With the wave of financial technology sweeping the capital market, the intensified ecological competition in the securities industry, as well as the active guidance and support of regulatory policies, digital transformation has become a new strategic highland for the future development of securities companies. However, digital transformation requires the support of high-quality data and a powerful digital platform. As a highly information-based industry, the securities market is generating massive amounts of data information all the time. How to truly leverage the value of data assets and turn data "burden" into data "gold mine", is the most urgent need for securities companies in achieving their transformation journey.

Data asset management in the securities industry started late and has faced many difficulties

Based on the needs of internal refined management and the pressure of external regulatory changes, major securities companies have started the exploration of data asset management. However, compared to the rich technical reserves and practical accumulation of banks in the field of big data, the data asset management practice of domestic securities companies is still in the early stage, facing many difficulties and challenges like:

·       Countless securities business systems, scattered data, uneven data quality and inconsistent data standards, resulting in difficulties in data integration and data sharing.

·       With the regulatory agencies issuing a series of normative guidelines for data standards, data classification and grading, data quality, etc., a lot of work still relies on manual sorting and inventory, and securities companies are insufficiently staffed and cannot respond quickly to changes and requirements.

·       Enterprise-level data assets unable to be managed online and visualized, causing inconvenience for asset application and management.

Professional services: one-stop empowerment from consultation to implementation

As a financial technology leader who has been deeply involved in the big data business for many years, Sunline has precise insight into the market demand, and believes that data asset management is not a data management activity purely aimed at governance, but should be built around the digital transformation of enterprises. As the core, from the aspects of organization, system and platform, build a data asset management system that integrates data standards, data quality, metadata, data models, data security, and data value. Relying on the data asset management experience accumulated in the long-term actual combat, Sunline started from "knowledge", "management" and "application" of data assets to extract an integrated solution from consulting and planning to product construction and implementation.

·       Data asset management consulting: Based on the securities industry SDOM model, classification and grading guidelines and other regulatory standards and best practices combined with years of practical experience, Sunline has formed 9 mature fields covering data standard management, data quality management, metadata management, and master data management that help securities companies quickly build a data asset management system.

·       Data asset management platform construction: Focusing on the goal of "managing and application of data", visualization and intelligence, and adopting the design concept of microservices and loose-coupling, the platform provides users with intelligent inventory of data assets and the construction of data standards and specifications, one-stop governance of data quality, helping securities companies realize data assetization and asset service, and continuously maximizing the value of data assets.

Application value: effectively support business operation management

With mature solutions and professional implementation capabilities, Sunline has provided data asset management consulting and implementation services for more than 20 securities companies such as GF Securities, Guosen Securities, China Merchants Securities, and Galaxy Securities, covering nearly 20 domestic top 20 securities companies, complying with regulatory guidelines, industry norms, and customer needs in the field of data asset management by:

·       Forming a data asset management knowledge base based on rich implementation experience, and continuously upgrades according to industry requirements, regulatory norms, and business changes to help customers quickly build a data asset management system and avoid detours.

·       Continuously upgrading the platform's intelligent capabilities to greatly reduce the investment of securities companies and improve the level of asset management through functions such as automatic metadata collection, standard intelligent recommendation, as well as intelligent data classification and classification.

·       Embedding data asset management into the demand process to support online management such as demand analysis, model design, development, testing, change release, impact assessment, process approval, etc., achieving sustainable and normal operation of data assets.

·       Promoting the application of data assets and empower businesses through functions such as data asset maps, intelligent full-text retrieval of data assets, and data asset value assessment.

·       Continuously upgrading the master data management function to reduce the problem of inconsistency of master data across systems to improve the ability of enterprise data sharing.

Data asset management is a continuous and systematic process. In the future, based on the development needs and application scenarios of the securities industry, Sunline will continue to make efforts in deepening data management, control and data asset application, helping data elements integrate into the core value chain of enterprises, and effectively supporting the digital transformation of securities companies!