Risk management is the cornerstone of the steady development of securities companies. Traditional risk control can hardly support the digital innovation and development of securities industry to a certain extent. The risk management department must adapt to the transformation of the new digital model as soon as possible, formulate risk control measures matching the new model according to its own characteristics, build a “intelligent risk control” system, and support the sustainable development of the business.
According to the cases of many securities customers implemented by SmartBi, this paper summarizes some construction experience of “intelligent risk control”, hoping to enlighten everyone.
1. Problems existing in traditional risk control
■ Disorganized internal data and lack of integrated control
Securities companies risk management index and risk management systems are obvious deficiencies, because do not have a unified data caliber, each department system data is difficult to form effective logic system, resulting in a large number of risk monitoring, analysis and evaluation index cannot be used, in the end is difficult to effectively realize the risk of interception, leading to risk management. At the same time, due to the lack of centralized risk data at the group level, it is impossible to achieve centralized risk control for the same customer and the same business, resulting in serious data fragmentation and prominent phenomenon of “data island”. There are hidden dangers in the security management of data rights.
■ Poor risk analysis effect and timeliness
The risk management system of securities companies is not only the necessary support for risk management, but also should have the ability of forward-looking prediction, fine management, better resource allocation and strong extension service, which can effectively prevent risks while meeting the regulatory needs and improve the ability of value creation. However, due to the lack of data analysis tools, each risk management line is unable to effectively contact data and conduct risk analysis in an effective and timely manner. Data analysis is floating on the surface and the value of data has not been fully utilized.
■ High threshold for risk model construction
Most securities companies risk management system construction is still in the response to the credit risk, operational risk, liquidity risk and compliance risk management such as stage and table management, fewer companies can achieve the real-time prediction and prevention and control of market risk, value creation and a certain distance, one of the important reasons is the lack of risk model construction ability, The lack of technical personnel with modeling and development ability makes it difficult to improve the whole level of risk management.
II. The implementation path of “intelligent risk control”
In the face of complex internal and external market environment, the “intelligent risk control” of the securities industry needs to fully touch the business and combine with the management process. With the help of SmartBi unified big data analysis platform, combined with the business scenarios of securities companies, driven by risk data platform + intelligent risk control, effective monitoring and management of risk analysis, risk early warning, risk rating and other aspects can be realized.
1. Data first — build a unified risk data platform
Based on the underlying risk index system architecture of securities companies, a unified risk data platform can be built to realize the systematic collection and processing of data and accumulate more comprehensive risk information. The construction of risk data platform also provides a basis for subsequent data analysis, which can meet the personalized needs of securities companies for analysis, early warning, display and other aspects of risk management of different types of risks and different businesses, and also improves the efficiency of risk management.
Securities companies can also build a sound data rights system through the data platform, face the data to all lines of personnel, gradually cover the whole business lines, subsidiaries and branches, optimize all kinds of risk processing processes, effectively prevent, identify and resolve risks, and finally realize real-time and penetrating management of business operation risks.
2. Deepening business — improving the ability of risk data analysis
In order to stimulate the enthusiasm of business personnel for data analysis and improve the ability of business personnel to analyze risk data, securities companies use a variety of self-help analysis tools provided by SmartBI to get business personnel out of repetitive human work, turn to accurate risk analysis, and improve the efficiency of business transformation.
Business personnel can timely control the credit transaction business to ensure the correctness, timeliness and security of risk data. Combined with the multi-dimensional screening method, it can quickly view the related information such as the opening of accounts on the same day, the use of quota, and the composition and structure of the size of short selling securities, so that the data management is more controllable and the business becomes more flexible.
3. Scientific decision-making — construction of group-level management cockpit
Data operation of the securities industry is a continuous systematic project, especially the risk control department, which needs to establish a stable mechanism in decision-making, management, collaboration and execution to ensure the orderly and controllable transformation work. Using the risk control and management cockpit, managers can conduct real-time analysis on the whole network data from multiple dimensions, so that the risk status can be digitally and dynamically monitored, which is convenient for penetrating identification of hidden dangers, and can also help the management to formulate contingency strategies quickly.
To meet the related parameters of each department of business information report to display the needs of the securities company risk index system, according to the different scale, the line, the structure and so on were analyzed, and the theme of the cockpit, set up a risk management for business can, through data visualization for management can assign, after implementation of risk management to the success of the real-time risk management across, improve business efficiency, Improve the ability and level of risk management.
In the future, the development of data-driven business will certainly become a “trend”. In order to enhance their competitiveness, securities companies can only create greater value by using big data technology to realize the deep connection between finance and data, build “intelligent risk control” system and realize the data-oriented operation of risk management.