Data governance of delayed financial institutions

Author | Su Wenli

Understand economic column writers and serve Sunshine Insurance (TA has settled in the app mini program)

At the company's strategic seminar at the end of last year, the leaders in charge of IT pointed out that the problem of data islands has affected the process of digital transformation of the company and called on everyone to pay attention to solution. Because the focus of the meeting was not that, the opinion did not cause much response.

The leaders of my sector are keenly aware of the seriousness of the problem. It used to think that IT could do all of this, but now it is clear from the speech of IT's highest leadership. This is not something that IT can solve. In order to promote the company to effectively solve the problem, we arrange for us to study their opinions.

Data island problem is prominent

The company has vigorously promoted the digital transformation strategy in recent years. A series of business model innovations were carried out around the data. Some line departments have tasted the sweetness and stimulated greater enthusiasm. The depth and breadth of data applications in the company have improved significantly.

Everyone is gradually dissatisfied with only the existing data, actively obtaining more data in business activities, and trying to use the relevant data owned by other subsidiaries, sectors, lines and departments in the group. The operating system of existing supporting mechanisms does not well support this change requirement.

Life insurance subsidiaries are typical to promote customer experience and improvement projects by data analysis. The project intends to draw a full -process and full contact customer service journey through collecting customer behavior data, discover the breakpoints or stagnation status in them, and then improve the service process and resource allocation in a targeted, thereby improving the customer service experience Essence

The project team found that a large number of customer data is not within its own control scope, and it needs to be across departments, lines, sections and subsidiaries to coordinate acquisition. Driven by the total push of its separation, the data acquisition problem in the strip line has finally been solved to a certain extent. The acquisition of data outside the line is unsatisfactory.

Based on the data that has been obtained, many customers have found problems, and they have been praised by customers after improvement. In view of the breakthroughs in the project, the team has greatly improved the customer service experience in the future, and has more expectations, and strongly hopes that the company can fundamentally solve the problem of data through data.

Further investigation found that other sectors, lines and departments in the company's group also had similar demands. As a result, this situation is not the lack of cooperation in all parties, but that the existing mechanism system does not encourage data sharing, and there are even negative incentives to some extent.

On the one hand, many customer data is not recorded in the system. The reason is that the records and storage of storage data need to increase a lot of IT costs. When the departments that master the customer activities service scenarios do not need data, they are naturally unwilling to record and store more data.

On the other hand, even if some data are recorded, the department with data is unwilling to provide it easily for other departments. After all, the security issues of customer information are involved, and improper processing may bring a series of unknown consequences. Since the responsibility is great, it will naturally act as carefully as possible.

Third, the department with data has a certain degree of external information shielding and self -protection, and is unwilling to share data. Worried about being obtained by others, it is equivalent to obtaining evidence that it is unfavorable to yourself, for fear of exposing the shortcomings in his work.

Fourth many data diameter standards are different and quality is uneven. Most of the data that have been obtained now are by -products of various business application systems, but they are recorded for supporting the application functions. They did not consider other purposes, and naturally did not consider the quality demands of other users.

In the fifth existing management system process, there is no support for coordinated data collection and use, and no effective definition of the responsibility, power, and benefits of participating parties, and no corresponding incentive mechanism. In addition, professional departments such as risk compliance, information security, and IT development must fulfill the corresponding responsibilities, which also increases the difficulty of organizational coordination.

Most of the matters of data sharing are the one. Everyone had different task goals, and time, energy and resources were very limited. Facing the additional work, it will naturally arrange a lower treatment priority, and there will be a passive cope in the operation.

In the company's major tasks in the company, if you want to comprehensively obtain data, high -level leaders must be coordinated. It takes great energy, but the effect is not guaranteed. Only by completely changing the existing institutional mechanism and allowing everyone to obtain and use data under the overall chess can the data flow smoothly.

Make a fundamental change from the level of corporate governance

I believe that many companies, like us, have already proposed similar goals such as "opening the underlying data" or "eliminating data islands". It is to make data flow smoothly and effectively, and generate value in use, thereby turning a large amount of data resources into the company's assets.

Although many measures have been taken, the result is not very ideal. The reason is that it is not high enough to solve the problem. Because the data is stored in a computer system, many leaders will naturally think that this should be handed over to the IT department.

However, the IT department can really play this role. Its role is the data steward, not the owner of the data. It is more about technical support for data collection, storage, processing, and sending in the requirements of the business department.

Some companies designate their responsibilities to a professional department. Due to the limitations of its identity positioning, lack of sufficient influence, it is difficult to assume the responsibility of overall overall overall overall situation, and will also encounter the dilemma of a small horse car, and can only achieve a certain optimization effect locally. Enterprise is the owner of the data, and its senior leaders authorize the business departments that produce data to exercise their responsibilities on their own. Data opening must be formulated by the company's highest decision -making layer to formulate effective operating rules, allow all data agents to reach a consensus, and work together under a plate of chess.

This must be deployed at the corporate governance level, similar to financial governance and IT governance, and carry out corporate data governance. This is not the governance of data, but the governance of data assets, the coordination and specifications of all relevant parties of the data assets, and the top -level design of corporate data work.

The content includes but not limited to data resources assets, data confirmation and compliance, value creation and talent training. Data is just some electronic records, and it is not born with asset attributes. Only by allowing data resources to generate expected income can it make it a data asset.

Data confirmation is to determine the property rights of the data. If the data is not confirmed for the time being, then at least to do it, the behavior of the actual controller of the data is strictly controlled to achieve legal and compliance. It is the core driving force for data governance to work hard to make data value. Then pay attention to the construction and cultivation of the talent team.

Data governance emphasizes the in -depth intervention of the highest leadership in the enterprise. Starting from the organizational structure and responsibilities of the enterprise, clarify the responsibilities, powers, and benefits of each data related parties in the process of data collection and use. Inner goodwill.

The so -called data governance carried out by many companies is only quality management of the existing data itself. It is just on professional levels such as information technology and data applications. It is the fundamental solution to only find a way to find a way to solve the problem at the level of problems.

With the continuous advancement of the company's data governance and creating a good cultural atmosphere of data sharing, it can promote everyone to actively collect data under various scenarios to ensure the security and data security of data, quickly accumulate larger data assets Essence

During the use of data circulation, relevant parties actively provide support and promote more depth and breadth of data applications. All working links involving data can be compliant according to law. While bringing greater value to enterprises, participating parties can also achieve their own value.

In the "Guiding Opinions of the General Office of the Bank of China on Digital Transformation of the Banking Insurance Industry" issued by the China Banking Regulatory Commission in January 2022, it clearly put forward the requirements for improving the data governance system to various financial institutions. As early as 2018, the CBRC issued the "Guidelines for Data Governance of Banking Financial Institutions". Detailed specifications have been provided for data governance architecture, data management, data quality control, data value realization, and supervision and management.

Many financial institutions have actively put the company's data governance on the agenda and achieved certain results. However, in the past three years, many financial institutions have been punished for supervision for data quality problems, indicating that the data governance work of the current financial institutions has a lot of room for improvement.

Increase company data governance intensity

According to the guidance of the CBRC document, combined with the actual needs in the digital transformation process, all financial institutions should make determination to increase the company's data governance efforts, change the existing model of developing data management at the department level, and make overall planning from the top downwards. Planning and deployment.

Since data governance belongs to the category of corporate governance, entrepreneurs must be led by entrepreneurs. The senior leaders of the enterprise should be handsome to lead the process of data governance. In the enterprise, a relatively influential department can be clarified as a leading unit, and the main parties related to data are assisted by the major parties related to data to assist leaders to start the planning of data governance in the form of project teams.

In view of the fact that data governance has a certain professional threshold, and most companies lack corresponding reserves, they can consider the introduction of an external company to provide consulting services support, obtain professional methodological guidance and advanced experience in the industry. An important responsibility for external companies is to do a good job of passing, helping, and bringing.

The specific project work must be based on the enterprise itself. With the guidance of external companies, it must quickly build a corporate data governance system. Complete the transfer of relevant knowledge in practice to ensure that the company can continue to carry out data governance in the future.

The company's data governance must be combined with the actual situation of the enterprise. First investigate the status quo of data, master the existing data architecture, data standards, and implementation status, status and pain points of data quality, and already have data governance capabilities, etc., and understand the bottom of the family. Also understand the goals that you want to achieve with the help of data governance. Based on this, a practical company data governance roadmap is formed.

The wide range of data governance involves a large scope, which can cover the entire business and technology field of the enterprise, as well as the entire life cycle of the data. It is not realistic and unnecessary to realize a complete corporate data governance at a time. It is likely to consume a lot of corporate resources, but it cannot bring more benefits.

The best choice should be to adopt a step -by -step strategy, focus on the main problems in the current data application, and concentrate the firepower to make breakthroughs. After a local success, further expand the results. With the expansion of corporate data application scope, it has gradually extended to more fields.

Many financial institutions are considering starting from solving the quality problems of regulatory data. The task goal is very clear, very urgent and important, and the effect achieves is better measured. Although it involves a wide range of surfaces, the process of implementation is not complicated. It is easy to control. It is a good choice. Be sure to focus on the business direction during the data governance process. The cause of data problems is often not technology, but business. On the surface, the technical problems are essentially irregular in business management, or even lack of management.

Take the quality problem of reporting supervision data as an example. Many of them are because of the large number of data sources and the relevant responsibilities are unclear. As a result, the same data has different expressions in different information systems. Specifications or lacks and so on.

Carrying out company data governance will change the behavior and interest pattern of everyone's original habits. At the beginning, the willingness of the relevant parties will not be high. Therefore, we must do a good job of unified thinking in the early stage. Let everyone realize the significance of all this to the future of the company.

At the same time, professional teams must be arranged to provide necessary guidance and help, and even support for providing additional resource support. As long as it is firmly implemented for a while, everyone will find that all current inconveniences will become extremely convenient for long -term and overall. Gradually develop new habits, everything is incorporated into the right track.

Company data governance is a long and complicated job. Special departments and professionals should be arranged to continue to promote the work. In the process, special attention should be paid to forming a timely and effective feedback mechanism, measured the progress, discovered the problems, and continuously iterated to improve.

The highest leadership of an enterprise should pay attention to the continuous growth and effective use of data assets as the enterprise's other assets. The company's digital governance is the most effective work starting point. As long as you persist, the energy source will inject the vitality of digital transformation into the enterprise, helping the enterprise to establish a new competitive advantage in the digital age.

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