Recently, the first financial work conference pointed out that finance should provide high-quality services for economic and social development, and it is required to "do a good job in science and technology finance, green finance, inclusive finance, pension finance, and digital finance." "Among them, whether it is technology finance or digital finance, it must be based on credible, secure and circulating data. At the same time, the recent release of the National Data Bureau's "Data Elements" Three-Year Action Plan (2024-2026) (Draft for Comments) has further promoted the new format of data element value creation to become a new driving force for economic growth.
Nowadays, in the era of digital economy, the marginal role of traditional factors in driving economic growth is decreasing, and the role of data elements in economic growth is becoming increasingly prominent.
Hemingway said, "The iceberg moving in the sea is majestic and grandiose, because only one-eighth of it is exposed on the water." "The data assets that many enterprises can effectively use are actually only the "tip of the iceberg", far from the whole picture. In order to move from "business-driven" to "data-driven" to a higher level of "data-driven" in enterprise digital transformation, it is necessary to enable the reasonable operation of enterprise data assets and give full play to the value of data-driven business.
This is also the intention of CLP Jinxin to release the "Financial Data Asset Operation", hereinafter referred to as "Financial Data Asset Operation" and the "Yuanqi Data Asset Operation Platform": focusing on the construction and practice of the data asset operation system, giving constructive ideas on the strategy and path of data asset operation in the financial industry, and opening up the world under the "iceberg" of data assets.
Defining a data strategy is the first step to a data-driven business
The foundation of digitalization is data, and the digital transformation of enterprises so far can be regarded as a process of mining the value of data from shallow to deep.
From the information age of the last century to the current digital age, enterprises have accumulated a large amount of data after years of system construction, but most of them are data islands, which are separated from each other and difficult to connect data, not to mention the mining of data value. With the development of emerging technologies, data has become more diverse, and various types of data such as structured data, unstructured data, and machine data are constantly derived and converged, which also makes many enterprises lose control of data.
Enterprises need to establish an operational perspective to build data into the main line of business innovation and the link between cross-scenario collaboration of business, so that it can truly become a valuable enterprise "asset".
However, the process of moving towards data asset operation is difficult, and many financial enterprises have not yet formulated an enterprise-level data strategy, and are still facing the problem of insufficient integration of industry and data, as well as a lack of business operation thinking and technology-driven promotion model. As a result, the operation of data assets cannot form a closed-loop mechanism, and the value cannot be realized.
The first step in running a data asset is to have a clear data strategy. The value chain of data from generation to storage, management, analysis, and operation is very long, so data strategy is not only the work of the IT department, but also the values that need to be comprehensively established in the business process of the entire organization, which requires enterprises to build a consistent data cognition from the top down, from the decision-making level to the execution layer.
Data asset operation under platform-based thinking
As an important part of digital transformation, data can only be integrated, shared, and utilized through the operation of data assets, thereby promoting the digital transformation of enterprises. The operation of financial data assets is the core module of the enterprise data asset management system, and its goal is to realize the elementalization of data and give full play to the maximum value of data.
However, it is easier said than done, and to do a good job in the operation of data assets, it is actually necessary to have practical support. Through its own practice, CLP Jinxin has put forward the concept of ".Root down, bear fruit up"Core data asset operator**.
Previously, it was pointed out in the "Data Governance" released by CLP Jinxin that data governance lays the foundation for data asset management. Without a data governance system as a guarantee, data not only cannot be transformed into enterprise assets, but also can easily lead enterprises into the trap of "data swamp". In fact, this is the core of "down roots", before the operation of data assets, data governance must be the foundation in order to be down-to-earth. The essence of "upward results" is to be business-oriented, which requires data asset operations to always focus on the release of data value, because customer experience is the best "result".
Guided by the logic of "doing a good job in governance down and promoting value release upwards", and then verified through practice, this is the closed-loop process of data asset operation with "governance, inventory, use, activity, and evaluation" as the core summarized by CLP Jinxin.
(CLP Jinxin Data Asset Operator**).
In fact, it can be seen that this party is a typical platform thinking, using the platform to carry data producers and serve data consumers, so that data can circulate effectively, from data assetization to data valorization, and finally make data-driven business innovation a new engine for enterprise digital transformation.
Origin-based data asset operation platform
How to help financial enterprises move towards data asset operation
Since data asset operation is a product of platform thinking, then this platform should also be productized, and the data asset operation platform is such a product, which is based on the data asset operation of CLP Jinxin, and is gradually formed from bit by bit through the evidence of a large number of customer practices.
Origin-based data asset operation platform
In the field of financial data asset management and operation, CLP Jinxin has been deeply engaged for many years, with a deep understanding and practical experience of financial data assets, research and development of independent innovation consulting methods and product systems, which can provide users with complete data asset operation solutions including data strategic planning, asset operation system design, data asset platform construction, data asset inventory, asset on-site operation, etc.
At present, CLP Jinxin's big data team has provided data services for more than 200+ customers, including 6 large state-owned banks, 12 national joint-stock commercial banks, 2 policy banks, 100+ city commercial banks, and 90+ other financial institutions, covering the construction of customer big data platforms or data application systems.
As the technical support of the data asset operation system, the data asset operation platform can support the diversification of asset services, the visualization of operation analysis, and the empowerment of AI technology, helping to solve problems such as the inability to coordinate the management of business data, the inability to track data application scenarios, and the "incomprehension" and "inevitability" of data usage.
First of all, why should asset services be diversified?This is because enterprises need to face data consumers at different levels and scenarios, and need to rely on the diversification of asset services to determine the width of asset release.
Second, why should operational analytics be visualized?Because enterprises need to show the details of data asset operation through business production links, data production links, and analysis production links, visualization will make operations and decision-making more efficient.
The technology empowers AI, which is to improve the efficiency of data operations through AI assistance. Because it is difficult to find, use, and manage data, the purpose of the data asset operation platform is to make the operation of data assets simpler and more efficient through these methods.
As the digital transformation of enterprises deepens, the scale of data will increase, and the difficulty of data asset operation will continue to increase, but once this road is completed, it is like gaining insight into the whole picture of the data "iceberg", which can release the kinetic energy of data elementalization from the perspective of data from a global perspective, give full play to the potential value of data, and drive the long-term and sustainable growth of the enterprise's own business.