Consumption finance artificial intelligence base building scheme

Abstract

The invention provides a consumption finance artificial intelligence base construction scheme, and aims to realize intelligence, automation and high efficiency of consumption finance business through construction of an AI middle platform and a self-evolution intelligent finance application platform. The AI middle platform comprises a multi-modal data processing module, an AI model management module, an intelligent labeling and sample management module, a reasoning service module, a platform management module and the like, supports multi-modal data processing and a flexible reasoning mode, and meets diversified requirements of consumer financial scenes. The self-evolutionary intelligent financial application platform integrates functions of intelligent interaction, intelligent supervision, intelligent credit, AI full-life-cycle management and the like, and supports full-process management from data introduction to model application. In addition, automation of document processing, business processes and the like is achieved through the RPA technology and scheme, the business efficiency is remarkably improved, the operation cost is reduced, and the customer experience is optimized. According to the invention, a complete intelligent infrastructure is provided for the consumer finance industry, and the business processing efficiency and accuracy are greatly improved.

Description

Technical Field

[0001] The present invention relates to the field of financial technology, and in particular to a solution for building an artificial intelligence base for consumer finance. Background Art

[0002] With the rapid development of the consumer finance industry, the increase in business volume and complexity have made it difficult for traditional manual operations and manual management models to meet the needs of today's market. Current consumer finance business involves a large number of data processing tasks, such as customer credit assessment, risk control, contract text review, etc. These operations require efficient and accurate processing. However, the existing consumer finance system relies on a large number of manual operations in data processing, customer service, risk control management, etc., resulting in low business efficiency and prone to human errors. In addition, manual processing methods cannot respond to customer needs in real time, and it is difficult to improve customer experience.

[0003] The introduction of artificial intelligence (AI) technology has provided new solutions for the field of consumer finance. Through technologies such as natural language processing (NLP), optical character recognition (OCR), and machine learning, AI can automatically process various types of data such as text and images, thereby realizing the automation and intelligence of consumer finance business. However, most AI systems currently face problems such as complex model management, cumbersome data labeling, single reasoning mode, and low resource utilization in practical applications, making it difficult to efficiently and continuously support the growth and changes of consumer finance business. Existing technologies lack a comprehensive platform that can uniformly manage multiple AI functions and provide flexible reasoning modes and efficient data processing.

[0004] In response to the above problems, the present invention proposes a solution for building an artificial intelligence base for consumer finance, which aims to provide an intelligent and automated comprehensive solution for consumer finance business by building an AI middle platform, a self-evolving smart financial application platform, and a digital human system based on RPA. The solution integrates multimodal data processing, model management, intelligent annotation, reasoning services, platform management, and RPA technology, realizes the automated processing of business processes and efficient use of resources, effectively improves business processing efficiency, reduces operating costs, and enhances user experience. Summary of the invention

[0005] The present invention relates to a solution for building an artificial intelligence base for consumer finance, which aims to achieve intelligent, automated and efficient upgrades in the field of consumer finance by building an artificial intelligence base with an AI middle platform as the core, in conjunction with a self-evolving smart financial application platform and a digital human system based on RPA. The present invention combines multimodal data processing, AI model management, intelligent labeling and sample management, reasoning services, platform management and RPA automation technology, thereby greatly improving the processing efficiency, service quality and decision-making accuracy of consumer finance business, and reducing business operating costs and risks.

[0006] The core of this invention is to design a fully functional AI middle platform and a self-evolving intelligent financial application platform to realize the in-depth application of AI in consumer financial services. The main technical solutions of this invention include the following aspects:

[0007] 2.1 AI Middle Platform

[0008] As a bridge between intelligent applications and underlying AI technologies, the AI ​​middle platform provides a number of AI capabilities and services to support the intelligent upgrade of consumer finance business.

[0009] Multimodal data processing module: This module can process various types of data such as text, images, videos, etc. It uses natural language processing (NLP) technology to understand and process text information, and adopts optical character recognition (OCR) technology to recognize text information in images, realize intelligent understanding and processing of multimodal data, and provide comprehensive data support for the business.

[0010] AI model management module: This module supports model training, management and self-training functions. Through automated training and optimization mechanisms, it enables rapid iteration and accuracy improvement of AI models to meet the needs of different businesses in consumer finance scenarios.

[0011] Intelligent labeling and sample management module: Through intelligent labeling tools and sample management functions, it helps business personnel to efficiently label and manage data. This module can simplify the data labeling process, ensure the quality of data samples, provide high-quality training data for AI models, and improve the training efficiency and accuracy of the model.

[0012] Reasoning module: supports online reasoning and offline reasoning. Online reasoning is suitable for scenarios with high timeliness requirements such as real-time risk control and customer service, while offline reasoning is suitable for scenarios such as batch data processing and model testing, providing flexible reasoning modes to adapt to different business needs.

[0013] Platform management module: This module provides multiple functions such as tenant management, algorithm management, metadata management, data statistics, monitoring and early warning. Through cloud computing and big data technology, it realizes elastic expansion of resources, real-time monitoring of data, and flexible configuration of algorithms, ensuring efficient utilization and stable operation of the AI ​​middle platform.

[0014] 2.2 Self-evolving smart financial application platform

[0015] With the "AI brain" as its core, the platform integrates modules such as data introduction, feature engineering, model training, model management and model application to provide one-stop AI full life cycle management services to meet the intelligent needs of consumer finance business.

[0016] Intelligent interaction: The platform supports a variety of intelligent interaction functions such as call center, intelligent dialogue, voice customer service, etc. Through NLP and speech recognition technology, it realizes natural human-computer interaction and provides customers with a convenient service experience.

[0017] Intelligent supervision: Through real-time monitoring and analysis of business data, the platform can promptly identify potential risk points, support intelligent supervision functions such as counter-attack, intelligent marketing, and intelligent asset management, and improve business security and compliance.

[0018] Smart Credit: This function supports intelligent risk control and credit approval, and uses machine learning algorithms and big data analysis technology to accurately assess customers' credit status and repayment ability, thereby reducing credit risks.

[0019] AI full life cycle management: including complete management processes such as data labeling, feature classification, model training, model management, and application development. Through automated modeling and model import and export functions, model iteration can be quickly achieved to improve AI application efficiency.

[0020] 2.3 Digital Human Resources System Based on RPA

[0021] RPA (Robotic Process Automation) technology is used in the present invention to realize the automation and intelligence of consumer finance business processes, reduce manual burden and improve operational efficiency.

[0022] Document processing automation: RPA technology combined with OCR can automatically identify and extract key information from documents, such as invoices and receipts, and achieve rapid archiving and retrieval, greatly improving document processing efficiency and reducing human errors.

[0023] Business process automation: RPA simulates manual operation processes to automate business processes such as data entry, report generation, and email sending, reducing manual intervention and improving business consistency and efficiency.

[0024] Human-machine interaction and collaboration: The combination of RPA and NLP technology enables RPA to understand and execute natural language commands, realizing human-machine collaboration. For example, through the combination of conversational robots and RPA, users can complete complex tasks through natural language interaction, improving user experience.

[0025] Beneficial Effects

[0026] The combination of the AI ​​middle platform and the smart financial application platform of the present invention can effectively solve the intelligent problems existing in the field of consumer finance and bring the following significant effects:

[0027] Significant improvement in business efficiency: Through automated data processing, model management, and reasoning services, the present invention can greatly improve the processing speed and accuracy of business processes.

[0028] Significant reduction in operating costs: Intelligent data labeling and sample management, flexible reasoning mode selection, and automated business processes effectively reduce labor costs and operating costs.

[0029] The service experience is significantly improved: the intelligent interaction function provides a more natural and convenient user experience, which can quickly respond to customer needs and improve customer satisfaction.

[0030] Enhanced risk management capabilities: Smart supervision and smart credit functions enable real-time monitoring and analysis of potential risks, improve the accuracy of risk identification, and reduce credit risks.

[0031] Efficient resource utilization: The use of heterogeneous computing power and cloud computing technology ensures efficient training and reasoning of AI models and makes full use of resources.

[0032] To sum up, the present invention provides a complete, intelligent and automated business processing solution for the consumer finance industry through the organic combination of AI middle platform, self-evolving smart financial application platform and RPA technology, realizes the organic integration of business intelligence and process automation, improves business processing efficiency, and enhances the market competitiveness of enterprises. BRIEF DESCRIPTION OF THE DRAWINGS

[0033] In order to more clearly illustrate the technical solutions in the present invention or the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings in the following description are only for the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0034] Figure 1 This is a schematic diagram of the module composition of the AI ​​middle station solution of an embodiment of the present invention;

[0035] Figure 2 A schematic diagram of a specific implementation of the business application and technical support services of an embodiment of the present invention;

[0036] Figure 3 This is a schematic diagram of the architecture design of the AI ​​middle station in an embodiment of the present invention;

[0037] Figure 4 This is a schematic diagram of the application value of RPA in the automation of consumer finance business processes according to an embodiment of the present invention. DETAILED DESCRIPTION

[0038] The present invention is described in detail below in conjunction with the accompanying drawings and specific embodiments. At the same time, it is explained here that in order to make the embodiments more detailed, the following embodiments are the best and preferred embodiments, and those skilled in the art may also adopt other alternatives to implement some known technologies; and the accompanying drawings are only for more specific description of the embodiments, and are not intended to specifically limit the present invention.

[0039] It should be noted that the references to "one embodiment", "an embodiment", "an exemplary embodiment", "some embodiments" and the like in the specification indicate that the embodiments described may include specific features, structures or characteristics, but not every embodiment may include the specific features, structures or characteristics. In addition, when a specific feature, structure or characteristic is described in conjunction with an embodiment, it should be within the knowledge of a person skilled in the art to implement such feature, structure or characteristic in conjunction with other embodiments (whether or not explicitly described).

[0040] In general, a term can be understood, at least in part, from its use in context. For example, depending, at least in part, on the context, the term "one or more" as used herein can be used to describe any feature, structure, or characteristic in the singular sense, or can be used to describe a combination of features, structures, or characteristics in the plural sense. Additionally, the term "based on" can be understood as not necessarily intended to convey an exclusive set of factors, but can instead, depending, at least in part, on the context, allow for the presence of other factors that are not necessarily explicitly described.

[0041] The present invention relates to a solution for building an artificial intelligence base for consumer finance, which aims to achieve intelligent upgrading in the field of consumer finance by building an AI middle platform and a self-evolving smart financial application platform. The solution includes multimodal data processing, AI model management, intelligent labeling and sample management, reasoning module, platform management module, and a digital human system based on RPA.

[0042] like Figures 1 to 4 Shown

[0043] 1. AI middle platform

[0044] As a bridge between intelligent applications and underlying AI technologies, the AI ​​middle platform provides a wealth of AI services and supports the intelligent upgrade of consumer finance business. The specific design is as follows:

[0045] 1.1 Multimodal Data Processing Module

[0046] Function description: Supports processing of multimodal data such as text, images, and videos.

[0047] Technical implementation:

[0048] Through natural language processing (NLP) technology, the AI ​​middle platform can understand and process text data, such as customer application information, consultation records, etc.

[0049] Optical character recognition (OCR) technology can identify and extract text information from images, such as identifying information in ID cards and contract texts, further achieving anti-fraud.

[0050] This module achieves a comprehensive understanding of different types of data and provides data support for consumer finance business.

[0051] 1.2 AI Model Management Module

[0052] Function description: Supports the management of AI models, including model training, optimization, and deployment.

[0053] Technical implementation:

[0054] It provides automatic model training function, based on deep learning and machine learning technology, to quickly train and iterate AI models to ensure the accuracy and high performance of the models.

[0055] Configure the model center to facilitate business personnel to manage various models, support the self-training function of the model, and realize personalized model training to meet different application scenarios.

[0056] Support model optimization and continuous iteration through data feedback to improve model efficiency and effectiveness.

[0057] 1.3 Intelligent labeling and sample management module

[0058] Function description: Simplify the data labeling process and improve the quality of model training data.

[0059] Technical implementation:

[0060] Through intelligent labeling tools, business personnel can efficiently label data samples and reduce manual workload.

[0061] Provides sample management functions, supports data sample access, cleaning, labeling, evaluation and other processes, and ensures the quality and diversity of sample data.

[0062] Realize automation and intelligence of sample management to improve the training effect and accuracy of the model.

[0063] 1.4 Reasoning Module

[0064] Function description: Supports online reasoning and offline reasoning to meet different business needs.

[0065] Technical implementation:

[0066] Online reasoning is suitable for business scenarios with high real-time requirements, such as real-time risk control and customer service, and achieves real-time response through an efficient reasoning engine.

[0067] Offline reasoning is suitable for scenarios that do not require real-time response, such as batch data processing and model testing, and improves processing efficiency through distributed computing technology.

[0068] This module provides flexible reasoning mode selection for consumer finance business to meet diverse business needs.

[0069] 1.5 Platform Management Module

[0070] Function description: Responsible for the operation and management of the AI ​​platform to ensure its efficient and stable operation.

[0071] Technical implementation:

[0072] Provides tenant management, algorithm management, metadata management, data statistics, monitoring and early warning and other functions.

[0073] Through cloud computing technology, elastic expansion and optimal utilization of resources can be achieved; combined with big data analysis technology, real-time monitoring and early warning of data can be achieved to ensure business continuity and stability.

[0074] Realize unified management of AI middle-end resources, algorithms, and data to improve the operability and efficiency of the platform.

[0075] 2. Self-evolving smart financial application platform

[0076] The self-evolving smart financial application platform takes the "AI brain" as its core, integrating modules of data processing, feature engineering, model training, model management and model application, providing one-stop AI full life cycle management services to meet the needs of intelligent development in the field of consumer finance.

[0077] 2.1 Platform Design Ideas

[0078] The platform is based on the core architecture of "AI brain" and is built through five links: data introduction, feature engineering, model training, model management, and model application, realizing the management of the entire life cycle of AI.

[0079] 2.2 Core Functions

[0080] Intelligent interaction: supports call centers, intelligent conversations, voice customer service, etc. Through NLP and speech recognition technology, it realizes natural interaction with users and provides a convenient service experience.

[0081] Intelligent supervision: Through real-time monitoring and analysis of business data, it has functions such as anti-attack, intelligent marketing, and intelligent asset management, supporting business risk management and strategy adjustments.

[0082] Smart Credit: Provides smart risk control and credit approval functions for credit business, and uses machine learning algorithms and big data analysis technology to achieve customer credit assessment and repayment ability analysis, thereby reducing credit risks.

[0083] AI full life cycle management: Supports the complete AI life cycle management process from data labeling, feature classification to model training and management.

[0084] 2.3 Technical Implementation

[0085] Heterogeneous computing power layer: adopts a heterogeneous computing power architecture, integrates multiple computing resources such as CPU, FPGA, GPU, NPU, and uses virtualization and container technology to achieve resource optimization and scheduling.

[0086] Data center: responsible for the introduction, storage, processing and analysis of data. It provides high-quality data support for AI models through data preprocessing, feature extraction and enhancement processing.

[0087] AI management platform: As the control center of the platform, it is responsible for model management, application deployment, user / tenant management, log management, etc.

[0088] Operation and maintenance management platform: provides functions such as DAG modeling, monitoring system and alarm management to ensure the stability and reliability of the platform.

[0089] 3. Digital human resource system based on RPA

[0090] In order to further improve the operational efficiency of the enterprise, the present invention also adopts RPA (robotic process automation) technology to build a digital human resource system based on AI.

[0091] 3.1 Document Processing Automation

[0092] Function description: Realize automatic recognition and extraction of documents, and reduce the error rate of manual processing.

[0093] Technical implementation:

[0094] Use OCR technology to identify and extract key information from documents, such as quick reading and archiving of invoices and receipts.

[0095] Through classification and archiving functions, standardized management and rapid retrieval of documents can be achieved.

[0096] 3.2 Business Process Automation

[0097] Function description: Simulate manual operation processes and automate highly repetitive business tasks.

[0098] Technical implementation:

[0099] Define the execution logic of business processes through rule engines and workflow engines to achieve process automation.

[0100] Including data entry, report generation, email sending and other routine tasks, reducing manual intervention and improving business consistency.

[0101] 3.3 Human-computer interaction and collaboration

[0102] Function description: Use NLP technology to enhance RPA's understanding and execution capabilities and achieve human-machine collaboration.

[0103] Technical implementation:

[0104] Through the combination of NLP and RPA, natural language parsing and response can be achieved, allowing users to interact with the system directly through language, improving user experience.

[0105] 4. Main innovations and advantages

[0106] The innovation of this invention lies in multimodal data processing, intelligent labeling and sample management, online / offline reasoning, heterogeneous computing power, RPA automation, etc. By integrating the AI ​​middle platform and the self-evolving smart financial application platform, the full process of consumer financial business can be intelligentized, which greatly improves business efficiency, reduces operational risks and costs, and enhances the market competitiveness of enterprises.

[0107] The present invention covers any substitution, modification, equivalent method and scheme made on the essence and scope of the present invention. In order to make the public have a thorough understanding of the present invention, specific details are described in detail in the following preferred embodiments of the present invention, but those skilled in the art can fully understand the present invention without the description of these details. In addition, in order to avoid unnecessary confusion about the essence of the present invention, well-known methods, processes, procedures, components and circuits are not described in detail.

[0108] The above is only a preferred embodiment of the present invention. It should be pointed out that for ordinary technicians in this technical field, several improvements and modifications can be made without departing from the principle of the present invention. These improvements and modifications should also be regarded as the scope of protection of the present invention.

Claims

1. A solution for building a consumer finance artificial intelligence base, including an AI middle platform, which has a multimodal data processing module, an AI model management module, an intelligent labeling and sample management module, an inference module and a platform management module, characterized in that: The multimodal data processing module can process multimodal data such as text, images, and videos, and uses natural language processing (NLP) and optical character recognition (OCR) technologies to understand and process multimodal data; The AI ​​model management module supports functions such as model training, model center, and self-training, enabling rapid iteration and optimization of AI models; The intelligent labeling and sample management module provides intelligent labeling tools and sample management functions to simplify the data labeling and sample management process; The reasoning module supports both online reasoning and offline reasoning modes to meet the real-time requirements in different business scenarios; The platform management module includes tenant management, algorithm management, metadata management, data statistics, monitoring and early warning and other functions to ensure efficient management and stable operation of the AI ​​middle platform.

2. According to the consumer finance artificial intelligence base construction solution of claim 1, the multimodal data processing module of the AI ​​middle station can support the recognition and extraction of various types of data such as text, images, videos, etc., process text data through NLP technology, and process image data through OCR technology, thereby providing comprehensive data support for consumer finance business.

3. According to the consumer finance artificial intelligence base construction solution of claim 1, the AI ​​model management module includes model automatic training, model management and self-optimization functions, which can achieve continuous optimization and accuracy improvement of the model to adapt to the application needs of different consumer finance scenarios.

4. According to the consumer finance artificial intelligence base construction solution of claim 1, the intelligent labeling and sample management module efficiently labels data samples through intelligent labeling tools, and supports the management of sample access, cleaning, labeling and evaluation processes to improve the efficiency and accuracy of AI model training.

5. According to the consumer finance artificial intelligence base construction solution of claim 1, the online reasoning of the reasoning module is suitable for real-time scenarios such as real-time risk control and customer service, while the offline reasoning is suitable for scenarios such as batch data processing and model testing, so as to flexibly meet the different needs of consumer finance business.

6. According to the consumer finance artificial intelligence base construction solution of claim 1, the platform management module further includes operation and maintenance management functions, which realizes the elastic expansion of AI middle-end resources, flexible configuration of algorithms and real-time monitoring of data through cloud computing and big data technology.

7. The consumer finance artificial intelligence base construction solution according to claim 1 also includes a self-evolving smart financial application platform, which takes the "AI brain" as the core, integrates functional modules such as data introduction, feature engineering, model training, model management and model application, realizes AI full life cycle management, and supports the intelligent development of consumer finance business.

8. According to the consumer finance artificial intelligence base construction solution of claim 7, the self-evolving smart financial application platform supports intelligent interaction functions, including call center, intelligent dialogue, voice customer service, etc., and realizes natural interaction with users through natural language processing and speech recognition technology.

9. According to the consumer finance artificial intelligence base construction plan of claim 7, the self-evolving smart financial application platform has intelligent supervision and intelligent credit functions, and supports intelligent risk control and credit approval of the business through machine learning algorithms and big data analysis technology, thereby reducing credit risks.

10. The consumer finance artificial intelligence base construction solution according to claim 1 further includes a digital human resource system based on RPA (robotic process automation) technology, which is applied to document processing automation and business process automation to improve enterprise operational efficiency and reduce the risk of human errors.

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