15results about How to "Improve risk control ability" patented technology

The invention provides an emotion index construction method and device, computer equipment and a storage medium. The method comprises the steps of obtaining multiple pieces of first comment information in a preset duration range and label information corresponding to each piece of first comment information; the label information comprises a positive label, a neutral label and a negative label; inputting the first comment information into a word embedding layer of a to-be-trained text classification model, and outputting a word vector matrix; inputting the word vector matrix into a convolutional layer, and outputting a first feature vector; inputting each first feature vector into a full connection layer, and outputting an emotion prediction result corresponding to the first comment information; completing the construction of a text classification model according to the emotion prediction result and the label information; and obtaining to-be-constructed second comment information, inputting multiple pieces of second comment information into the constructed text classification model, outputting an emotion classification result, and completing construction of emotion indexes corresponding to the multiple pieces of second comment information according to the emotion classification result.

The invention relates to a risk assessment method and device, computer equipment, a readable storage medium and a program product. The method comprises the following steps: acquiring a risk data set of the power industry in a preset area range; the risk data set at least comprises power accident data and operator data; performing feature extraction processing on the risk data set by using a data mining algorithm to obtain risk features; inputting the risk features into a pre-trained risk prediction model to obtain a risk prediction result; the risk detection result is used for evaluating the risk of the power industry in the preset area range. The method can improve the risk assessment accuracy of the power industry.

The application relates to the technical field of artificial intelligence, and discloses a data processing method, device, equipment and storage medium to improve blacklist processing capability. The method part comprises the following steps: receiving a loan approval request sent by a target business system, the loan approval request carrying loan approval data, the loan approval data comprising a system type of the target business system and attribute information of an applicant; calling a blacklist interface corresponding to the system type to obtain a system blacklist; judging whether the applicant is a user in the system blacklist according to the attribute information of the applicant; when the applicant is not a user in the system blacklist, a platform blacklist of an automatic approval platform is called; judging whether the applicant is a user in the platform blacklist according to the attribute information of the applicant; when the applicant is a user in the platform blacklist, a loan service corresponding to the loan approval request is rejected, and rejection result information is generated and fed back to the target business system.

The invention discloses a multi-mortgage guarantee clearing ability assessment and risk disposal method and device, electronic equipment and a storage medium, and relates to the field of financial risk assessment. According to the technical scheme, the method comprises the following steps of: evaluating the clearing capability, obtaining a mortgage guarantee object type, and determining a mortgage guarantee object clearing capability value; performing settlement risk assessment, and obtaining a comprehensive settlement capability coefficient of the assessment object after loan default; carrying out clearing risk early warning, and carrying out risk prompting to a lending institution according to the comprehensive clearing capability coefficient of the evaluation object; and carrying out clearing risk disposal, calculating an amount of adding or replacing the mortgage guarantee according to the comprehensive clearing capability coefficient of the evaluation object and a preset lowest comprehensive clearing capability coefficient, and displaying a mortgage guarantee supplementing scheme to a lending institution. The problem of low stock loan risk assessment and disposal efficiency in the prior art is solved.

The invention discloses an energy storage power station collaborative planning method and system based on uncertainty propagation analysis. In order to solve the problems that an existing energy storage planning method is indefinite in physical mechanism and insufficient in interpretability, the planning method comprises the steps that operation data of a power system are obtained, and an analysis alternating current probabilistic power flow model used for establishing an analysis relation between system voltage statistical characteristics and line power statistical characteristics is constructed based on the operation data; constructing a propagation matrix representing the uncertainty propagation characteristics of the system based on the analysis of the AC probabilistic power flow model; performing spectral analysis on the propagation matrix to identify one or more dominant propagation modes which play a dominant role in the uncertainty of the system; and based on the one or more dominant propagation modes, determining a planning scheme of at least one type of energy storage power station, the category of the planning scheme including the access position capacity of the energy storage power station. According to the method, energy storage configuration is guided by using an uncertainty physical propagation mechanism, and the risk control effect, the calculation efficiency and the engineering interpretability of a planning scheme are remarkably improved.

A computer-based financial data distributed online management system relates to the technical field of distributed data management and comprises a monitoring center which is in communication connection with a financial data management platform, a feature clustering module, a data detection module and a data analysis module. Collecting financial data uploaded by the equipment terminal; obtaining an expenditure feature set of each expenditure type of financial data stored in each block chain node and a block chain network of a plurality of clustering feature points; carrying out distributed joint potential anomaly detection operation on the financial data uploaded by the equipment terminal, and obtaining a distributed joint potential anomaly detection operation result of each block chain node; performing real-time data detection operation on the financial data uploaded by the equipment terminal according to the estimated financial data of the block chain node; according to the cost-benefit ratio of each expenditure type, the preferential reduction object is obtained, and the efficiency and safety of financial management are remarkably improved.

The present application relates to the field of credit risk control, and in particular to a method, device and storage medium for cost optimization and model construction. Using a training set and an out-of-time sample set, a base model is built through traditional logistic regression or a tree model; using the base model and a preset lift value, samples of different score segments are selected for superposition training to obtain a model set and a first processing result; using the first processing result, the model set is mapped to a unified scale according to the overdue rate to obtain a trained base model. It can be understood that the technical solution provided by the present invention utilizes the uniqueness of the data source and improves the accuracy of the model in a targeted manner according to the needs of the business scenario, so that the prediction results are more accurate, which can help financial institutions to reduce procurement budgets while improving the risk control effect of the model, thereby achieving the effect of reducing costs and improving efficiency.

The invention is suitable for the technical field of Internet, and provides a bond management report automatic generation system and method. In the embodiment of the invention, the system collects the bond initial data from the bond target data source, preprocesses the bond initial data, generates the bond target data matched with the data analysis model, and analyzes the bond target data through the pre-trained data analysis model, thereby automatically obtaining the bond research report. And after the bond research report is audited and passes, the bond research report is published and shared. According to the system, the bond report is automatically generated, the information processing accuracy and efficiency are improved, and the quality of the enterprise bond report is improved.

The invention discloses a financial derivative pricing method and device, electronic equipment and a storage medium. The method obtains a market data stream; performing first quantum preprocessing based on a plurality of subject asset price paths in the market data stream, and iteratively calculating an expected income price of the target derivative based on a first quantum preprocessing result by using a quantum amplitude estimation algorithm; performing second quantum preprocessing based on the risk factor of the investment portfolio in the market data stream, and iteratively calculating a risk open expected value of the target derivative based on a second quantum preprocessing result by using a quantum approximate optimization algorithm; and target derivative pricing is realized under the condition that the expected income price is matched with the risk opening expected value. According to the technical scheme, the risk control effect of financial derivative pricing is improved.

The application provides a credit business risk control decision method, device, equipment and medium based on multi-source data fusion, which comprises the following steps: acquiring multi-source data related to the subject identifier of a credit subject; performing entity analysis and alignment on the multi-source data based on the semantic features of each entity in the multi-source data, and constructing an initial knowledge graph; performing fusion and conflict resolution on the multi-source data through a space-time decay fusion model based on the confidence score of each data source in the initial knowledge graph and the corresponding time decay weight, performing entity screening on the initial knowledge graph based on the fusion result, and obtaining an optimized knowledge graph; for each entity node associated with a heterogeneous data source, calling a scoring model adapted to the data characteristics thereof, and generating a comprehensive credit score through a model integration mechanism; and determining a risk control decision for the credit subject based on the comprehensive credit score. The method, device, equipment and medium provided by the application realize accurate and efficient risk control decision, and significantly improve the risk identification accuracy.

The invention discloses a resource auditing evaluation method and device, electronic equipment and a storage medium. The method comprises the following steps: acquiring auditing data generated by auditing resources by a user; based on the data of each dimension in the audit data, respectively obtaining the management score of the user in the corresponding dimension; and obtaining an evaluation result for representing the resource audit risk according to the management score of each dimension. The auditing data generated by auditing the held cloud resource by the user is obtained, and the auditing data comprises records of auditing the resource in various aspects by the user, so that the management scores of the user in the corresponding dimensions can be respectively obtained based on data for describing different dimensions in the auditing data; according to the method and the device, the resource auditing capability evaluation of the user in each dimension is realized, so that the resource auditing risk is automatically evaluated by utilizing the management score of each dimension, the cloud use risk of the user in the auditing perspective is measured, the user can conveniently and effectively manage resources in a targeted manner, and the cloud use risk control capability of the user is improved.

The invention discloses a goods value risk control method and system based on imported customs declaration price data, and relates to the technical field of goods value risk control. The goods value risk control method comprises the steps of obtaining existing data; historical customs declaration price data, cargo data and historical conversion data of imported cargos are extracted from a customs declaration system, and the historical customs declaration price data and the cargo data are represented as heterogeneous data. According to the method, the simulation database is established, the change possibility of the actual price associated data is calculated based on the calculation tool, when the actual price associated data is changed, the corresponding simulation data is directly called from the simulation database based on the changed data, and the original goods value evaluation data is covered by the simulation data; according to the method, a large number of cargos are directly covered, the cargo evaluation data can be quickly and timely updated according to the dynamic information, the condition of underestimated or overestimated cargo value during customs declaration is avoided, and the risk value calculation accuracy is further ensured.

The invention relates to a visual risk control method and device based on non-invasive detection of respiratory signals. The method comprises the steps of collecting image data of an upper body area of a user in a remote authentication process of the user; capturing a breathing signal of the user from the image data; constructing a breathing curve of the user based on the breathing signal; extracting respiration characteristics of the user from the respiration curve; the breathing characteristics comprise at least one of breathing frequency and breathing amplitude; detecting whether the user has an abnormal state or not according to the breathing frequency and / or the breathing amplitude; and if the user has the abnormal state, triggering a verification measure for the user. According to the scheme provided by the invention, the abnormal state of the user can be effectively detected, the detection precision and robustness are improved, and the risk control capability is enhanced.

The invention relates to the technical field of machine learning and finance, and discloses a credit loan bad debt analysis method and device based on LSTM, equipment and a medium, and the method comprises the steps: obtaining the historical loan data of a loan institution, and extracting the data features of the historical loan data; generating feature vectors according to the data features, and generating data combination vectors through combination of the feature vectors and loan periods corresponding to the historical loan data; adjusting and optimizing target parameters of the LSTM model according to the data combination vector to obtain a target LSTM model; acquiring test data, and performing bad debt probability analysis on the test data by using the target LSTM model to obtain a loan bad debt probability; and obtaining a loaning risk value, and carrying out analysis operation according to the loaning risk value and the bad debt probability to obtain the total loaning bad debt amount. And the future bad debt risk is accurately estimated and corresponding risk control measures are taken, so that the occurrence of bad loans can be reduced.

The present invention discloses a method, device and electronic device for API risk equipment identification based on single classification, the method comprising: obtaining original equipment sample data from multiple channels; configuring a unified standard for identifying risk equipment in the multiple channels, and labeling the data in the original equipment sample data that meets the unified standard; extracting the labeled risk equipment data in the original equipment sample data as training samples to train a single classification model; and identifying risk equipment accessed through different channels based on the trained single classification model. The present invention unifies the standards for identifying risk equipment in various channels, and trains a single classification model based on the unified risk equipment standards, thereby ensuring the unification of risk equipment identification results by various network service platforms, and after identifying risk equipment, other equipment is considered risk-free equipment, thereby unifying the risk identification results of various platforms and improving risk control capabilities.