Core Viewpoint - The article highlights the innovative use of big data and artificial intelligence in combating economic crimes in Shanghai, showcasing the development of the "full-scenario fund analysis intelligent system" by Gong Chen, which significantly enhances the efficiency of financial crime investigations [1][4]. Group 1: Development of Technology - Gong Chen initiated self-learning in programming to address inefficiencies in financial data analysis, leading to the creation of a "fund data cleaning tool" that reduced analysis time from 7 days to 4 days [3]. - The tool evolved into the "full-scenario fund analysis intelligent system," which further decreased analysis time to just 30 seconds, earning recognition in a national police technology innovation competition [3][4]. Group 2: Risk Management - The "enterprise risk warning model" was developed to identify potential risks among over 3 million businesses in Shanghai, transitioning from reactive crime fighting to proactive risk management [5]. - The model successfully issued a warning about a 54.41% increase in "one-day fake" shell companies, allowing for early intervention and a 98.6% reduction in the monthly growth of such companies [5]. Group 3: Specific Case Studies - The model was optimized to address scams targeting the elderly, leading to the identification of a company involved in a deceptive investment scheme that affected thousands of investors [7]. - Quick action by law enforcement, based on model predictions, prevented the transfer of illicit funds and resulted in the closure of high-risk enterprises, achieving an over 80% risk blockage rate [7].

Core Viewpoint - The Shanghai Public Security Bureau has significantly enhanced its law enforcement capabilities through a new policing model that integrates "professionalism, mechanisms, and big data," contributing to the city's high-quality development and public safety [1][2]. Group 1: Public Safety and Crime Prevention - In 2025, Shanghai police discovered over 700 shell companies involved in fraudulent VAT invoicing through collaboration with tax authorities and risk warning models, significantly improving proactive intervention times [2]. - The city has implemented over 7,400 data models to predict and mitigate risks, resulting in a 13.7% year-on-year decrease in criminal cases [2]. - The police have successfully prevented losses of 5.14 billion yuan by warning 620,000 potential scam victims, with a decrease in both the number of completed and reported telecom fraud cases by 8.6% and 8.4%, respectively [3]. Group 2: Traffic Management and Law Enforcement - Shanghai's traffic management has seen a 12.9% increase in average vehicle speed at 360 intersections due to the introduction of a "traffic congestion model," leading to a reduction in traffic accidents and fatalities by 2.7% and 7%, respectively [3]. - The city has adopted a "textbook-style" law enforcement approach, promoting adherence to traffic laws and resulting in a consistent decline in traffic incidents [3]. Group 3: Drone Regulation and Community Safety - The police have launched initiatives to regulate drone usage, resulting in a 34.4% increase in registered drone operators and a 44.9% rise in registered drones [4]. - The Shanghai police have resolved over 1.19 million conflicts and assisted more than 1,200 troubled youths, enhancing community safety and addressing grassroots issues [4]. Group 4: Business Support and Legal Services - During the 8th China International Import Expo, the Shanghai police established "Blue Whale" service points to provide legal advice and dispute resolution for participating businesses, aiming to create a supportive business environment [5]. - The police have resolved over 130 business-related disputes and investigated more than 2,200 cases of intellectual property infringement, preventing losses exceeding 10 billion yuan for enterprises [5]. - The implementation of streamlined approval processes for large events has led to a 33.9% increase in the number of events held, while reducing application materials by 70% and approval times by 60% [5].