7 results about "Financial impact" patented technology

The invention provides a new energy project business and finance integrated platform. The platform comprises a station real-time data acquisition module for acquiring operation and state data streams; the business financial data access module accesses a cost and financial rule data flow; the data processing and state estimation module is used for filtering, standardizing and generating high-credibility station state data; a mapping model is built in the business-finance dynamic association engine, and business event-driven finance influence data are cooperatively calculated and output in real time; the dynamic visualization and decision support module receives the data and generates a decision view with a causal link. According to the invention, dynamic association and visual display of the business event and the financial influence can be realized, the operation decision-making efficiency and the financial management level of the new energy project are improved, and the economic benefit and the risk management and control capability of the project are enhanced.

The invention discloses a home insurance intelligent planning and display method and system, a medium and a product, and relates to the field of data processing. According to the method, based on family basic data and a preset actuarial model, family guarantee gap data and a dynamic financial model are calculated; generating an initial insurance planning scheme containing at least one initial graphical representation, and displaying the initial insurance planning scheme on a graphical interface of the user terminal; determining a susceptible risk event corresponding to the family basic data, and receiving a trigger risk event; calling a corresponding preset financial impact parameter according to the easy risk event and the trigger risk event, and performing reconstruction calculation on the dynamic financial model based on the preset financial impact parameter to generate a financial missing model; and based on the financial missing model, modifying the initial insurance planning scheme to obtain a target insurance planning scheme, and displaying the target insurance planning scheme on a graphical interface. By implementing the technical scheme provided by the invention, the pertinence of insurance planning is improved.

The invention relates to the technical field of cloud data processing, and discloses a cloud financial data analysis and early warning device which comprises a cross-domain event aggregation module, a dynamic graph construction module, a causal flow inference module, a pattern convergence analysis module and an interactive presentation module. The method comprises the following steps: aggregating business events from a plurality of business systems, and constructing a dynamic business process map; then, identifying an abnormal disturbance event in the map, and generating one or more abnormal causal chains connected to the quantitative financial influence based on the event tracing so as to generate tactical early warning; the device performs pattern clustering and root cause analysis on the plurality of abnormal causal chains to generate strategic insights. According to the method, the dynamic graph is constructed, and causal inference and mode convergence are executed, so that the problems that traditional financial analysis is lagged and a deep causal relationship between business and finance is difficult to reveal are solved, and prospective and penetrating analysis and early warning from a single business event to a systematic risk root cause are realized.

The application discloses a new media project traffic monetization and financial collection cross-domain data mapping method, belongs to the technical field of business data processing, which comprises the following steps: instantiating business operation data and financial subject data, generating a value event atomic sequence and a financial impact factor set; performing time sequence causal tracking on target atoms, generating a dynamic correlation chain; combining a historical mapping knowledge graph for structured comparison, generating a mapping hypothesis set; generating a target mapping hypothesis through multi-stage verification; correlating and calculating the value event atomic sequence and the financial impact factor set, generating an industry and finance mapping relationship set; using external feedback signals for difference calibration, generating a calibrated industry and finance mapping relationship; and supplementing and logically correcting the historical mapping knowledge graph accordingly. The application adopts the technical means of constructing a business process causal chain and comparing and verifying with an evolvable knowledge graph, and can realize high-precision, self-adaptive and automatic mapping of new media business data and financial subjects.

The invention discloses a cross-domain data mapping method for new media project traffic realization and financial collection, and belongs to the technical field of business data processing, and the method comprises the steps: carrying out the instantiation of business operation data and financial subject data, and generating a value event atomic sequence and a financial impact factor set; performing time sequence causal tracking on the target atoms to generate a dynamic association chain; performing structured comparison in combination with the historical mapping knowledge graph to generate a mapping hypothesis set; generating a target mapping hypothesis through multi-stage verification; performing correlation calculation on the value event atomic sequence and the financial influence factor set to generate a business-financial mapping relation set; performing difference calibration by using an external feedback signal to generate a calibrated business-financial mapping relationship; and performing supplement and logic correction on the historical mapping knowledge graph. According to the method, the technical means of constructing the business process causal chain and comparing and verifying the business process causal chain with the evolvable knowledge graph is adopted, so that high-precision and self-adaptive automatic mapping of new media business data and financial subjects can be realized.

This invention belongs to the field of data analysis technology and provides a method and system for enterprise risk early warning based on dynamic quantification of ESG issues. The technical solution involves calculating the impact importance score of each issue, constructing multi-dimensional ESG scenarios, introducing cross-impact analysis to correct the probability of scenario occurrence, analyzing the changes in financial value under each scenario, and finally decomposing and standardizing the financial impact to output the financial importance score of each issue, which is then integrated to obtain a comprehensive importance score. Based on real-time text data related to the target ESG issues of the enterprise to be evaluated, public opinion analysis and issue relevance analysis are performed to generate dynamic adjustment factors and dynamically adjust the comprehensive importance score to obtain an adjusted dynamic comprehensive importance score. Based on the adjusted dynamic comprehensive importance score, all ESG issues are dynamically prioritized, and risk warnings are issued in conjunction with the set hierarchical warning rules. Corresponding risk management strategies are generated based on different risk warnings.

The invention discloses a financial data processing method and system based on big data analysis, relates to the technical field of financial data processing, and aims to construct a financial data vector set Fin for a target transaction object, break a data island and provide a comprehensive data basis for multi-dimensional analysis. The income stability is evaluated by calculating a transaction fluctuation index Vt; calculating an income channel authenticity score Ra to evaluate the health of the growth mode; and calculating a potential enumeration value Ld, and converting the operation risk into a specific financial influence. A financial feature vector set Fan is constructed based on the risk indexes, a comprehensive risk index IRI is calculated, a transaction decision AIR is generated and executed by comparing the comprehensive risk index IRI with a decision threshold interval theta, a complex analysis process is concentrated into an objective decision basis, and decision efficiency and scientificity are improved. And finally, iterative optimization is performed according to a historical database HIS, a self-learning and evolution closed loop of the model is established, and long-term accuracy and adaptability are ensured.