In the era of big data, how to improve personal credit and personal integrity

There are two ways to improve your online credit.

1. Don't apply for online loans too often, so as not to cause your own online black index score to be low, thus becoming an online loan blacklist.

Generally, the number of online loan applications should not exceed 3 times per month, and the total number of online loan application records in three months should not exceed 7 times.

2. There is borrowing and repaying, and it is not difficult to borrow again.

As long as the user has overdue behavior, no matter what online loan platform will upload the overdue information to the online loan database as soon as possible, it will also affect the user's online black index score.

The score of the Internet Black Index is 0-100 points, and the higher the score, the better the credit. If the user's online blacklist score is less than 40 points, it belongs to the online loan blacklist.

Therefore, it is recommended to check your own online loan data report in time to prevent blind application from becoming an online loan blacklist.

You only need to open WeChat and search: know and check. Click to query, enter the information to query their own Baihang credit data, the data comes from more than 2,000 online loan platforms and UnionPay centers across the country, users can query their own big data and credit situation, can obtain various indicators, query their own personal credit situation, online black index score, blacklist situation, online loan application records, application platform type, whether it is overdue, overdue amount, credit card and online loan credit estimate and other important data information.

Compared with the personal credit report of the central bank, the atmosphere of personal credit records is more extensive, and the institutions issued are more diverse, such as knowing and checking, sesame credit scores, etc., all of which are part of personal credit records, and on the whole, they are more similar to the big data credit information on the Internet, which is a useful supplement to the traditional personal credit report.

At present, the state is building an all-round "credit network" without dead ends, connecting the society and sharing information, whether it is credit reports or personal credit records, which are important parts. Protect your credit, for everyone, credit is the greatest asset and wealth.

Now the easiest way to check credit, you can print a credit report, or to test personal big data credit, the former can go to the credit information center of the People's Bank of China to print, the latter, go to WeChat: letter friends, detect the credit status of big data. Including the individual's overdue status, blacklist situation, credit score, etc.

Too many inquiries will affect personal credit, and inquiries must choose a larger and more reliable platform.

In the era of big data, every piece of data that can be incorporated into the credit database may affect the evaluation of credit records, credit records are not a separate event, but a comprehensive analysis, and different credit data account for different weights. So everything that can have a transaction record should be paid attention to. In fact, you don't have to pay special attention to it, as long as you are a faithful person, you will naturally have a good credit history.

In the current era of big data, every time we make credit behaviors such as loans, credit card use or online loans, credit records will be generated, and the central bank will collect and sort out and issue records of these credit information, which is what we often call personal credit.

Good personal credit is the passport to apply for online loan products, on the contrary, if the borrower's online loan credit is too expensive or too dark, it will naturally be frustrated everywhere.

If you want to improve your personal qualifications, you can try to get a big data report on your online loan on WeChat: "Early Know Data" and other data query platforms to analyze your credit situation.

The central bank credit report needs to be brought to the local central bank outlets for self-service inquiry. The central bank's credit report will record the user's lending platform, loan amount, loan term, negative records and other data content in the past 5 years.

Internet black, generally people who do not repay on time, or users with bad behavior, are easy to be included in the network black, to judge whether they are network black, on WeChat: four happy data, you can view. You can also see your credit score, contact blacklist, etc.

If there are overdue records on the Internet or loan records on multiple platforms, then all kinds of records will be recorded by big data risk control, and then the online loan platform will be frequently rejected, and even Huabei borrowing will be closed.

The umbrella is dressed in a wild goose, and the goose is full of sorrow, and the bee fence is silent, and the claws are open-minded.

One is the disclosure of public information, including the public availability of information and the accuracy and availability of corporate financial information; The second is the protection of personal privacy, which is more prominent in the big data credit reporting industry. In terms of privacy protection, in the traditional model, the borrower surrenders some personal privacy, mainly the information of borrowing and repaying the money, in exchange for the opportunity of fair credit transactions, forming a basically equal transaction model in the long-term process. However, in the credit investigation mode of big data, it is easy to break the equal exchange model between the transfer of privacy and the acquisition of credit.

In the process of data use, special attention is paid to the principle of transparency and the protection of individual rights: who is collecting and selling the use of data, why is it doing so, how long the data is kept, and with whom the data will be shared; Individuals' right to use information, the right to know about the information processing process and the right to be forgotten are the core connotations of individual rights and interests under big data. It is worth noting that due to the higher dependence of big data credit on the Internet and technology, the information security risks faced are more severe, once the credit information is illegally accessed, intercepted and tampered with, the information system will be irreversibly destructive, which will pose a major threat to personal privacy and the protection of customer rights and interests.

Not only that, it is also necessary to be vigilant against possible violations of laws and regulations in big data credit, such as some online social platforms or e-commerce platforms collect and use user data without the user's knowledge or provide it to third-party credit reporting agencies. Big data credit bureaus may have collected or used users' sensitive data intentionally or unintentionally. Although Tencent Credit and Sesame Credit have a large amount of user behavior data, these data have little to do with personal lending behavior, so the models they establish are not necessarily accurate and difficult to be cited by mainstream financial institutions.

Therefore, credit reporting establishments must have strict and complete systems and norms in the collection, management, use, and relief of information, and strictly comply with them. At the same time, it is necessary to clarify the dominant position of individuals in the open use of their information. This requires both the legislative department and the relevant functional management departments to introduce and improve relevant laws, regulations, and rules and regulations as soon as possible, so as to find a balance between the open use of information and the right to information privacy.

There should be clearly defined boundaries as to what information may be collected, what information may be publicly released, and what credit information may be provided to relevant parties.

If the individual's big data credit score is high, it means that the person's credit is not good, and the loan application is easy to be rejected. Then you have to look to see if there is something wrong with your credit. Look at Sen Repentance to see if it is overdue, or whether it has been blacklisted, etc.

Generally, there are two ways to understand personal credit, the first is to test through the People's Bank of China Credit Information Center. Second, it is big data credit detection, on WeChat: Xinyouge, you can check your credit status.

Remember to check your credit must choose a big platform, otherwise the content of the inquiry may be easy to be fake.

Online loan big data is a third-party credit inquiry system for lending institutions, which uses the technical means of big data to integrate the loan records of various online lending platforms.

Many platforms will use online loan big data as a reference basis when reviewing, and if there are stains on online loan big data, such as overdue or frequent loan application records, then the loan application will be easily rejected.

You can learn about your current credit situation in WeChat "Raindance Quick Check", get rid of bad loan application habits, and cover the dishonesty with new good payment records, so that when you encounter an economic crisis again, you will not have no way to find a way out, and you will hit a wall again and again.

The online loan big data system is a professional risk control system, which connects many unrelated online lending institutions, changing the situation of isolation of online lending platforms.

The database cooperates with more than 2,000 online lending platforms, and the query data is very accurate and comprehensive.

After becoming blacklisted, the loan application can easily be rejected and needs to be dealt with in a timely manner.

The most obvious impact of big data hacking is that the loan application is easy to be rejected, and even if the application is made, the amount is not high.

Weirs defend orange rolls, twist astringent households, and are wide, dramatic, stubborn, vertical, and unscrupulous.

First, based on legislation, optimize the institutional mechanisms for the establishment of the creditworthiness system. Adopt legislation to safeguard the legitimacy of credit data**; Increase the level of the establishment of the creditworthiness system by improving the collection and management of credit data, as well as systems for creditworthiness oversight, and rewards and punishments.

The second is to interconnect, so that integrity data can be connected and shared together. Uniformly regulate the establishment of the city's creditworthiness data platform, through giving play to the pivotal function of the credit information exchange and sharing platform, breaking down the barriers between legal persons and natural person information, releasing big data functions, increasing credit information inquiries, credit product transaction matching, and so forth, to create a version of the city's credit data platform, truly eliminating "information islands", and promoting the open sharing of creditworthiness data.

The third is to put the market first and realize the value-added development of energy efficiency of information and data. Support the development of socialized credit reporting establishments through methods such as credit authorization, develop data transactions and credit data assessments, and provide individuals and enterprises with diversified credit services and value-added services.

Fourth, we should focus on diversity and raise the level of social creditworthiness in a wider range of fields. Accelerate the establishment of the credit system with the support of big data, promote the widespread use of credit data in many fields such as financial services, social governance, administrative oversight, and people's livelihood services, and use administrative creditworthiness and economic creditworthiness as a breakthrough point to lead the construction of the city's creditworthiness system to a new level.

Fifth, the environment is the first priority, forming an overall joint force to promote the construction of the integrity system. Through strengthening creditworthiness education, creating a social atmosphere, and strengthening the coordination and cooperation of all ** departments and public institutions, ensure that the city's efforts to establish a creditworthiness system are solidly and effectively advanced.

It is necessary to establish a comprehensive record of market creditworthiness.