key aspect, including: actively develop industrial digital finance, vigorously promote the digital transformation of personal financial services, improve the digitalization level of financial market transaction business, build a digital operation service system, build a safe, efficient, and win-win cooperation The financial service ecology, efforts to strengthen the construction of digital risk control capabilities, etc., cover all aspects of business management of financial institutions. The signal is very clear. In the digital age, the financial industry's demand for digital transformation is more urgent and urgent.
However, there are many roadblocks and challenges under the demand, and financial institutions are also facing many problems that need to be solved in the digital transformation. How to transform? Where to turn? What are the industry experiences and lessons worth learning? What are the prospects and trends of future industry development? How to give full play to the role of data elements and use the massive data assets of the financial industry to better serve the real economy. These are issues of great concern to financial practitioners, said Ran Xuedong, deputy editor-in-chief of China Times.
In this context, the computing power think tank teamed up with the China Times Financial Research Institute. It took two years to visit and investigate a number of top financial institutions and innovative financial technology companies. A number of representative excellent cases, and finally completed the "Financial Digital Transformation Report 2022 under Data Intelligence".
Yan Li, the founder of the computing power think tank, interpreted the "Report". Yan Li pointed out that data has been considered a very important asset by the financial industry, and data mining and governance capabilities are one of the core competitiveness of a financial institution. At present, the digital transformation of the financial industry has entered a new stage, and the underlying logic of financial services is undergoing major changes.
On the other hand, the "Report" shows that the current development of data smart finance is also facing some challenges, mainly at the data level, technical level, scenario application level, and regulatory level. For example, data compliance acquisition, calculation and governance, data classification mechanism need to be improved, artificial intelligence can not fully achieve independent decision-making, and data isolation is serious. The phenomenon of "narrow scenarios" and "shallow applications" in smart finance is more obvious.
The development of digital smart finance is also showing new trends. Specifically, the implementation of smart finance will focus on business empowerment in the short term and model innovation in the long term. Model innovation has also become the key for future financial institutions to reduce costs and increase efficiency, grasp core competitiveness, and promote industry reshuffle. Smart finance realizes the diversification of financial organization forms by building a huge fintech service ecosystem. The "virtualization" and "intelligence" of future financial services will be the only way for model innovation. In addition, it is worth noting that 2B business has gradually replaced 2C business as the focus of market competition.
Yan Li summarized the characteristics of the digital transformation of financial scenarios into four points, namely channel integration, service integration, deep integration, and business scenario.
In-depth analysis of the five major scenarios of "credit, marketing, insurance, payment, and supply chain" to take the
pulse of the digital transformation roadmap
The "Report" makes a detailed analysis of the current status of data intelligence transformation in the financial industry based on five scenarios: credit risk control, financial marketing, insurance technology, third-party payment, and supply chain finance.
In the credit risk control scenario, intelligent risk control technology is becoming more and more mature. Combine big data, artificial intelligence and other technologies with risk control, use artificial intelligence to find user behavior patterns reflected behind the data, and inertial patterns that may be helpful for risk management, so as to identify, select and manage risks in advance.
For example, Immediate Consumption has built a new generation of financial big data intelligent risk control platform, mainly based on self-developed cross-source SQL engine, decision analysis, model real-time prediction and other technologies, which are used for real-time credit approval, anti-fraud, and risk control marketing in the financial industry. In other scenarios, it solves technical problems such as "data islands" in the field of real-time risk control, difficulties in data integration, high computing technology thresholds, and high storage costs, as well as low data utilization caused by traditional risk control systems that are difficult to form risk control panorama data assets. The platform can quickly and flexibly adapt and optimize risk control strategies, help the healthy development of credit business, and help financial institutions achieve the goals of stable risk control and rapid business development. This platform, Luma credit system, and Gcolo collection system constitute a risk management system for immediate consumer independent property rights.
In the financial marketing scenario, how to achieve marketing intelligence, mobility and customer experience is a topic of great concern to many financial practitioners. The development and application of financial technology has formed a strong support for the transformation of financial digital marketing.
For example, Suoxinda Holdings' "Consonance Integrated Intelligent Marketing Platform" includes six sub-products: intelligent marketing platform, real-time marketing platform, personalized recommendation system, label management system, marketing content management system, and user portrait system, which can provide financial institutions with The end-to-end integrated marketing solution of intelligence, mobility and ultimate customer experience helps financial institutions to conduct comprehensive links and refined operations with customers.
Suoxinda's "Consonance" product has been implemented in many financial institutions. Suoxinda has participated in the construction of an intelligent marketing platform for a joint-stock bank since 2015. It has helped the bank to accumulate more than 150 marketing scenarios, accumulated more than 300 intelligent models, formulated more than 1,000 marketing strategies, and liberated a lot of labor. The marketing management and execution of the original offline operations are fully online, and strategies can be automatically executed to support differentiated scenarios. Suoxinda also helps many small and medium-sized banks build data-driven intelligent marketing. The introduction of Suoxinda's "Lingxi" intelligent marketing platform has solved the problems of overly complex system operations, scattered data, and low efficiency in digital marketing for small and medium-sized banks.
In the context of insurance technology and the digital age, insurance companies establish a digital support system to achieve digital insight into customers, and then achieve accurate matching of personalized, customized, and differentiated products and services. With the help of digital means, full-scenario services have become the mainstream development trend of the insurance industry.
For example, Lima Technology provides insurance operators with comprehensive insurance digital solutions including insurance SaaS and product supply chain. On the enterprise management side, Lima Technology helps insurance institutions realize the digital management of the whole process of organizational development-business operation-financial settlement. In terms of organizational digitalization, Lima Technology provides flexible organizational digital products for agency agencies. At the same time, Lima Technology also provides a one-stop data analysis platform for internal business personnel and management personnel of merchants.
Focusing on transactions, Lima Technology empowers the whole process of insurance marketing transformation, accurately locates target users through big data and cloud computing, judges the needs of user groups, realizes content management for thousands of people, and achieves automated intelligent operations and personalized marketing The promotion not only helps companies reduce labor costs, but also improves the professionalism of insurance consulting as a whole, greatly improves user experience, and increases the turnover rate of agents.
In the third-party payment scenario, data intelligence opened the second half of smart payment. The open innovation of big data and artificial intelligence has accelerated the intelligentization process of the payment industry. Supplemented by cloud computing capabilities, payment institutions have realized platform-based intelligent data management, and innovative products such as facial recognition payment and sensorless payment have been launched one after another. In the future, in addition to the basic functions of payment, third-party payment institutions will also need to deeply participate in merchant operations through various technical means.
In the supply chain financial scenario, the application of data intelligence has completed the development of centralization, online, and platformization, and has begun to evolve towards intelligence. For example, banks can embed new technologies such as the Internet of Things and blockchain into transaction links, and use technologies such as mobile sensing video, electronic fences, satellite positioning, and radio frequency identification to implement remote monitoring of logistics and inventory commodities, so as to ensure the authenticity and rationality of transactions. Exercising review and professional judgment.