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Recently, the People's Bank of China announced the full text of the "Financial Technology Development Plan (2022-2025)" (hereinafter referred to as the "Plan"), reviewing the past financial technology development, while looking forward to the 2022-2025 financial technology development.
In terms of the application of regulatory technology, the Plan points out that in-depth regulatory technology applications, such as monetary policy, payment and settlement, anti-money laundering, credit investigation, and consumer protection, digital compliance tools are used to seamlessly embed transaction behavior monitoring, business data reporting, and risk event reporting to improve financial supervision efficiency and reduce compliance costs.
in bridging the digital divide, the Plan calls for strengthening financial accessibility services. Aiming at intelligent service methods, focusing on high-frequency financial scenarios in the daily life of the elderly, disabled, ethnic minorities, etc., deeply mining technical advantages such as artificial intelligence and big data, and optimizing interface interaction, content reading, operation prompts, voice assistance and other functions, Encourage the application of "care mode" and "elders mode", and establish a "fault-tolerant" product interaction mechanism, different from person to person, we will create aging and barrier-free mobile financial products and services such as large-character version, voice version, national language version and simplified version. Through experience learning, trial application, experience exchange, mutual assistance and other means to improve users' digital literacy, efforts will be made to bridge the digital divide caused by difficulties in the use of intelligent technology, so that the masses can better share the achievements of financial technology development.
In terms of data sharing, the Plan requires that data be shared in an orderly manner. In terms of technology, actively apply multi-party security computing, federal learning, differential privacy, alliance chain and other technologies, explore the establishment of a cross-subject data security sharing privacy computing platform, and standardize the development of data sharing applications under the premise of ensuring that the original data does not leave the domain to ensure Data interaction is safe, use compliance, and scope is controllable, so that data can be used and invisible, and data does not move. In terms of management, explore the establishment of diversified data sharing and ownership determination mechanisms, clarify the ownership relationship, use conditions, and sharing scope of data, and realize cross-institutional, cross-regional, and cross-regional through model calculations, fuzzy queries, and intelligent verification. The orderly sharing of industry data resources enhances the scale effect and positive externalities of financial data under the premise of ensuring the minimum necessary and dedicated purposes, and improves the efficiency of data element resource allocation.
At the same time, the Plan clearly requires data security protection. Strictly implement data security protection laws, regulations, standards and specifications, clarify the person in charge of data security and the management organization, and comprehensively use the methods of statement and publicity, user express, etc., to clarify the purpose of original data and derivative data collection, processing methods and scope of use, and ensure that users are fully informed, Standardize the use of data collection under the premise of clear authorization to avoid excessive collection, misuse, and overflow of data. Establish and improve long-term mechanisms and protective measures for data life-cycle security management, use technical means such as concealment query, de-labeling, and trusted execution environment to prevent data reverse tracking, privacy disclosure, data tampering and improper use, and protect the privacy of data subjects from infringement in accordance with laws and regulations. Establish a historical data security cleaning mechanism, use professional technology and tools to delete and destroy user data beyond the shelf life in a timely manner, and regularly carry out data recoverability verification to ensure that data cannot be restored. If it is really necessary to save as sample data, it should be approved by the user and de-identified, moved to the non-production database for storage, to ensure that the user's private information is not directly or indirectly identified, and effectively protect the user data security.
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