Which risk control model providers are more reliable?

Provide customers with the following functions:

1. Multi-source data collection: third-party data, Internet data, industry data, policy data, etc.;

2. Industry decision-making model construction: build industry-based data models through data preprocessing, risk control modeling and execution training; 3. Pre-review and access: shareholder information, enterprise operation information, legal person credit information, credit information, court information, etc. 4. In-process monitoring and management

Through the industry risk control decision-making model, people, events, and behaviors are optimized and risks are controlled; 5. Post-event follow-up feedback: automatic tracking of intervention and early warning information, process processing; 6. Open platform: self-service risk control model for multi-industry and multi-role users.

NETX Forex FCA regulated.

Boolean data, to tell the truth, Boolean data is reliable.

Founded in 2017, Boolean Data focuses on vertical industries, focusing on providing professional intelligent risk control solutions for financial institutions and e-commerce platforms through joint modeling and scenario personalization services. It has achieved very high accuracy and coverage in a single industry, and the scoring quality of the risk control model has been well received by cooperative customers.

The main services include four parts: model service, joint modeling, cloud platform, and risk control decision engine. At present, Boolean Data Service has nearly 10,000 customer platforms, and has gradually become a provider of intelligent risk control products with great influence in the industry.

There are many companies that have developed risk control system models, and Boolean data is one worth recommending.

Boolean Data is the first brand of Hangzhou Shouxin Network Technology, committed to intelligent risk control, with the industry's professional AI risk control engine technology, the integration of machine learning supervised and unsupervised algorithms into a fully supervised algorithm that fits the actual situation of the domestic market. Compared with peers, it has obvious product advantages:

All-round risk profile: Comprehensively portray customer risk portraits through the correlation between multi-dimensional data.

Refined customer stratification: Integrate multi-dimensional features, model classification, and customer stratification to improve the level of refined risk control management.

Customized requirements: Realize the custom combination of products to meet the different needs of various types of institutions for risk control with high flexibility.

The risk control management model has three types of data: enterprise information, financial data, and first-class data, which dynamically reflect the latest status of the rating object based on statistical models and expert methods, and regularly test the appropriateness of the calculation results of the model and revise the model.

Enterprise information: including industry, region, years of establishment, historical transactions, attributes of operators, etc.

**Data: The risk control management model includes the name and category of the goods sold, the details and summaries of the sales quantity and amount in the latest period (such as daily, weekly, monthly, quarterly, etc.), the details and summaries of the purchased quantity and amount in the latest period, the details and summaries of the inventory quantity and amount in the latest period, the analysis of commodity structure, and the relevant year-on-year and month-on-month comparisons.

In addition, the risk control management model can help the business to carry out accurate data docking and chain events, abnormal reminders of payment time, and can also set warning values for large-scale transactions. It fully demonstrates the repayment risk coefficient of the financier and lays a solid foundation for the better development of the enterprise in the future.

Risk control model is the abbreviation of risk control model.

It is commonly used in credit guarantee companies to control the risk of the business.

At present, the risk control model in China mainly includes: the risk control model developed by ICBC.

In the highly refined risk control model, an important part is to use advanced statistical econometric models to more accurately describe the correlation of fluctuations in multiple financial assets**. In real financial transactions, we will be dealing with hundreds or thousands of financial assets, so we need a theoretically flexible and realistic statistical model that can describe, estimate and simulate the correlation of a large number of risk factors at the same time. In scientific research, we are constantly exploring and trying to find a more flexible model on the basis of the existing model to accurately and efficiently describe the dependence between various high-dimensional financial risk factors.

Of course, the highly quantitative quantitative risk model must be able to be calculated relatively quickly in the actual application of the industry, so as to carry out real-time risk** and monitoring of various financial portfolios.

This highly quantitative risk control model will calculate the risk degree of various asset portfolios in real time for exchanges, clearing houses and major brokerage companies all the time, so as to always control the market risk of various financial transactions within a reasonable range, so that derivatives market transactions can operate stably, and reduce the crisis brought by huge fluctuations to the market to the greatest extent.

What is Risk Modeling? There are two types of models:

1. One-size-fits-all, the passage of greater than this threshold, and the rejection of less than this threshold.

2. Grading, indeterminate manual intervention.

One-size-fits-all model, first of all, one thing to declare, in my understanding, there should be no company that has a kind of, just rely on a model to completely determine the quality of the customer, give him a loan or not, if there is the existence of this company, please accept my knees, please accept me as an apprentice. After all, my company wouldn't dare to do that.

Generally, this one-size-fits-all model is a model that puts a lot of policy rules, anti-fraud rules, and various verification rules almost the last step, and the model gives the customer a score, and uses the score to divide a threshold, and the pass above the threshold (assuming that the higher the score, the higher the quality of the customer), and the rejection below the threshold.

At this time, it is also necessary to mention that risk control, the full name is risk control, risk control means to control risk, but it is not completely risk-free, so the division of the threshold, the central idea is: I can let bad customers enter the loss, can be used to use the income of good customers in addition to the labor, data, customer acquisition of various miscellaneous cost coverage, but also to obtain an accepted income under the premise that I go to draw this threshold. This means that the determination of the threshold is not higher than the threshold of the customer must be a good customer, if you are a good customer, then you 100 people come in, you will take the highest score, then the overdue rate must be low, but in this way your marketing department will definitely turn against you, Lao Tzu pull 100 customers, you will give one, what do you mean, me!

In order to avoid this kind of risk control and market struggle, you need to find a threshold that weighs the customer and the benefit.

Costs involved by customers: (The specific figure needs to be adjusted according to the company's data.) ）

Customer acquisition cost: The customer acquisition cost you put in the product channel, this is estimated to ask the marketing department, you can also estimate, this is not actuarial, not need to be refined to the real specific customer acquisition cost, probably enough, should your threshold will be adjusted.

Cost of funds: It is the money you lend, which belongs to that channel, and you need to pay the interest of the other party, which can be asked to the leader. Because the amount of each customer may be different, there is no need to count the loan amount of your customers, you can take an average loan amount and multiply it by the total number of loans, after all, your customers are all loans, and the model should be aimed at the customers who are applying.

There are multiple funding channels, you can take the average, or you want to be conservative, and you can take some of the average. ）

Labor cost: You have a threshold to determine whether it is good or bad, so this labor cost, tan90°.

Data cost: Each customer has to access some of your external data, and estimate the cost of external data for customer access. (You can also ask your leader).

If you can't get the above cost data, then you don't want to do this profit maximization work. I mean really, after all, I don't know if your company can tell you this information.