70results about How to "Reduce credit risk" patented technology

The invention discloses a method for constructing a financial asset trading system based on an alliance chain. With an alliance chain as a technical support, a novel financial asset digital unique certificate is provided based on the existing laws and regulations. The system uses a distributed technology architecture. All participants jointly maintain the ledger of financial asset trading. It is ensured that the trading of financial assets is open, transparent, real and credible. The credit risk of trading is reduced. The cross-platform and cross-region flow of financial assets is promoted. Tedious manual account checking work between platforms is omitted. In addition, the block chain technology is applied to the field of financial asset trading for the first time. A unified and standardized financial asset trading platform is established. Digital management of financial assets is realized. The credit risk of trading can be prevented effectively. The efficiency of trading and supervising is improved. The trading cost is reduced.

The invention discloses an anti-fraud modeling modeling method and an anti-fraud monitoring method based on machine learning. The anti-fraud model modeling method based on machine learning comprises the following steps: extracting sample data required for modeling from a database, and carrying out labeling processing on each sample data; matching the association information of each sample data from the database, using the results of labeling processing to establish the multi-dimensional credit data based on the user, and processing and dividing the credit data into training set data and test set data; training and adjusting the parameters of the anti-fraud model by using the training set data; using the test set data to test the anti-fraud model, obtaining the fraud probability value thatthe test set data is fraudulent users. The obtained fraud probability value is compared with the corresponding actual sample situation, and the stability of the anti-fraud model is judged according tothe comparison result, and the anti-fraud statistical threshold value is established. The method can effectively reduce the risk of fraud through label processing and supervised machine learning.

An automated system and method of purchasing prepaid and other services against a deposit or a credit threshold. A server provisions requests for electronic PINs. This provisioning server maintains a record for each retail merchant, distributor, or third party processor. Depending on their credit worthiness, the control server either establishes a credit threshold retail merchant, distributor or third party processor or requires a cash deposit. A retail merchant or distributor or a third party processor may obtain an electronic PIN from the provisioning server in real-time or in batches against their credit threshold or deposit.

The invention relates to an unstructured data default probability prediction method based on deep learning. The method comprises the steps as follows: unstructured data, including text data and time series data, of credit subjects are integrated and cleaned; the unstructured data are converted into a data format recognizable by a deep learning model; data features are extracted as sample data on the basis of a deep learning model frame; as for the extracted sample data, a credit risk model is constructed by use of a complex machine learning classification algorithm-integrated tree model, and default probability prediction is output. According to the method, the unstructured data such as text and time sequence data are mined, potential risk behavior modes of the credit subjects are caught on the basis of deep learning and a big data technology, high dimensional data credit risk modeling is performed accordingly, automatic, comprehensive and procedural quantitative credit risk analysis for the credit subjects is realized, the finance risk control capacity is improved, and the credit risk is reduced.

The invention belongs to the technical field of financial information data management, and discloses a credit rating default probability measure and risk early warning method. The method comprises thefollowing steps: mining valid data and measuring and calculating default probability; constructing a default loss rate prediction model, and checking the consistency of rating results; and constructing a binary response risk early warning model, and realizing an early warning strategy by means of a data mining technology. Through research and application of a credit rating mathematical model, a set of credit rating system which can be verified by using data and is high in feasibility is finally formed by using a data mining technology, and effective practical experience is obtained. Meanwhile, the research result can cooperate with the financial industry and can also cooperate with credit enterprises to provide credit products and technical services for the enterprises and provide data reference for transaction decisions of market subjects, so that contribution is made to credit demands and credit industry development.

The invention discloses a credit monitoring and scoring method and system based on a behavior model. The method comprises the following steps: obtaining the original data of an account in an observation period; carrying out feature extraction on the original data of the account to obtain a prediction variable; according to the prediction variables, using the machine learning algorithm for modeling, and obtaining the prediction model of the response variables and the prediction variables; predicting an account with repayment performance according to the predicting model to obtain a default probability in the predicting period of the account; calculating the behavior score of the account according to the default probability of the account during the prediction period. The invention can increase the data changing speed, improve the applicability and generalization, and carry out accurate behavior scoring on the account.

The invention relates to the field of Internet finance payment, and particularly discloses a payment big data analysis system based on Internet finance and an analysis method thereof, and the method comprises the steps: carrying out the semantic feature information extraction of the description of a user portrait and a to-be-paid service through a context-based semantic understanding model; and processing the obtained feature matrix by using the same convolutional neural network model, so that the extracted associated features have correlation as much as possible relative to the user tag features and the service semantic features in a high-dimensional feature space. And furthermore, the parameters of the convolutional neural network are updated by using a gradient transfer method, so that the classification accuracy is improved. In this way, more appropriate matching can be performed between the user and the to-be-paid service, and then the credit risk of payment of the Internet financial platform is effectively reduced.

The invention discloses a credit anti-fraud method, which comprises the following steps: when a credit core body call is detected, obtaining the risk level of the current core body customer, and obtaining the voice data of the customer collected in the process of the credit core body call; Determining a target anti-fraud strategy according to the risk level, wherein the target anti-fraud strategyis one or more of voiceprint anti-fraud strategy, voice anti-fraud strategy, light voice anti-fraud strategy, background voice anti-fraud strategy and voice emotion anti-fraud strategy; According to the customer voice data and the target anti-fraud strategy, performing an anti-fraud identification operation to obtain an anti-fraud identification result of the current core customer. The invention also discloses a credit anti-fraud system, a device and a computer-readable storage medium. The invention can improve the identification rate and coverage rate of fraud and reduce the credit risk.

The invention discloses a credit asset support pass transaction method and system based on a block chain, wherein the method comprises the steps of classifying and packaging the cash flow assets of anappointed account into a credit asset support pass, and managing through an intelligent contract ; packaging the credit asset support pass into an investment combination, and managing the investmentcombination by adopting the intelligent contract; and writing a transaction contract of the investment combination in the intelligent contract, and enabling a buyer of the investment portfolio to obtain the earnings according to the intelligent contract. The invention provides a credit asset support pass transaction method and system based on the block chain. In combination with the block chain technology, the credit asset supporting pass transaction using the cash flow assets as security guards and the hosting, insurance and supervision of the transaction process are realized, the credit riskis reduced, and the security performance of the credit investment product transaction is improved.

The invention relates to a multilevel relation management method and a platform for credit money allocation. The method comprises steps: through analyzing the credit value of an enterprise which is about to access the platform, the enterprise is marked as a core enterprise, and according to a protocol channel, an upper-lower enterprise relation between the core enterprise and a first invited enterprise is built; an upper-lower enterprise relation between the first invited enterprise and a second invited enterprise is built; the total credit money amount value is pre-allocated to the core enterprise, and allocation of the credit money amount value is carried out on other enterprises which access the platform according to the protocol channel. Through building the upper-lower enterprise relation, the allocation of the credit money amount value between upper and lower levels of enterprises is managed, the risk control ability is improved, the credit risks are reduced, the supervision strength is enhanced, the credit money amount allocation ability is further improved, and interests and needs of the enterprise are met.

The invention provides a supply chain management system based on a cloud platform, and aims at overcoming disadvantages in the prior art. The system comprises a service end and clients. The service end is loaded in the cloud platform, the cloud platform receives data of the client, the data is analyzed and processed, and corresponding feedback information is back fed to the clients. The service end comprises a waybill matching module, a financial management module, a logistics monitoring module, a vehicle condition monitoring and early warning module, a road information monitoring module and adatabase module. The clients include a vehicle mounted client, a shipping party client, a carrier client, a financial client and a consumption client. The system can update transport vehicle information in logistics of a supply chain timely, positions and progress of a transport vehicle can be monitored in the whole course, the consignment fund is closed in a closed loop way, bills and documentsare obtained timely, the logistics cost is reduced greatly, and the logistics efficiency is improved.

The invention provides an Internet of things movable property supervision method and system. The method comprises the following steps: after a target warehouse position is at a supervision state, generating a target warehouse receipt corresponding to target goods in the target warehouse position; obtaining in real time physical attribute information of the target goods corresponding to the target warehouse receipt in the target warehouse position and/or state information of goods transport tools; based on the physical attribute information of the target goods and/or the state information of the goods transport tools, determining whether abnormal operation happens in the target warehouse position; and if yes, sending alarm information to warehouse management personnel and/or pledgees associated with the target warehouse receipt. According to the invention, the target warehouse receipt is endowed with real-time and real target goods information, the pledgees are notified when target goods risks occur, such a supervision mode changes a conventional supervision mode featuring too much manual intervention and low efficiency in the prior art, the problem of warehouse receipt repetition caused by too much manual intervention is avoided, and the credit risks of banks are greatly reduced.

The invention provides an intelligent credit and information authentication system and method, and the system comprises a video recording module which is used for obtaining image collection data collected by a user at a remote terminal through an intelligent terminal used by the user; The image recognition and analysis module is used for forming picture image data after obtaining the video image data, carrying out image recognition and analysis according to an image analysis algorithm, and carrying out text data verification through a text analysis algorithm after image verification is passed;The voice guiding module is used for guiding the user to operate a corresponding recognition and authentication process through voice, reminding the user by using the synthesized voice and entering an authorization page according to a safety recognition and authentication condition; The anti-fraud module is used for identifying whether the user identity information is user identity information ornot; And when the user uses other people screenshot data or the image data subjected to image modification for identity authentication, the image recognition and analysis module judges whether the user is a fraudulent behavior or not, and transmits the fraudulent behavior to the remote terminal to record the information authentication operation.

The embodiment of the invention provides a service processing method, a model training method, equipment and a storage medium. In some exemplary embodiments of the present application, a server devicepre-trains a credit risk prediction model, a computing device collects a face image of a target user, and extracts face features of the target user from the face image of the target user based on a face recognition technology; inputting the face features of the target user into a pre-trained credit risk prediction model to obtain a credit risk value of the target user; and performing service processing on the target user according to the credit risk value of the target user to reduce the service risk.

The invention discloses a credit customer qualification classification method based on WOE conversion through machine learning. A system comprises a data preparation and preprocessing module, a modeltraining and evaluating module, a model deployment module, an inlet data processing module and a client qualification division module. The data preparation and preprocessing module is used for calculating original data I from the application data, the credit investigation data and the call record, calculating original data II through the customer category and the repayment data, and carrying out data preprocessing on the original data I and the original data II. The invention relates to the technical field of qualification classification. The credit customer qualification classification methodbased on WOE conversion through machine learning provides the system for realizing customer classification with different qualifications based on the machine learning method, the workload of manual auditing can be reduced, the approval efficiency is improved, learning is performed in time according to newly added customer information, self-adaption to customer qualification change is realized, the manual auditing efficiency can be improved to a greater extent, and the labor cost is reduced.

The invention provides a blockchain-based credit data processing method and device, a computer and a medium, and the method comprises the steps: obtaining a business information data packet of a first party, and uploading the business information data packet to a blockchain network; generating contract information in response to the signing information of the first party and the second party, and uploading the contract information to the block chain network; obtaining a financing request initiated by a first party; and transferring the financing fund to an account corresponding to the financing request based on the second confirmation information. The business information data packet of the first party is uploaded to the block chain network, the privacy information of the user is protected by using the encryption technology of the block chain, and the contract information signed by the first party and the second party is uploaded to the block chain network, so that the security and credibility of contract information storage are improved, and a decentralized storage mode of the block chain is adopted, so that the business information data packet and the contract information can be stored more quickly, and tampering is effectively avoided.

The invention relates to a system and a method for insurance investment, which are applied to the insurance field of financial e-commerce. The invention aims to provide a new capital operation mode of investment type insurance, so that a consumer can freely select credit expansion or investment reward improvement or zero-risk saving, and the insurance industry can be free from interest risks. The system for insurance investment is taken as the a main part of operation, so an insurance company can leap out of the frame of making capital operation reward but taking interest risks and turns to eliminate the interest risks by collecting commission charge under the operation of a capital bidding mechanism; and an insurant can expand credit in the course of insurance to improve the investment income and strengthen the insurance guarantee.