Qfin Holdings, Inc.

Ladies and gentlemen, thank you for standing by and welcome to the Kewfin Holdings First Quarter 2026 Earnings Conference Call. All participants are in a listen-only mode. There will be a presentation followed by a question and answer session. If you wish to ask a question, you will need to press the star key followed by the number 1 on your telephone keypad. Please also note today's event is being recorded. At this time, I'd like to turn the conference over to Ms. Karen Gee, Senior Director of Capital Markets. Please go ahead, Karen.

Thank you, Darcy. Hello, everyone, and welcome to Kingston Holdings' first quarter 2026 earnings conference call. Our earnings release was distributed earlier today and is available on our IR website. Joining me today are Mr. Wu Haisheng, our CEO, Mr. Alex Xu, our CFO, and Mr. Zheng Yan, our CIO. Now I will quickly cover the safe harbor statement. Today's discussions may contain forward-looking statements, particularly statements about our business and financial results that are subject to risks and uncertainties, which could cause actual results to differ materially from those contained in the forward-looking statements. please refer to the Safe Harbor Statement in our earnings release, which also contains a reconciliation of the non-GAAP financial measures to GAAP financial measures. Now I will turn the call over to Mr. Wu Haisheng. Please go ahead.

Hello, everyone. Thank you for joining us today. Since April 2025, China's consumer credit industry has undergone profound structural adjustments under regulatory guidance. Entering Q1 this year, demand for consumer credit remained soft and asset quality faced broad-based pressure. Household short-term consumer loan balances declined for the fifth consecutive quarter, decreasing by approximately RMB $470 billion, or 5% sequentially, In this challenging industry environment, we have upheld compliance, prudence, and high quality as the core principles of our operations. Rather than pursuing scale, we proactively optimized our user and asset mix to strengthen overall health and long-term resilience of our business. Building on the proactive measures we implemented in the second half of last year to enhance risk management and business operations, we delivered a resilient performance in Q1 with notable improvements in risk indicators and operation efficiency. As of the end of Q1, our AI-powered credit decision engine and asset distribution platform served 167 financial institutions delivering intelligent digital credit services to over 64 million credit line users on a cumulative basis. In Q1, we maintained rigorous risk standards against the backdrop of a softening retail credit market. As a result, total loan facilitation and origination volume on our platform declined by approximately 7.5% sequentially to RMB $65 billion. Non-GAAP net income declined by 11.6% sequentially to approximately RMB 950 million, while non-GAAP EPADS on a fully diluted basis decreased by 6.4% to RMB 7.70. Excluding run-off items, take rate improved sequentially. In the second half of 2025, We continuously tightened risk policies, and this forward-looking strategy began to translate into tangible results in Q1. During the quarter, we further iterated and optimized our underlying risk capabilities across the entire credit life cycle. As a result, our SPD-7, a leading risk indicator for new loans, declined by approximately 20% in Q1 compared with Q4 last year. As legacy loans continue to run off, portfolio-level risk metrics also improved month over month. By March, C2M2 ratio, the risk indicator that measures the outstanding delinquency rate after 30 days of collection, returned to levels seen in July. and August 2025. For the quarter as a whole, C2M2 ratio decreased by roughly 17%, sequentially to 0.8%, largely achieving our risk optimization targets. Specifically, these improvements were driven by the following initiatives. In the pre-loan and in-loan stages, we further strengthened our ability to identify high-quality customers while proactively screening out higher risk segments. In the pre-loan stage, we upgraded the income and drawdown prediction models in our application scorecard, or A scorecard, to more accurately assess user income and borrowing intent, which enabled us to serve more high-quality users. In the in-loan stage, we further refined our behavior scorecard, or B scorecard, enabling targeted strategies such as credit line adjustments, rate reductions, and flexible repayment options for high-quality borrowers. We also continuously updated our risk models to capture potential risk exposures. For example, when previously low-risk borrowers experience income fluctuations or take on multiple loans, Our system could quickly detect these changes and proactively mitigate risk by reducing credit lines or raising approval thresholds. As a result of these efforts, average FPD7 for loans issued between January and March declined by approximately 5% compared to that in December last year, which provides a solid safety cushion against potential market volatility. In the post-loan stage, we continue to optimize our collection strategies during the quarter. Since January, our day-one delinquency rate has shown an overall downward trend, with the Q1 rate decreasing by roughly 7%, sequentially easing pressure on our collection front. Against this backdrop, we scaled back less cost-effective collection efforts and improved the efficiency of our resource allocations. At the same time, we upgraded the capabilities of our collection scorecard or C-Scorecard by incorporating new features that reflect recent market conditions and shifts in user behavior. This enabled us to differentiate users more accurately by risk level and repayment willingness and to match each segment with the most appropriate collection approach. Through these efforts, we were able to manage risk while optimizing costs, effectively enhancing our collection efficiency. Together, these measures contributed to a steady month-over-month improvement in our 30-day collection rate during the quarter, with a quarterly average of 85.8%, up 1.8 percentage points sequentially. On the customer acquisition front, we maintained a disciplined approach, continuously optimizing acquisition channels and improving efficiency. In Q1, our overall acquisition costs fell by approximately 17% sequentially, with unit acquisition costs remaining largely stable compared to Q4. In parallel, we strategically increased marketing spending on high quality users to further refine our user mix and build a pipeline of high quality assets. In Q1, spending on this segment increased by approximately 40% sequentially. High quality users tend to carry much lower risk than regular segments with higher utilization, steadier long-term demand, and more repeat borrowing. This shift in our user mix will strengthen our portfolio quality and build a more resilient and sustainable mode for our business. Meanwhile, we substantially cut back on underperforming channels within the embedded finance model, helping to improve the risk and return profile of new users. On the funding front, the industry continued to face liquidity pressure during the quarter. By further increasing the proportion of ABS in our funding mix, we were able to reduce funding costs by approximately 10 basis points sequentially. In Q1, ABS issuance totaled RMB 2.9 billion, up 16% from the prior quarter. For the remainder of the year, we will align the pace of our ABS issuance with unbalanced sheet loan origination to maximize capital efficiency. Since April, as industry adjustments continue, liquidity in the funding market has also tightened. To navigate the periodic market volatility, we will continue to optimize our funding structure and diversify our partnership with financial institutions to ensure sufficient funding supply in a volatile market while striving to keep our overall funding costs stable. Turning to our tech solutions business, we have continued to deepen collaboration with financial institutions and actively cultivate our enterprise-facing technology offerings as another long-term strategic pillar, supporting banks in serving customer segments priced between 3% and 12%. At this stage, we are focused on validating these capabilities at scale which will lay a solid foundation for long-term commercialization opportunities ahead. In Q1, loan volumes empowered by our tech solutions business reached RMB 9.96 billion, representing seven-fold year-over-year growth. This demonstrates that our tech-driven capital light model is steadily gaining industry recognition and being validated across multiple use cases. Our credit-focused AI agents have also entered initial commercial deployment. For example, one of our core AI agents, AI Loan Officer, is being deployed at a city commercial bank covering its retail, SME, and corporate business lines. With our Focus Pro credit solution, we help banks serve small businesses and individual customers more efficiently by applying digital and intelligent tools across their full credit lifecycle. From customer acquisition and the risk of profiling to day-to-day operations. This not only expands the scope of our business, but also reflects our commitment to supporting the real economy and promoting financial inclusion. At the technology foundation level, we set a more ambitious long-term goal to fully transform the company into an AI-native organization. Central to this strategy is deep knowledge modeling. We are converting all historical documents, strategy libraries, and operational experience into structured context for large language models, creating a truly queryable knowledge base. With this foundation, departments across risk management, product, design, marketing, and engineering can integrate AI into their core operations. This not only provides assistance in day-to-day work, but also fundamentally enhances the professional competence, decision-making quality, and professional boundaries of personnel across all departments. Cost savings and efficiency enhancements, often highlighted by the market, will be a natural byproduct of this evolution toward an AI-native organization. For example, AI coding tools have achieved impressive adoption across our engineering teams. As of May, 98.4% of technical personnel were using AI tokens. with key roles consuming tens of millions of tokens per person per day. This indicates that AI adoption within our engineering has reached penetration levels comparable to those at top-tier internet companies in China. Token usage has also shown a clear correlation with productivity gains. Looking ahead, we will steadily extend this AI leverage to more business scenarios, accelerating our evolution into an AI-native organization. As we continue to strengthen our core domestic business, we are also accelerating overseas expansion while carefully managing risk along the way. In Q1, we successfully launched operations in a new emerging market and continued to fortify local teams and refine risk models in the market where we are already active. Leveraging our combined strengths in global capital, advanced technology and local operational expertise, we aim to build a robust international presence, expanding efficiently and operating safely across multiple markets. Looking ahead, as the industry continues to adjust and restructure, we expect short-term uncertainties to persist. That said, The ongoing shakeout is creating a more structured and efficient market environment, offering a prime opportunity for industry leaders to strengthen and consolidate their positions. We remain committed to our one coal, two wings strategy with our domestic credit business as the coal and tech solutions, commercialization and overseas expansion as the two wings driving sustainable high-quality growth over the long term. Thank you. With that, I will now turn the call over to Alex.