43 results about "Client status" patented technology

Systems and methods for receiving an enterprise resource dataset associated with a customer from an enterprise application associated with the customer, the enterprise resource dataset including a plurality of financial inputs captured on or before a first date, a plurality of customer recommendations, and a plurality of recommendation replies, receiving, from a first machine learning model, a predicted customer state including one or more predicted financial outputs corresponding with the predicted customer state at a second date subsequent to the first date, providing the plurality of financial inputs to a second machine learning model trained to predict a customer recommendations, determining, a customer recommendation corresponding to an action to be performed at a third date subsequent to the first date, wherein performing the action causes the first machine learning model to predict an updated customer state differing from the predicted customer state.

Systems and methods for receiving an enterprise resource dataset includes a plurality of financial inputs captured associated with a customer from an enterprise application associated with the customer, providing the plurality of financial inputs to a machine learning model trained to predict a customer state using a plurality of training financial inputs and a plurality of training financial outputs, each of the plurality of training financial inputs corresponding to financial data and each of the plurality of training financial outputs corresponding with financial data, determining, responsive to providing the plurality of financial inputs to the machine learning model, a future customer state of the customer, including a predicted financial output, at a fourth date, and generating one or more financial recommendations based at least partially on the determined future customer state of the customer.

The invention relates to the technical field of customer relationship management, and discloses an intelligent customer life cycle management SCRM system, which comprises a multi-source data acquisition and fusion engine; a dynamic customer portrait modeling engine; a customer life cycle state evaluation engine; a predictive intervention engine; an intelligent strategy decision engine; a task distribution and execution engine; and a feedback closed loop and learning engine. According to the intelligent customer life cycle management SCRM system and method, by setting a multi-modal decision engine, taking a customer state as input, learning an optimal strategy of maximizing a long term value (LTV) through a DQN / PPO algorithm, when a customer is in a high loss risk state, triggering an exclusive retention scheme for the customer, and generating a strategy according to a comprehensive conversion rate, cost and satisfaction target, so that the customer life cycle management is realized. Moreover, the personalized content template can be automatically generated, the optimal information channel is accurately sent to different clients, personalized matching is carried out for the clients, and the loss rate of the clients is reduced.

The invention relates to the technical field of artificial intelligence and data processing, and discloses a digital customer value evaluation method and system based on artificial intelligence, and the method comprises the steps: obtaining customer behavior data, and processing the customer behavior data into a behavior vector sequence; calculating a customer behavior entropy representing the uncertainty of the next behavior of the customer and evaluating a potential value interval representing the value tendency so as to jointly form a two-dimensional dynamic state of the customer; according to the two-dimensional state, a differentiated intervention strategy mode is determined through a value gating decision-making mechanism, and an execution intervention action is generated; and tracking an intervention effect through a closed-loop feedback link, and carrying out self-optimization updating on a model in the system. According to the method, accurate and multi-dimensional dynamic perception can be carried out on the customer state, differential intervention is realized, the effectiveness of decision making is continuously improved through self-learning, and the automation and intelligence level of customer operation is remarkably improved.

The invention discloses a cross-border e-commerce platform customer value evaluation method based on artificial intelligence, and relates to the technical field of customer value evaluation.A digital twinborn technology is adopted, customer behavior time series data and multi-modal features are fused into a virtual image through nonlinear mapping, discrete data are converted into continuous images to be displayed, and the customer value is evaluated. Therefore, the customer behavior evolution process is visually presented; after time series data mean value aggregation, mapping the time series data mean value with multi-modal features, adjusting influence of each piece of data by using a weight matrix and bias, realizing effective connection between the data, and intuitively displaying a corresponding relationship between a customer state and a behavior; customer behavior data are encoded and decoded through a depth auto-encoder, reconstruction errors are calculated and are converted into abnormal scores through a score mapping function, and abnormal detection is carried out in combination with an isolated forest algorithm, so that early warning signals are generated, and the risk of sharp increase of returned goods and abnormal transaction is recognized in time; the defects of a traditional method in the aspect of real-time risk monitoring are overcome.

The invention discloses an MQTT offline message caching method and device and a medium, and relates to the technical field of MQTT communication. The method comprises the following steps: integrating an MQTT plug-in, wherein the MQTT plug-in is respectively connected with an Internet of Things server, a publishing end and a subscription end; when the MQTT plug-in receives client authentication information sent by the Internet of Things server, whether caching is carried out or not is judged according to subscription Topic in the ACL and a corresponding TTL value, and a message task queue is created or updated when caching is needed; a client is authenticated and the online state of the client is updated through an MQTT plug-in, when the MQTT plug-in receives information that a publishing end publishes a message to a Topic, a subscription Topic matched with the published message Topic in the authentication information of the client is searched, the message is sent or offline caching is carried out according to the state of the client, and then the cached message is sent after the client is online. According to the MQTT offline message caching method, the MQTT offline message caching device and the medium provided by the invention, efficient offline message management is realized by expanding the MQTT plug-in.

The embodiment of the invention provides a multi-source heterogeneous data processing method and device, equipment, a medium and a product, and relates to the field of artificial intelligence or the field of financial science and technology. A dynamic knowledge graph is constructed by acquiring multi-source heterogeneous data including customer-related data from different data sources and having different formats or structures, and multi-task processing of customer loss prediction, product recommendation and compliance detection is performed on the dynamic knowledge graph through a graph neural network. According to the method, the dynamic knowledge graph which can be updated in real time is constructed, and the graph neural network is combined to realize multi-task processing, so that the problem that an existing service system depends on a static label system and cannot meet dynamic change of customer requirements is solved, dynamic perception of customer states is realized, and customer experience is improved. The processing precision and efficiency of tasks such as customer loss prediction, product recommendation and compliance detection are effectively improved, and reliable data support is provided for business decision making.

The invention discloses a customer relationship maintenance optimization system based on comparative learning, and the system comprises a data collection and preprocessing module which is used for collecting and preprocessing multi-source behavior data associated with a target customer; the customer characterization module is used for training the standardized customer data set by adopting an improved MoCo-v3 contrast learning method to generate a customer characterization model; the customer state analysis module is used for carrying out feature coding, similarity calculation and state marking on the target customer; the maintenance instruction generation module is used for determining maintenance content and an execution mode based on the client state information; the model updating module is used for collecting actual response behavior data and performing incremental training on the customer characterization model; and the maintenance optimization module is used for outputting a customer relationship maintenance optimization result based on the updated customer characterization model. According to the invention, the improved comparative learning method is adopted to realize the intelligent maintenance of the customer relationship, and the method has the advantages of accurate feature representation, adaptive strategy optimization and high maintenance efficiency.

The invention belongs to the technical field of artificial intelligence, and relates to an artificial intelligence-based strategy generation method, which comprises the steps of converting first utterance data input by a student into a semantic vector, and combining the semantic vector with a customer state space of a virtual customer to obtain an initial state representation; performing verbal skill action strategy selection on the initial state representation based on a deep reinforcement learning network to obtain a target verbal skill action; updating the client state space based on second utterance data corresponding to the target verbal skill action and preset dimension information to obtain a target client state space; and if the current dialogue meets the ending condition, performing feature extraction on the target customer state space to obtain a state feature, and when a target dialogue scene matched with the state feature exists in the historical dialogue scene feature library, obtaining a verbal strategy corresponding to the target dialogue scene and pushing the verbal strategy to the student. The method can be applied to a strategy generation scene in the financial science and technology field, and can intelligently and accurately provide a real-time verbal strategy for students.

The invention discloses a dynamic limb interaction method and system for an electric power intelligent service virtual digital human, and relates to the technical field of fusion of virtual digital human intelligent interaction and an electric power service system.The method comprises the steps that customer multi-source information is collected, and in combination with limb behavior actions, interaction intentions and customer state tags are extracted; analyzing the semantic tag and the state tag, judging operation logic according to a business rule, and generating a candidate limb action sequence; and iteratively adjusting the action output parameters according to the client interaction feedback data, and generating and executing the digital human action corresponding to the semantics. According to the method, client intention and state labels are extracted through multi-source data fusion, a candidate action sequence is generated in combination with power business logic, action output is iteratively optimized based on a reinforcement learning strategy network, and finally dynamic limb interaction highly matched with client semantics and states is achieved. The defects of perception, decision making and adaptability in the prior art are overcome, and the refinement and humanization level of intelligent services is improved.

The invention relates to the technical field, in particular to a customer data digital management method and system based on a CRM system, and the method comprises the steps: carrying out the deep integrated non-inductive collection of multi-source heterogeneous data generated by the interaction of customers through a mobile terminal; automatically matching the data with CRM customer information and associating the data with a corresponding customer digital file; performing automatic analysis on the interaction data based on a pre-configured business rule set, and judging a sales follow-up behavior state and compliance; responding to a judgment result, automatically triggering a client management instruction, updating a client state or generating an intervention signal. Multi-source data intelligent acquisition is realized through deep integration of the mobile terminal, full-course digitization and intelligentization of customer data management are realized in combination with automatic matching, rule-driven analysis and a real-time execution mechanism, the accuracy of data integration and the efficiency of sales follow-up are remarkably improved, and the manual intervention cost and the management risk are effectively reduced.

A system for AI-driven multi-bank payment orchestration with secure real-time transaction processing and regulatory compliance management, wherein the system (100) comprises: a transaction capture and normalization module (1) configured to receive transaction requests from a variety of banks, payment service providers, merchants, customer channels and enterprise interfaces and generate a normalized transaction profile that includes transaction amount, currency, originating bank, destination bank, sender's responsibility, recipient's responsibility, transaction time, payment channel availability and contextual metadata;a module (2) for monitoring the state of the multibank payment network, configured to maintain a dynamic representation of the participating banks, payment channels, settlement corridors, liquidity availability, processing costs, congestion levels, probability of default, and predicted settlement latency; a federated engine (3) for modeling fraud risk, configured to generate fraud risk assessments for combinations of transactions and routes by using privacy-compliant, cross-bank model learning without transferring raw transaction data between participating banks;an AI-based regulatory compliance check engine (4) configured to assess jurisdiction-specific regulatory requirements, sanctions restrictions, anti-money laundering thresholds, Know Your Customer status, payment route authorization rules, and policy version data prior to route execution; an augmented learning adaptive routing engine (5) configured to select an optimized payment route from the eligible routes based on settlement latency, costs, liquidity, fraud risk, and compliance risk; a secure real-time transaction execution controller (6) configured to execute the selected payment route through one or more banking interfaces and payment channels, enforcing authentication, encryption, authorization, and transaction status monitoring;and a blockchain-based audit and regulatory traceability layer (7) configured to generate immutable audit records corresponding to routing decisions, fraud checks, compliance checks, execution events and regulatory reporting events, with the fraud risk assessment and compliance eligibility output being used as active decision inputs for selecting the payment route prior to transaction execution.

The invention discloses a customer resource allocation inheritance method and system oriented to enterprise WeChat and a medium. The method comprises the following steps: constructing a rule pool comprising a triggering condition, a filtering condition and a receiver matching rule; periodically monitoring customer states and automatically marking to-be-inherited customers; an optimal inheritor is intelligently screened for the to-be-inherited client through a rule matching engine; calling an enterprise WeChat interface to execute customer resource transfer and synchronize related data; and establishing an inheritance tracking and feedback mechanism. By constructing the configurable customer inheritance rule pool, intelligent customer inheritance under multiple scenes is realized, the problems of low customer resource allocation efficiency, dependence on manual operation and the like caused by employee demission, customer idling and the like in existing enterprise WeChat customer management are solved, automation and intelligence of a customer inheritance process are realized, and the customer resource allocation efficiency is improved. And the redistribution efficiency and accuracy of the customer resources are obviously improved.

Systems and methods are provided for providing references to additional services solicited by a client relating to transactions (e.g., real estate or other transactions) and / or other information from engagement platforms and other applications. Centralized systems and related methods for providing such references interact with a user interface with dynamic data display, client status and agent rating features, and customizable and interactive elements, and are used to facilitate providing such references, resulting in enhanced service management, improved communications, quality assessments and feedback, centralized information access, adaptability and customization, and progress tracking, and which can be used by human and / or artificial intelligence agents to enhance the particular application.

The present invention belongs to the field of computers, and specifically relates to a method, system, device and medium for client fault optimization. The method includes: collecting the business operation status of a private client and a server, and judging whether an abnormality occurs to the private client and the server in a predetermined manner based on the operation status of the private client and the server; and sending the abnormal state information and / or processing method of the abnormal end to the non-abnormal end according to the judgment result. A client fault optimization is proposed through an embodiment of the present invention, which can not only monitor the client status and display information through the storage system, but also in certain fault scenarios, the storage system Monitor service compares the collected status information of the server and the client, completes the abnormality judgment, and informs the client to complete the corresponding recovery operation. The technical solution of the present invention effectively improves the reliability of the storage system.

A secure computer network is described, within which a routing node interacts with multiple client nodes each assigned for local user use. The client nodes each periodically report operating data for the client node reflecting (a) a level of availability of the client node to perform external requests, (b) a level of availability on the client node of each of multiple software modules, and / or (c) a predicted level of performance of the client node in executing each software module. The routing node receives this operating data, and uses it to update a client status resource for each of the client nodes. When it receives a request identifying a software module and input data, it uses the contents of the client status resource to select a client nodes, to which it causes the request to be delegated to execute the identified software module upon the input data to produce execution results.

An object of a system according to an embodiment is to simultaneously improve a knowledge level and a service skill level of a crew.SOLUTION: A system includes a customer situation input unit, a talk generation unit, and an information inquiry generation unit. The customer situation input unit inputs a situation of a customer. The talk generation unit generates a talk of the high acquisition crew on the basis of the customer situation input by the customer situation input unit. The information query generator generates a necessary information query together with the token generated by the token generator.SELECTED DRAWING: Figure 1

A system and method for automatically transitioning between carrier and IP messaging that can include receiving a messaging request specifying a destination endpoint for a message, retrieving client status of the destination endpoint from a client application registry system, determining, based on whether the client application is reachable using an IP-based communication protocol and on features supported by the client application, a messaging protocol option selected from one or more carrier-based communication options and one or more IP-based communication options, and transmitting the message to the destination endpoint using the selected messaging protocol option.

The invention relates to a storage gateway resource recovery method, which is applied to the technical field of storage. The method comprises the following steps: a pooling controller applied to a storage gateway resource pool responds to a resource recovery request for a target storage gateway, firstly obtains a cloud disk list in the target storage gateway, and then divides the cloud disk list into a first cloud disk list and a second cloud disk list according to the client state of each cloud disk in the cloud disk list; then, deleting the second cloud disk list from the target storage gateway; and sending the first cloud disk list to a corresponding target client to indicate the target client to migrate a cloud disk access path of the first cloud disk list, and under the condition that the cloud disk list in the target storage gateway is empty, recycling storage resources of the target storage gateway. By adopting the method, the resource recovery of the storage gateway can be quickly realized on the basis of ensuring that the cloud service is not interrupted.

The invention provides an international logistics e-commerce customer resource management method and system, and belongs to the technical field of logistics management. The method comprises the following steps: collecting data information related to a client according to a business scene, verifying the data information and storing the data information; analyzing and determining a weight coefficient in combination with historical data, performing dynamic adjustment, and calculating a customer activeness score to judge a customer state; according to a judgment result, client unbinding or salesman rebinding is carried out; after the client unbinds or the salesman completes rebinding, the system sends a notification to the related salesman and records operation information; the system comprises a data acquisition and verification module, a client activeness calculation module, an unbinding module, a binding strategy module and a notification and recording module. According to the invention, the problems of inflexible data acquisition, inaccurate activeness evaluation, unreasonable binding mechanism, imperfect notification record and the like existing in customer resource management in the prior art are solved.

The invention relates to the field of artificial intelligence, can be applied to the fields of finance and medical treatment, and discloses a speech generation method, device, equipment and medium for coping with customer apathy response, and the method comprises the steps: obtaining a target sales strategy matched with a customer state recognition result from a sales strategy library when it is determined that a customer is in an apathy state; a sales promotion prompt template and a guide question are obtained through the target sales strategy, the historical dialogue text and the guide semantic slot position set, and then customer interest contour information is obtained through customer feedback information corresponding to the guide question; and inputting the historical dialogue text, the customer state recognition result, the sales promotion prompt template and the customer interest contour information into a pre-trained large language model to obtain a target verbal skill output by the large language model. According to the method, the semantic understanding capability, the context sensing capability and the sales strategy knowledge of the large language model are fused, so that the verbal skill content output by the large language model is optimized, and the sales success rate is improved.

The invention relates to the technical field of coupon generation, and discloses a dynamic coupon generation method and system, and the method comprises the steps: collecting the historical behavior data of a customer, building a state vector, and initializing the state information of the customer; setting a coupon strategy variable based on the customer state; constructing a cost and response benefit function, and establishing an optimization target model of the coupon strategy; solving the objective function through a numerical optimization method to obtain an optimal coupon strategy path; generating coupon information according to the strategy path, and binding the coupon information to the client identity label; the system comprises a data source module, a data cleaning module, a feature engineering module, a strategy engine module, an optimization module, a coupon code generation module and a distribution module. According to the technical scheme of constructing the customer state vector model based on the customer historical behavior data, a more accurate coupon strategy generation effect is achieved, personalized coupons can be customized for each customer, and the utilization rate of the coupons and the satisfaction degree of the customers are improved.

This invention discloses a dynamic management system for DingTalk Stream mode in a multi-tenant scenario, comprising a configuration access layer, a core control layer, and a resource support layer. The configuration access layer includes a configuration management module and a manual control module. The core control layer includes a configuration listening module, a health check module, an event bus module, and a client factory module. The resource support layer includes a resource management module, a multi-tenant client pool module, and a log recording module. A ConcurrentHashMap client pool with tenant ID as the key is used to achieve independent storage and thread-safe access for each tenant client instance. Through collaboration between modules in the core control layer, automatic creation, updating, and destruction of clients driven by configuration changes are achieved. Automatic monitoring of client status is achieved based on timed heartbeat monitoring and event-driven mechanisms. On-demand resource allocation is achieved through expansion / contraction mechanisms and resource quota management, while a resource early warning mechanism is also added.

The invention discloses a customer data-driven precision marketing activity generation method and system, and relates to the technical field of customer data processing and precision marketing, and the method comprises the steps: fusing text, image and behavior sequence data through a multi-modal feature extraction technology, and generating an enhanced customer portrait vector; in combination with a dynamic decision-making mechanism of a reinforcement learning agent, a customer state is mapped into a quantifiable marketing action tuple, and real-time accurate adaptation of a marketing strategy is realized; a closed-loop optimization architecture from strategy execution to feedback capture is constructed, and a value function is continuously updated by utilizing a customer response behavior, so that the defect of strategy adjustment lagging of a traditional system is overcome. And finally, the adaptability of a marketing strategy is enhanced while the customer portrait accuracy is improved, and the whole technical scheme naturally has a cross-channel collaborative execution capability, so that full-process automation support is provided for precise marketing activities.

The invention provides a financial linkage business guidance system, and relates to the technical field of financial equipment, in the device, a registration module identifies and receives customer information and transmits the customer information to a central control module, a judgment module judges customer demands and feeds back the customer demands, and a guidance module is pre-filled in to guide customers to take a table corresponding to their business; the path guiding module guides a client to a vacant site of a data filling area, the state monitoring module identifies the client state in real time, and light guides the client to a rest area or a handling window. The modules in the device exchange information, the central control module carries out overall processing and issues an instruction, and intelligent guiding of the whole process of business handling is achieved.

The embodiment of the invention provides a latent guest mining method and related equipment, and belongs to the technical field of latent guest identification. The method comprises the steps of obtaining platform behavior data of a first object; the platform behavior data is obtained by performing identity unification on original behavior data which are obtained from a plurality of different platforms and are associated with the first object; performing feature extraction according to the platform behavior data to obtain a car purchase behavior feature and a social behavior feature of the first object; the vehicle purchase behavior characteristics are related to individual vehicle purchase behaviors; the social behavior characteristics are related to group vehicle purchasing behaviors; determining an individual purchase intention of the first object based on the car purchase behavior characteristics; determining a group purchase impact of the first object based on the social behavior features; analyzing based on the individual purchase intention and the group purchase influence, and determining the customer state of the object; according to the embodiment of the invention, the automobile sales conversion rate can be effectively improved through the technical means of unification of multi-platform data identities and individual group double-aspect analysis.

The present invention discloses a customer value evaluation method for a cross-border e-commerce platform based on artificial intelligence, which relates to the technical field of customer value evaluation. The present invention adopts digital twin technology to fuse customer behavior time series data and multimodal features into virtual images through nonlinear mapping, so that discrete data is converted into continuous image display, thereby intuitively presenting the evolution process of customer behavior; the time series data mean is aggregated and mapped together with the multimodal features, and the influence of each data is adjusted using a weight matrix and bias to achieve effective docking between data, and intuitively display the correspondence between customer status and behavior; the customer behavior data is encoded and decoded through a deep autoencoder, and the reconstruction error is calculated, which is converted into anomaly scores through a scoring mapping function, and then combined with the isolation forest algorithm for anomaly detection, thereby generating early warning signals, and timely identifying the risks of surge in returns and abnormal transactions, thereby making up for the shortcomings of traditional methods in real-time risk monitoring.

A client-side state management system for a lithography machine is provided. This system includes: a system state module for configuring system states; an object management module for maintaining pointers to interface object instances based on system state changes, wherein the interface object instance pointers are associated with system state changes through registration and removal; and a control operation module for setting control operation modes based on task IDs according to system state changes. By managing system state changes through an object management module independent of system state, and setting control operation modes by the control operation module when system state changes, the efficiency and rationality of user task execution are improved.

The invention discloses a method for supporting real-time development of marketing activities, and the method comprises the steps: enabling branches to autonomously maintain activity numbers, standard judgment types and white list data through a branch intelligent management platform which comprises a data storage module, a parameter checking module, a judgment execution module and an interface calling module; when a customer participates in an activity, a head office platform forwards a standard judgment transaction to a branch system, after the branch system checks parameters, judgment is executed in three types including white list judgment, real-time judgment and white list and real-time judgment, whether the customer is in a white list or not is judged and verified in the white list, and the state of the customer is verified by calling an external interface in real time. According to the method, the problems of slow response and incapability of real-time judgment of the head office are solved, the activity period is shortened, and the marketing efficiency is improved.

Provided are a system, a method, and a program of banking operation support for supporting execution of accurate and efficient banking operations. A control unit (21) of a support server (20) acquires external state information, a financial transaction condition, customer state information, and a financial transaction state of the same time period, from a back-end system (40); performs machine learning using a data set made up of the acquired pieces of information as learning data, and generates a customer action prediction model which associates the financial transaction condition with the financial transaction state; and calculates, for a current external state and a current customer state, a financial transaction condition corresponding to a target value of a transaction state using the customer action prediction model.