创业黑马：版信通业务有望带动公司业绩增长，AI帮助公司主业降本增效

Investment Rating - The investment rating for the company is "Buy" (maintained) [1] Core Views - The acquisition of Banxintong is expected to drive revenue growth for the company, with AI helping to reduce costs and improve efficiency in its main business [7] - The company is actively following the AI trend and accelerating the AI transformation process for small and medium-sized enterprises, which presents significant future growth potential [7] - The financial forecasts for the company have been adjusted, with expected net profits for 2024-2026 revised to -61 million, 63 million, and 89 million RMB respectively, indicating a strong recovery trajectory [7] Financial Summary - Total revenue for 2022 was 347.12 million RMB, with a projected decline to 236.29 million RMB in 2024, followed by a rebound to 502 million RMB by 2026 [1] - The net profit attributable to the parent company is expected to improve from -83.31 million RMB in 2022 to 88.86 million RMB in 2026, reflecting a significant recovery [1] - The latest diluted EPS is projected to be -0.36 RMB in 2024, improving to 0.53 RMB by 2026 [1] - The company's P/E ratio is expected to be -76.81 in 2024 and 52.57 in 2026, indicating a transition from losses to profitability [1] Market Data - The closing price of the stock is 27.91 RMB, with a market capitalization of approximately 4.67 billion RMB [5] - The company has a price-to-book ratio of 9.62 and a total circulating A-share market value of 3.96 billion RMB [5][6] Business Model and Growth Potential - Banxintong's business model leverages blockchain technology for efficient copyright registration, which is expected to yield high profit margins due to its asset-light operation [7] - Future growth opportunities are identified in the re-certification of apps for Huawei's HarmonyOS and the registration of AI intelligent agents, which are anticipated to have a larger market than traditional app certification [7] - Collaborations with ByteDance's Volcano Engine are aimed at enhancing service efficiency and reducing labor costs, facilitating a shift from traditional labor-intensive services to digital and intelligent services [7]