762 results about "Customer information" patented technology

The invention relates to the technical field of automatic arrangement, and discloses a method and device for automatically arranging a business relation chain and a storage medium, and the method comprises the steps: constructing a business rule base based on supplier information, customer information and business information, and carrying out the standardization processing of customer demand data, and obtaining the standardized business demand information; performing multi-dimensional matching operation on the standardized business demand information based on the business rule base to obtain an initial supplier set, and performing dynamic weight adjustment on the initial supplier set to obtain an optimal supplier sequence; constructing a chain node graph according to the optimal supplier sequence, calculating and verifying a business constraint relationship between nodes, and generating a business relationship chain; the business relation chain is converted into a standard order format, order data synchronization is completed and an order synchronization result is output through encryption signature and a concurrent distribution mechanism, and the accuracy and efficiency of business relation chain arrangement are improved.

The invention relates to the technical field of semantic analysis, can be applied to business scenes of financial science and technology, medical health and the like, and discloses an intention analysis and strategy generation method, device, equipment and medium, and the method comprises the steps: obtaining interaction data, recognizing an interaction type according to metadata features, selecting a corresponding analysis model to analyze and process data, and generating a text corpus; current user information is extracted from the text corpus, user intention score analysis is executed based on an intention analysis strategy corresponding to the interaction type, and a current user intention score is generated; and generating a demand list according to the user information, the intention score and the interaction type, and generating and outputting an interaction strategy based on the user information and the demand list. Through interaction data processing and automatic intention scoring analysis, the demand list and the interaction strategy of the customer can be quickly and accurately generated, the customer information processing efficiency and accuracy are improved, the workload of manual input and analysis is reduced, and the customer service quality and the response speed are improved.

A method, apparatus, and system of activating and using a contactless card via unique activation codes are disclosed. A system includes a memory and a processor configured to: receive an account number for a contactless card from a third party computing system; generate a card activation code for the contactless card, the card activation code being unique to the contactless card; generate a customer-specific uniform resource locator (URL) by appending the card activation code to a general URL, the general URL being associated with an entity of the system; transmit the customer-specific URL to the third party computing system with instructions to write the customer-specific URL into a wireless chip of the contactless card; associate the card activation code with the account number and information regarding a customer associated with the contactless card; and store the card activation code within the memory to be referenced during activation.

The invention relates to the technical field of information encryption, in particular to a customer information encryption protection method in a pork transaction process, which comprises the following steps of: based on pork transaction data, sequentially finishing key distribution path sorting and serial number verification, screening deviation in combination with customer operation behaviors, adjusting a sensitive field encryption strategy and replacing a key; and performing consistency verification on the identity data abstract combination, generating a signature according to the transaction content, and verifying a signature consistency result. In the invention, through a dynamic key path and inter-node sorting coding, real-time adjustment of a flow link is realized, transaction behavior data drives an encryption strategy to be switched in time, a sensitive field key can be dynamically updated along with the change of an operation characteristic, and segmentation consistency confirmation of a client identity is realized through multi-abstract combination cross verification; digital signatures are synchronously incorporated into double check of multi-source abstracts and transaction contents, and when behavior abnormity and node abnormity are found, related processes are actively interrupted, and risk marking is automatically completed.

The invention relates to the technical field of big data analysis, in particular to an operation management system and method based on financial marketing big data, and the system comprises a data standardization module, a customer portrait disambiguation module, a strategy matching module, a real-time transmission module and an operation strategy generation module. According to the method, a data table with a unified structure is constructed through combined judgment of field semantics and numerical rules, the data consistency is improved, customer information integration is executed based on field conflict time, credibility level and logic verification, the recognition accuracy is enhanced, and the matching relation is judged by combining the transaction amount, the product association degree and the interaction frequency with strategy attributes; according to the method, strategy dynamic screening is achieved, pushing content is screened according to the strategy emergency degree and the channel state, the transmission efficiency is improved, customer clicking, conversion and feedback participate in behavior trend judgment, strategy updating linkage is supported, an overall processing chain is of a closed-loop structure, and the fusion accuracy and the strategy response timeliness are improved under the conditions of data fragmentation and multi-source heterogeneous.

The invention belongs to the field of artificial intelligence, can be applied to the field of finance, and relates to a product recommendation method, which comprises the steps of classifying historical insurance policies according to a preset dimension, and generating a corresponding classification label for each classification category; matching the customer tags of the potential customers with the classification tags to obtain target classification tags; screening out a target customer group according to the target classification label; inputting the obtained target customer information of the target customer group and the target claim settlement case into a verbal skill recommendation model, outputting a target recommended verbal skill, pushing the target recommended verbal skill to potential customers, and receiving voice data fed back by the potential customers; recognizing the voice data to obtain recognized text data; and matching a target product based on customer demand information extracted from the identified text data, and recommending the target product to potential customers. The invention further provides a product recommendation device, computer equipment and a storage medium. In addition, the invention also relates to a block chain technology, and the client tag can be stored in a block chain. According to the method, clients can be accurately positioned, and the product recommendation effect is improved.

A system and computer-implemented method of continuously updating information about one or more of a customer approved for a mortgage and a real estate property identified as mortgage ready. The method includes monitoring information accessed from a memory storage location corresponding to a customer identification number, the information used to determine the customer is approved for a mortgage, and receiving new information about the customer, the new information used to determine the customer is approved for a mortgage. The method also includes updating, at a memory coupled to the one or more processors, the memory storage location to include the new information. The method still further includes recalculating the amount in which the customer is approved for a mortgage based upon the new information received.

The invention discloses an automatic order sending system with an intelligent matching function, and the system comprises a data collection module which is used for collecting customer information, order information, service personnel information, and environment information; the data acquisition module is connected with a plurality of data sources, and obtains customer information such as basic information, historical order data, consumption habits and preferences of customers through an interface protocol; order information such as the type, the amount, the time, the emergency degree and the special requirement of the order is acquired; and service personnel information such as skill level, working experience, working time arrangement and service area preference of the service personnel is obtained. According to the automatic order sending system with the intelligent matching function provided by the invention, the technical aspect of the automatic order sending system with the intelligent matching function is remarkably improved. Through multi-dimensional data acquisition, the system can obtain more comprehensive and accurate information, and a solid data basis is provided for intelligent matching.

The invention discloses a customer information storage management method and system based on a block chain, and relates to the technical field of distributed data evidence storage, and the method comprises the steps: collecting terminal customer information, generating an encrypted data packet, carrying out erasure coding, and generating an encrypted data fragment set; carrying out distributed storage based on the encrypted data fragment set, and calculating a data availability commitment at the same time; executing availability sampling according to the data availability commitment, and generating a fragment validity proof; based on the fragment validity proof, performing format and validity verification to obtain a to-be-processed proof set; and generating a recursive aggregation proof according to the to-be-processed proof set, and submitting the recursive aggregation proof to the block chain to verify and update a proof storage state. And cryptographic authentication is carried out on the persistent evidence storage state of the data assets, so that the dual beneficial effects of ensuring data privacy and credible evidence storage are achieved.

The invention provides a customer marketing method and device, electronic equipment, a medium and a program product, and can be applied to the technical field of big data and the technical field of artificial intelligence. The method comprises the steps of obtaining multi-dimensional customer information, and performing customer grouping based on the multi-dimensional customer information to obtain a target customer group; executing first marketing push based on the target customer group to obtain customer response information; on the basis of the customer response information, using a prediction model to carry out purchase willingness prediction to obtain a purchase willingness score; and generating a recommendation list based on the purchase intention score, and executing second marketing push based on the recommendation list.

The invention provides an AI-based customer service intelligent interaction method and system, and a medium. The method comprises the following steps: collecting attribute information and behavior track information of a target customer, processing to obtain a customer information portrait, extracting personalized demand information of the target customer according to the customer information portrait, executing intelligent interaction service based on the personalized demand information, monitoring an interaction service process in real time, collecting service state parameters, and sending the service state parameters to the target customer. Whether manual customer service switching needs to be executed or not is judged according to the service state parameters, intelligent interaction service in a preset time period is monitored, service index data is extracted, quantitative evaluation processing is conducted according to the service index data, a service reliability coefficient is obtained, the reliability of the intelligent interaction service is judged, and corresponding optimization measures are taken. Therefore, the AI-based customer service intelligent interaction technology is realized.

There is a system for admitting automobiles to a venue comprising: at least one camera for recognizing an automobile, and a license plate. A server is configured for receiving a picture of the automobile and a picture of the license plate of the automobile. Furthermore, there is at least one database for storing, matching and identifying the picture of the automobile and the license plate. In addition, there is at least one screen for allowing a user to identify their automobile taken from a list of automobiles. There is also a process for tracking an automobile within an area which comprises the steps of identifying a pre-defined area and identifying an automobile for screening into the area. Next the auto and its license plate are photographed. This information is stored in a database and then used to generate invoices and track the location of these automobiles. Customer can access the database, enter the license plate of his vehicle, the database recognizes his vehicle, the customer makes payment for his vehicle, and the app places the customer information onto the PAID category list on the database.

The invention relates to a cold and hot data migration method and device, computer equipment, a readable storage medium and a program product, and relates to the technical field of software development. The method comprises the steps of obtaining customer information in response to a trigger operation for a front-end application; inputting the customer information into a pre-trained customer behavior prediction model to obtain a customer behavior prediction result; comparing the customer behavior prediction result with a cold and hot data knowledge graph to obtain associated data corresponding to the customer behavior prediction result and a predicted cold and hot data type of the associated data; generating a migration strategy for the associated data according to the actual cold and hot data type of the associated data and the predicted cold and hot data type; the migration strategy is used for migrating the associated data to a first memory where hot data is located or migrating the associated data to a second memory where cold data is located. By adopting the method, the identification accuracy of cold and hot data can be improved.

A system and method for outbound call campaign management model in a contact center using a generative artificial intelligence which processes prompts such as “Schedule a follow-up call with client X,” understanding intent and context. Leveraging pre-trained language understanding, it interfaces with campaign components, scheduling calls or updating client information. The model dynamically adapts to varying scenarios, enhancing efficiency and personalization. The system employs secure interfaces, integrates with contact center tools, and undergoes continuous improvement through periodic retraining, ensuring optimal performance and compliance with evolving campaign requirements. Overall, it streamlines outbound call operations, automating actions and facilitating smoother interactions for a more productive and customer-centric contact center environment.

The invention discloses a customer information updating and management method and system based on big data, and relates to the technical field of big data and customer relationship management. Comprising the following steps: firstly, collecting multi-source customer data and constructing a multi-dimensional time sequence characteristic panel; then, through sharing an integrated model of a bottom layer, synchronously predicting a dynamic life cycle value and a continuous loss risk probability of the customer; the network influence weight of the customer is quantified by using an influence penetration model and Monte Carlo simulation; further, fusing the three dimensions, and generating a resource allocation coefficient through a multi-objective optimization function based on a customer type dynamic configuration weight; and finally, automatically updating the customer label based on the coefficient, and combining atomic operations through a strategy arrangement engine to form personalized strategy workflow execution and closed-loop optimization. According to the method, the problems of static isolation and strategy lag of traditional customer information management are solved, and accurate insight of customer values and dynamic intelligent distribution of management resources are realized.

The invention provides a dynamic permission smart contract generation method and system based on data sensitivity self-adaption, and relates to the technical field of data security, the method comprises the following steps: classifying and marking multi-dimensional data in a business scene, and constructing a customer information classification matrix according to data types; based on data types of the client information classification matrix, sensitivity quantitative evaluation is carried out by utilizing a rule engine based on a decision tree, the engine takes a data use scene, a regulation constraint label and a timeliness weight label as input, a sensitivity result is judged and output according to a preset tree-shaped path, and a structured sensitivity level matrix is generated after all data types are traversed; and according to the data sensitivity level matrix, in combination with a preset post role permission rule, establishing a mapping relationship between data sensitivity and role permission, and generating a dynamic permission policy tree. According to the invention, through data classification and sensitivity evaluation, the data security is balanced and the protection capability is improved.

The invention discloses an intelligent customer obtaining method and system based on multi-modal data, and relates to the technical field of multi-modal data. Corresponding customer demand information is determined according to detection of a demand space; according to the content of the customer demand information, the information weight and the multi-modal data, multiple pieces of target data in the multi-modal data are determined, and the final customer obtaining path is determined based on the multiple pieces of target data, the enterprise database and the customer demand information, so that the accuracy of the customer obtaining path is improved. Therefore, the corresponding customer information is determined according to the detection of the customer obtaining node of the customer obtaining path, and the corresponding customer obtaining mode is matched based on the customer information and the customer demand information; and determining a corresponding customer obtaining number according to the execution of the customer obtaining mode, and triggering autonomous optimization of the customer obtaining mode according to the customer obtaining number and the execution condition of the customer obtaining mode until the customer obtaining number is greater than a preset customer obtaining number threshold value, so as to improve the intelligent customer obtaining effect.

The invention relates to a tobacco enterprise customer classification and grading method and system based on sentiment analysis, and the method comprises the steps: obtaining the session data inputted by a customer in a tobacco customer service scene, and judging the intention of the customer; inputting the session data into a pre-trained multi-mode sentiment analysis model, and outputting a sentiment analysis result of the current customer dialogue data; acquiring target customer information initiating the current session, and inputting the target customer information into a pre-trained customer classification and grading model for processing; and generating a recommended customer strategy based on a Q-Learning algorithm, optimizing a service strategy by combining a preset generative AI model with the customer intention of the current customer, the sentiment analysis result and the recommended customer strategy, and generating a response mode and response content based on the optimized service strategy. According to the scheme, a tobacco industry dynamic knowledge base is constructed, and personalized service strategies are formulated in combination with emotional appeals and behavioral habits of customers, so that the answer accuracy and satisfaction of intelligent customer service staff are improved.

Blockchain identity proofing via federation protocols is disclosed. A method may include: receiving, at a digital wallet application for a financial institution on a customer electronic device, a customer login from a customer; receiving, by the digital wallet application and from the customer, a request for an assertion, wherein the request redirects a session with the digital wallet application to a financial institution backend via a financial institution website or a financial institution application using a federation protocol; authenticating, by the financial institution backend, the customer; confirming, by the financial institution backend, the assertion using verified customer information in a verified customer information database; redirecting, by the financial institution backend, the session to the digital wallet application; returning, by the financial institution backend and using the federation protocol, the assertion to the digital wallet application; and writing, by the digital wallet application, the assertion to a distributed ledger.

The invention provides a data management method and device for a credit system, a storage medium and a system, and the method comprises the steps: obtaining customer information under the condition of customer authorization, and carrying out the encryption processing of the customer information, and obtaining encrypted customer information; dividing the encrypted customer information into a plurality of pieces of sub-encrypted customer information with preset sizes; determining a target distributed storage node according to the attribute information of each distributed storage node; and uploading all the sub-encrypted customer information to the target distributed storage node so as to realize storage of the customer information. According to the method and the device, the problem of low data security caused by easy tampering or leakage of user data due to the fact that a centralized data storage mode is generally adopted by a credit system in the prior art is solved.

The invention discloses a multi-platform customer information integration and unified management method and system, and relates to the technical field of customer relationship management, and the method comprises the steps: dynamically accessing multi-platform data through a distributed API gateway, and uniformly converting the multi-platform data into an Avro format data stream through a lightweight container; the method comprises the following steps: processing a data stream by adopting a three-stage cleaning assembly line, extracting multi-modal features in combination with a BERT micro model and a pruned MobileNetV3, and fusing the multi-modal features into 384-dimensional feature vectors according to a weight matrix; dynamically constructing a Transform-XL skeleton network based on the feature flow, and optimizing the model in real time through knowledge distillation and reinforcement learning regulators; constructing a customer portrait version tree by using a dual-channel full-connection layer to realize millisecond-level emergency update; personalized services are generated based on a multi-arm bandit algorithm, feedback is collected, and closed-loop optimization is completed through a preference offset degree driving model scalpel mechanism. According to the method, the problems of real-time fusion of multi-source heterogeneous data, dynamic portrait updating and model adaptive adjustment are solved.

The invention relates to the field of artificial intelligence, can be applied to business system platforms of financial science and technology, medical health and the like, and discloses a digital life cycle management method, device and equipment of a product and a medium, and the method comprises the steps: collecting product associated data of different dimensions, carrying out the demand integration analysis, and generating product demand information; inputting the product demand information into a generative adversarial network for product scheme generation processing to obtain a product design scheme; performing semantic analysis on the product design scheme to generate corresponding standard product information; performing feature matching on the standard product information and different customer groups, determining a target product of each customer group and pushing marketing information; and when a purchase request is received, performing pricing evaluation according to request customer information and request product information in the purchase request, and returning a dynamic pricing result to the customer. The full life cycle management from demand to sales is realized by processing the multi-dimensional product associated data, and the life cycle management efficiency of the product is improved.

Aspects described herein may provide an interface and / or search functionality for a dealership to determine vehicles a customer is most likely to purchase. A recommender system may generate vehicle recommendations for a dealership to sell to a customer based on customer information, vehicle information, and dealership information. Machine learning may be used to generate the recommendations. The recommendations may be based on the vehicle preferences of a customer.

The invention, which relates to the technical field of online customer service evaluation, discloses an online customer service evaluation system for cross-border e-commerce, comprising a customer information acquisition module, a cultural feature mapping module, a weight configuration module, an emotion correction module, an aging evaluation module, a score generation module and a model optimization module. The customer information acquisition module is used for acquiring nationality, language and time zone information during customer session; the culture feature mapping module is used for extracting corresponding power distance, uncertainty avoidance, personality, long-term guidance and positive rigidity feature values from a pre-stored culture dimension database according to the nationality information to form culture feature vectors; and the weight configuration module is used for generating a dynamic weight of a service evaluation index according to the culture feature vector and a preset mapping rule, so that scoring emphasis on accuracy, responsiveness, polite and co-estrus expression under different cultures is different.

Some embodiments provide systems comprises: a customer database; a product database; a training data database; a customer evaluation system configured to implement one or more machine learning acceptance probability models to identify an acceptance likelihood factor, and determine whether the each respective customer has a corresponding acceptance likelihood factor greater than a likelihood threshold value; and a plurality of point of sale (POS) systems configured to complete sales transactions, obtain customer identifying information, and communicate the customer identifying information to the customer evaluation system; wherein the customer evaluation system is configured to communicate customer information to the payment method offer entity when the customer has an acceptance likelihood factor greater than a likelihood threshold value, receive authorization to present the customer with a payment method offer, and to present the payment method offer.

Examples described herein include systems, methods, instructions, and other implementations for data security. One example includes receiving a status inquiry associated with a secure transaction, a merchant system, and a client device. The status inquiry is processed to determine that the merchant system associated with the status inquiry has been previously validated and that the status inquiry is from the merchant system. Then, in response to the determination that the merchant system has been previously validated, postback data including a tokenized client account number associated with client information is accessed and the tokenized client account number is transmitted. The tokenized client account number facilitates processing the secure transaction without the merchant system having access to the client information.

The invention discloses a data processing method and system in an automatic ETL (Extract-Transform-Load) process of a data warehouse. The invention relates to the technical field of data warehouses. And extracting data from the data source table according to a data extraction step defined in the ETL flow chart. In the extraction process, according to a configured integrity detection rule, preliminarily checking the extracted data, including checking whether the number of record lines conforms to expectation and whether a field value is null or missing; through an integrity detection rule, data which does not meet requirements can be effectively filtered out in a data extraction stage, such as data with inconsistent recording lines, null field values or missing data. Therefore, 'junk data 'is prevented from entering a subsequent processing flow, and the data entering the conversion stage has a relatively high quality basis. For example, in the customer information extraction process, if key fields such as customer names and contact information are empty, data can be marked and subsequently processed, and it is ensured that subsequent analysis is based on complete and effective customer data.

The invention discloses a customer information gridding screening method and device, and the method comprises the steps: constructing a preliminary grid boundary of a secondary branch row on an electronic map, and carrying out the adjustment of the preliminary grid boundary based on an electronic fence editing tool, and obtaining a secondary branch row grid boundary; calling an electronic map interface, obtaining latitude and longitude information corresponding to the address information of each enterprise, comparing the latitude and longitude information with the boundary of the secondary branch grid, determining the enterprise located in the boundary of the secondary branch grid, establishing an enterprise database in the secondary branch grid, and when an enterprise query request of a customer manager is received, sending the enterprise query request to the customer manager. And according to a multi-dimensional enterprise screening condition set by a customer manager, screening out an enterprise meeting the condition from the enterprise database in the secondary branch grid, and further displaying the screened enterprise information to the customer manager through a front-end page. According to the invention, the efficiency and accuracy of acquiring enterprise information in a secondary branch exhibition area by a customer manager are improved.

The invention relates to the field of information confidentiality management, in particular to a client information confidentiality management method and system based on an encryption algorithm. The whole-process closed-loop management from key distribution to data encryption and decryption and then to service analysis and optimization is realized. Firstly, high-strength key protection and hardware acceleration provided by a hardware security module are utilized, key management and core encryption and decryption operation of sensitive data are executed in a secure environment as much as possible, and the risks of key leakage and data tampering are reduced from the source. And secondly, the system ensures the responsibility division and information transmission orderliness of each module in the processing flow through clear data stream butt joint. Through the architecture, large-scale and diversified data can be encrypted firstly after entering the system, then differential analysis is realized according to different sensitive levels, and finally a comprehensive result is obtained through linkage optimization.

The invention discloses a customer group-based service method and device and a program product, relates to the field of artificial intelligence and is applied to the field of financial science and technology, and the method comprises the steps: receiving first input information of business personnel, generating a reply text through a main agent, and recognizing a first intention of the business personnel; under the condition that the first intention belongs to the establishment of the customer group, dialogue information between the business personnel and the master agent is sent to a target agent in the multiple slave agents, and interaction with the business personnel is carried out through the target agent; establishing a target customer group based on customer group information in the dialogue information through the target agent; and sending the target customer group to the business personnel, thereby enabling the business personnel to provide services for the customer according to the target customer group. Through application of the method and the device, the problem that the working efficiency of business personnel is relatively low because the business personnel need to establish the customer group by repeatedly optimizing the input customer information in the fixed element of the front-end page when the service is provided for the customer according to the customer group in the related technology is solved.