HUA XIA BANK(SH:600015) Zheng Quan Ri Bao·2025-08-27 16:13Core Viewpoint - The banking industry is experiencing a significant increase in the transfer of personal credit card non-performing loans (NPLs), with a notable rise in both the scale and discount rates of these transfers since 2025 [1][2]. Group 1: Transfer Details - Huaxia Bank is publicly transferring seven batches of personal NPLs related to credit card overdrafts, with a total outstanding principal of 4.483 billion yuan and total outstanding interest of 6.305 billion yuan, amounting to a total of 10.789 billion yuan [2]. - The starting price for these transfers is set at 245 million yuan, which is approximately 0.23% of the total outstanding principal and interest [2]. - Since 2025, multiple banks have accelerated the transfer of personal credit card NPLs, with several projects exceeding 10 billion yuan and starting prices significantly discounted, some as low as 0.2% of the total amount [2]. Group 2: Market Trends - The first quarter of 2025 saw a transaction volume of 37.04 billion yuan for personal NPL transfers, a more than sevenfold increase from 4.3 billion yuan in the same period last year, with credit card overdraft NPLs accounting for 5.19 billion yuan [2]. - The trend indicates a shift in the banking sector towards more aggressive management of credit card risks, reflecting a broader industry transition from "incremental expansion" to "stock management" [4]. Group 3: Expert Insights - Experts suggest that the low discount rates for some credit card NPL transfers are driven by poor asset recovery expectations and the time value of money, as banks face challenges in recovering debts from borrowers with weak credit profiles [3]. - The current wave of NPL transfers highlights the core issues in credit card business practices, including over-reliance on new customer acquisition, weak risk control, and low collection efficiency [4]. - Banks are exploring diverse strategies to enhance NPL recovery efficiency, including asset securitization, debt restructuring, AI-enabled collections, and cross-border transfers [5].