澳门金威尼斯游戏(中国)官网·BinG百科

Based on the strategic planning of retail transformation in banking industry, Yusys Technologies has built a bank-level customer label management platform which is oriented to the actual needs of digital marketing, and to provide data guarantee and comprehensive support for customer portrait, customer segmentation, product recommendation, activity planning, cross marketing, and scenario marketing. The customer label management platform has core functions such as label definition, label generation, label library management, label service, and label evaluation, covering the entire life cycle of labels. The platform has a pre-built label library for customers in the financial industry and supports integration with multiple data sources, enabling banks to quickly build a bank-wide label service system to support business requirements and maximize data value.

The customer behavior analysis platform is a system specially designed by Yusys Technologies to analyze user preferences and trends in online banking, mobile banking, direct banking, and other online banking channel systems. The customer behavior analysis platform provides banks with a variety of detailed user behavior analysis reports, predicts user habits, and helps banks to conduct targeted marketing accurately. The platform can collect, analyze, and sort all user behavior data in the banks’ network channel system. These data and statistical analysis provide basic data for the banks’ CRM and big data targeted marketing system, enabling banks to develop more accurate and effective marketing programs.
The customer behavior analysis platform provides log collection, buried point collection, SDK collection, batch collection, and other collection methods, covering multiple channels and multiple device types. It uses behavior information to identify the same customer and provides customer label profile mapping, behavior path analysis, and analysis result push functions to analyze customer behavior, identify labels, and push identification results to subscription channels.

With the development of big data technology and the vent of the internet era, the ability to establish a big data machine learning model accurately and quickly has become critical for the financial industry to improve its competitiveness and operating efficiency. Based on big data distributed computing, the data modeling laboratory uses artificial intelligence method and starts from data features to establish an “integrated” intelligent model platform serving business scenarios for customers. In order to realize the unified development, application and management of machine learning models, a large number of statistics, demonstration, and observation algorithms are designed in the data model laboratory, and several model templates are provided to enable the build business models rapidly. At the same time, the data model laboratory provides a model development and deployment platform to control the entire life cycle of model development, deployment, monitoring, and maintenance. In addition, the web-based drag-and-drop interface of the data model laboratory does not require complicated and redundant codes. Thus, it greatly improves modeling efficiency and provides a visualization platform and customized modeling services, ensuring clear and precise modeling that is easier to explain, demonstrate, and maintain.
Yusys’s data model laboratory has independent and complete visual machine learning modeling capabilities. It supports microservice architecture, enables rapid model deployment, and real-time model monitoring and feedback, which not only increases on-line speed of model and business efficiency of customer, but also meets the model operation monitoring requirements of business personnel and regulatory departments. The data model laboratory maintains Yusys Technologies’ business-based design concept from the customers’ point of view, and is oriented toward preset scenarios for financial services, especially banking. According to the characteristics of each business, the algorithm of the corresponding model is deeply customized, close to the banking business and regulatory requirements, to provide configurable modeling solution, so that the model development can fully meet customer needs.

In order to provide efficient, accurate and comprehensive data analysis and decision-making ability, Yusys Technologies has built a big data intelligent decision-making platform based on financial technology, which utilizes data from within and outside the industry as the benchmark, is guided by rich industry experience, and uses the strategy model as the starting point. The platform focuses on situational applications such as operation decision-making, risk control decision-making, and credit rating decision-making and leverages technologies such as streaming computing and machine learning to achieve millisecond-level decision-making responses and help users achieving real-time business decision-making. The platform can be used for multiple risk control scenarios such as credit cards, new online loans, and traditional credit loan. At the same time, the big data intelligent decision-making platform has a data management center for comprehensive online management and processing integration of real-time streaming data, batch table data, and internal and external interface data. The decision-making flow is used to independently arrange and assemble the rule set, score card, decision table, and other components, so as to realize the whole link risk control ability of access, anti-fraud, scoring, credit granting, and early warning.

Based on the big data architecture, the historical data query platform integrates, archives, stores and centrally manages all historical data of the banks’ various businesses and management systems. It provides online historical data analysis and offline data download functions and provides online APIs and historical data query functions in a page form to the full channel.
The historical data query platform provides historical data query services through real-time API interfaces, custom WEB page query services, and batch export of files. It provides real-time API interface service data, which can be used to quickly configure and publish stable and efficient historical data services online. The platform provides custom WEB page query services, where the query page can be easily configured and customized using drag-and-drop interface, to build online query, audit analysis, and business query of historical data. The platform also provides batch export services of historical data for applications such as data analysis and mining modeling.

Yusys Technologies’ financial data asset modeling is a logical data model for enterprise-level data warehouses, data platforms, and data centers. It adopts a business-oriented approach and is guided by multi-dimensional model design principles to effectively organize various business data from diverse sources. At the same time, it can fully reflect banks’ complex business rules and support a large number of analysis applications. This product uses a unified logical language to describe the banking business, and provides strong support for data analysis. Meanwhile, it also ensures data consistency, which is an important foundation for business intelligence. In order to meet different business requirements, the Yusys financial data asset model has realized highly abstractness, structure, and modulation. As the basis of the underlying data platform, the data model must maintain a unified business definition during the design process, such as channel dimension definition, customer dimension definition, and classification. To unify the business definition of the entire model, Yusys Technologies combines the characteristics of financial services to generate a unified abstraction and definition, so that the entire model can be consistent within the enterprise.

Yusys Technologies’ external data management platform is dedicated to helping banks manage data beyond their own business operations. As banks rely on external data in marketing, risk control, credit management, and customer life cycle management, they need to import data from multiple external channels, conduct multi-dimensional customer information data collection, analysis, and standardized integration, and achieve effective integration of internal and external data information management platforms. Yusys' external data management platform realizes the sharing and application of data across the bank by providing unified external data service capabilities within the bank, and establishes centralized and unified management of massive data, thereby providing effective support for business operation and analysis, and solves problems such as information asymmetry and limited data acquisition ability.

Yusys Technologies’ real-time computing platform is a financial technology innovation. It is a full-link real-time big data analysis platform based on the Apache Flink stream computing framework. The platform can asynchronously adapt to multi-source and multi-type data, to enable multi-source data collection and integration. It also supports full-stack analysis capability for batch-flow integration, provides visual job configuration, and simplifies the complexity of data development under BI scenarios. At the same time, the real-time computing platform is based on the distributed architecture of the big data ecology technology to achieve high efficiency and accuracy of data analysis and millisecond-level delay, so that to meet the timeliness requirements of data decision-making, while providing multiple data service interfaces that serve the commonality of streaming data based on various application scenarios. Yusys can fully assist real-time transformation of enterprises through the real-time computing platform, and truly implement the business development goals of financial technology empowerment. It supports various application scenarios: real-time data warehouse, real-time data platform, real-time reports, real-time large screen, real-time management and driving, and real-time operation and maintenance analysis.

The purpose of the data development management platform is for "management to enable data, and data to enable business". It relies on data standards, data dictionaries, and data indicators to build standard enterprise-level data models, and uses flexible data development methods to provide customers with high-quality and convenient data development and usage experience. It is a key product to realize DataOps in the data platform system.
The data development platform manages the entire data development process through data work orders, including creating data models, data development, reviewing operation content and testing environment verification, and verifying relevant data models and model mappings in the testing environment. At the same time, after the test is passed, the system generates and launches a script file, and uploads the script file to run in the production environment to achieve the final data development purpose.

The intelligent data exchange platform enables the integration of decentralized application information systems and realizes information exchange through the technology of big data ecosystem. By establishing a central database, this platform integrates data extraction, concentration, loading, and presentation, and enables unified data processing and exchange for customers to ensure the interconnection and interoperability of various heterogeneous systems. At the same time, the intelligent data exchange platform provides several application subsystems for unified transmission and sharing of information and data, thereby improving the utilization rate of information resources, and ultimately achieving the basic goal of information system development.