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.

Thank you, Haisheng. Good morning and good evening, everyone. Welcome to our first quarter earnings call. There was another quarter of challenging micro-condition and timing regulatory scrutiny, which caused further changes in industry landscape and the participants' behavior. We continue to focus on mitigate risks, improve efficiency, and reduce costs under such micro headwinds. Total net revenue for Q1 was $3.91 billion versus $4.09 billion in Q4 and $4.69 billion a year ago. Revenue from credit union service capital heavy was $2.96 billion in Q1, compared to $3.43 billion in Q4 and $3.11 billion a year ago. The year-on-year decline was mainly due to a decrease in off-balance sheet loan volume, more than offsetting the increase in on-balance sheet loans. The sequential decline was due to lower overall capital heavy loans, as well as a decrease in average pricing of the loans. Overall funding costs declined roughly 10 basis points Q1Q, as we further optimized the funding mix with increased percentage contribution from ABS in Q1. Revenue from platform service, Capital Light, was $951.9 million in Q1 compared to $660 million in Q4 and $1.58 billion a year ago. The year-on-year decline was mainly due to significantly lower ICE contributions in response to the regulatory changes. The sequential increase was mainly due to better ICE take rate due to improved risks. During the quarter, average IRR of the loans we originated and or facilitated was 18.7% compared to 19.5% in prior quarter. As we continue to focus on attracting high quality users in the coming quarter, looking forward, we may see modest fluctuation in average pricing under current regulatory framework. Sales and marketing expenses declined 17% Q on Q and 23% year on year. We added approximately 1.19 million new credit line users in Q1 versus 1.45 million in Q4. We took more cautious view in customer acquisition and will continue to maintain controlled pace to acquire new users in the near term in response to the changing regulatory direction and still uncertain micro condition. 90-day delinquency rate was 3.5% in Q1 compared to 2.71% in Q4, which reflects the elevated risk level near the end of 2025. Here, 90-day delinquency rates is a lagging indicator, and internally is not a metric we care much about. Day 1 delinquency rate was 5.7% in Q1 versus 6.1% in Q4. 30-day collection rate was 85.8% in Q1 versus 84.1% in Q4. C-M2, which represents the outstanding delinquency rate after 30 days collection, was 0.8% in Q1 versus 0.97% in Q4. The noticeable risk improvement in Q1 was mainly related to our risk-pending measures and loan makeshift toward new loans, and we saw continued modest improvement in the overall risk performance in recent months. Given current micro-conditions, and regulatory changes, we continue to take prudent approach in booking provisions against potential credit losses. Total new provisions for risk-bearing loans in Q1 were approximately $1.68 billion versus $1.92 billion in Q4. The decline in new provision was mainly due to lower risk-bearing loan volume, partially offsetting by increased provision booking ratio. despite improved new loan risks Q1Q. Writebacks of previous provision were approximately $308 million in Q1 versus $274 million in Q4. Provision coverage ratio, which is defined as total outstanding provision divided by total outstanding delinquent risk-bearing loan balance between 90 and 180 days, was 391% in Q1. compared to 481% in Q4. The temporary decline in provision coverage ratio was mainly due to higher risk level in Q4 driving up the delinquent risk-bearing loan balance between 90 and 180 days in Q1. As total outstanding provision were largely unchanged Q and Q. Non-GAAP net profit was 946 million in Q1 compared to $1.07 billion in Q4 and $1.93 billion a year ago. The significant year-on-year decline in profitability was mainly due to lower loan volume and lower pricing, higher credit costs, and deleveraging in operations. Non-GAAP net income per fully diluted ATS was 7.7 RMB in Q1 compared to 8.23 in Q4. Effective tax rate for Q1 was 21.6% compared to our typical ETR of approximately 15%. The higher than normal ETR was mainly due to withholding tax on dividend distribution from onshore to offshore and more prudent tax provision under tightened tax regulatory scrutiny. Leverage ratio, which is defined as risk-bearing loan balance divided by shareholders' equity, was 2.4 times in Q1 versus 2.7 times in Q4 due to lower risk-bearing loan balance. We expect to see leverage ratio fluctuate around this level in the near future. We generated approximately $2.1 billion cash from operation in Q1 compared to $3.15 billion in Q4. Total cash and cash equivalent and short-term investment was $10.79 billion in Q1 compared to $10.72 billion in Q4. In Q1, we continued to buy back our outstanding CBs. As of May 26, 2026, the company had repurchased approximately US$577 million in aggregate principal amount of the CBs. for US$502 million in cash on the open market and in off-market privately negotiated transactions. Approximately US$113 million in aggregate principal amount of the CBE remained outstanding. The repurchase of the CBE allowed us to reduce our long-term debt obligation and associate interest payment at favorable terms, potentially strengthening our financial positions and flexibility. We will continue to optimize our actual allocation strategy to reflect the changing micro dynamic to support business initiatives and to return to shareholders. As we maintain a progressive DPS dividend policy, we may start to opportunistically look into an entry point to resume share repurchase, even though micro and the regulatory environment is still uncertain and unsettled. Finally, regarding our business outlook, While we are encouraged by the noticeable improvement in risk metrics, micro uncertainty and the regulatory pressure will likely persist in the near future. We will continue to take cautious approach in business planning for 2026 and focus on risk control, efficiency improvement, and cost cutting. For the second quarter of 2026, the company expects to generate non-GAAP net income between RMB 900 million and RMB 980 million, representing a year-on-year decline between 47% and 51%. This outlook reflects the company's current and preliminary view, which is subject to material changes. With that, I would like to conclude our prepared remarks. Operator, we can now take some questions.

Thank you. If you wish to ask a question, please press star 1 on your telephone and wait for your name to be announced. If you wish to cancel your request, please press star 2. If you're using a speakerphone, please pick up the handset to ask your question. For those who can speak Chinese, please start your question in Chinese followed by English translation. To allow enough time to address everyone on the call, please keep it to one question and one follow-up and return to the queue if you have further questions. Thank you. Your first question, it comes from Richard Zhu with Morgan Stanley.

Please go ahead. Thank you, Mr. Hai. Thank you for the detailed introduction. I have two questions I would like to ask. We see that the average price of this quarter still maintains a downward trend. It is still a little different from the relatively stable price strategy of the same year. I would like to ask some reasons and thoughts behind us. Then, looking at this year's speed, Two questions for me. Just, you know, observing the average pricing of the loans, it continues a downward trend. Rather than to relatively stable pricing at the peers, what was the rationale and thinking behind that? And also, where the average loan pricing will eventually settle later this year? And also, based on the current business model, what's the average demand as well as business scale going forward and how that will impact shareholder returns? Thank you. Okay. Thank you, Richard. Let me take your first question, and Alex may maybe take a second one. In terms of pricing, first, as we're currently in this kind of cycle, lower financing costs help improve the household balance sheet and unlock healthy consumption demand. And as we mentioned before, this is overall positive for the industry as it is accelerating market consolidation. Long-term platforms that relied on high prices to cover high risk and aggressively grow their market shares in the past will eventually exit the market. At the same time, this set a higher bar for the market participants. Over the longer term, companies with more precise user profiling and better risk-based pricing capabilities are likely to take the market shares. With this in mind, we proactively adopted targeted pricing to optimize our user mix. Since Q4 last year, we have put more efforts to acquire high-quality users. This quarter, Our spending on that segment was up by about 40% sequentially. As a result, the share of high-quality users in our new customer loan volume jumped 25 percentage points from Q3. At the same time, we also optimized pricing for our existing users with better RIF type profile. By giving them more competitive offers, we intended to increase their stickiness on our platform. In addition, we also expanded their volume capabilities reasonably to help build a stable long-term LTV. As a result of these efforts, our average pricing was down 80 basis points sequentially. Based on our observations so far, high quality users tend to carry lower risk than regular segments. With higher utilization, more repeat volume set your long-term demand and therefore much healthier LTV. Going forward, we will continue iterating our models to better identify high-quality users, improve risk performance, and using flexible pricing strategies. together with a great user experience to drive retention and repeat borrowing. All of this will further improve LTV for this segment. Strengthening our capabilities to serve high-quality users is a long-term play. In the short term, it requires investment, but in substance, it's a trade-off between near-term profit and long-term sustainable value. By building these capabilities, We are also reshaping our business model, making it a healthier and better position to navigate a more complex and fast-changing market environment. On our look of pricing, first we increased our investment in opposition and conversion rate of high-quality users starting in June for last year. Over the past two quarters, we have seen a step-changing increase in share of high-quality customer segments in total volume, with pricing trends moving in the same direction. As a result, our pricing has declined by 2.2 percentage points over this period. Going forward, we expect to maintain a relatively steady pace on acquisition and offer strategy. As the user lifecycle continues to evolve, our mix will gradually shift to higher quality users. Meanwhile, we will continue to optimize pricing strategy for high quality users and regular users, so as to strike a balance between risk and profit. Over the longer term, we will remain flexible and but just our pricing strategy based on regulatory and market change. At the same time, we will continue to improve our risk model and operational efficiency to strengthen profitability.

Okay, Rich, I will take the second part of your question. So I think the landscape changing of the consumer finance industry is still ongoing, and the near-term macro and the regulatory environments remain pretty complicated. On our side, we are actively adjusting our SMNICs and exploring ways to diversify our business. Market demand is always there, and as we keep upgrading our capability in serving high-quality users, we are confident that in our ability to meet more credit need over time. However, at this stage, I would say our focus probably remains about the healthy and sustainability of the business as opposed to the scale of the business. In terms of shareholder returns, our balance sheet is still pretty robust, and we have strong capital base to support both the business growth and the shareholder returns. At the same time, our business continues to generate substantial profit and healthy positive cash flow which steadily build up our capital base. Both dividend and the buybacks are considered as options for us. At this stage, we see dividend as a way to give shareholders certainty in an uncertain environment. And assuming that the stable regulatory environment, we will maintain a progressive DPS policy and achieving this through flexible adjustment to the dividend payout ratio. On the buyback side, we believe our current valuation is very attractive, obviously, and our net assets far exceed our market cap. And we have strong conviction in our intrinsic value. Although there is still uncertainty around the micro and regulatory environment, and our business model continues to evolve, we believe shared buyback once again, becomes a viable option for shareholder returns at this junction. Thank you.

Thank you. Your next question comes from Alec Yu, DBS. Please go ahead. Pardon me, Alex. Your line may be muted. Okay.

So my question is regarding the long growth outlook. So given the sterilization of quality and we have already shifted our custom mix toward higher quality customers. So when do we expect the company to increase its risk appetite a little bit and shall we expect long volume to return to some sequential growth in the coming quarters?

Thank you. Okay. Thank you. First, The structural change we have made to risk management and our user mix have delivered clear results. In the second half of 2025, we have implemented a series of risk-catching measures, significantly reallocating resources toward the acquisition and engagement of high-quality users. These initiatives have led to a market market improvement in both of our asset structure and asset quality. Improvement. Our risk metrics improved month by month. C2M2 ratio in March has returned to levels seen in July and August of last year. In April and May, C2M2 ratio stayed stable and continues to improve marginally. While keeping risk stable and improving, we're also exploring structural growth opportunities. For example, for customers with a solid safety margin based on our risk models, we dynamically adjusted our approval and credit line rules. Within a safe range, we improved our conversion rate and effectively served more credit demands. We're also optimizing our asset distribution strategy and working with funding partners to explore innovative, compliant business model to improve the acceptance rate at the partners' end. In addition, we're also expanding our product offerings to serve long-tail customers throughout their life cycle, improving our ability to serve them while maintaining a healthy risk buffer. That said, there is still some uncertainty around the regulatory environment, and near-term adjustments are still ongoing. Therefore, we will continue to maintain a prudent approach in our overall business strategy. At this stage, our focus is on improving our user mix. asset health and operation efficiency. We won't chase volume growth blindly, and we won't rush to loosen these standards just because of short-term improvement in asset quality. By continuously improving our asset mix and overall platform resilience, we will be better positioned to navigate potential market volatilities in the future. Thank you.

Thank you. Your next question comes from Cindy Wong with China Renaissance. Please go ahead.

谢谢管理层给我这个提问的机会。 那我这边有两个问题想请教。 第一个,可不可以跟我们讲一下目前国内这个4月份5月的一个整体的一个风险表现。 那有机会持续在第一季度的一个基础下持续上好吗? 那第二个的话,想请问一下现在目前的一个货客成本的趋势。 目前采用了哪些货客渠道去获取高质量的一个客群? 然后现在看到的一些新货客的风险表现是如何? 那我很快地翻译一下我的问题。 Thanks for taking my questions. I have two questions here. First, could you give us some color on domestic risk performance in April and May? Is overall credit risk continue to improve from very colder? Second, what is the trend in customer acquisition costs? What customer acquisition channels are currently being used to acquire high-quality customers? And what is the risk performance from new customers? Thank you.

Okay. Yan, can you take the first one, and I will take the second one. Thank you.

Okay, let me answer the risk question first. The overall risk indicator of Q1 has improved significantly. Our C2MI indicator dropped 17% to 0.8%. In March, the C2MI of the big market has basically returned to the level of July and August last year. The overall risk improvement is also above expected, and it has basically reached a target of our risk optimization. This is mainly due to the continuous optimization of the wind tunnel strategy and some of the models. First of all, we continued to tighten the wind control measures in the second half of last year. We continued to upgrade the models of A-card and B-card on the underlying wind control capabilities to improve the identification and distribution capabilities of high-end customers and border high-end customers. The new FPD30 index also got some improvements with these optimizations. On the basis of Q3, Q4, FPD30 plus decreased by 18%. On the basis of Q1, Q4, FPD30 plus decreased by 22%. So the current performance of the new FPD7 in April is basically the same as in March. It continues to remain at a relatively low level of history. The average deadline for our loans is about 10 to 11 months. With the increase in the amount of loans added and the increase in the amount of loans accumulated, the large-scale risk will be gradually optimized. This period is about two to three seasons. Therefore, I would like to say that the quality of Q1 assets can be completely improved. Please translate at the same time.

Okay, let me briefly translate Mr. Jones' answers above. Other risk metrics improved meaningfully in Q1, with C2M2 ratio down 17% sequentially to 0.8%. By March, the ratio had returned to the levels seen in July and August last year. Overall, the improvement was greater than we had expected. and we have largely achieved our risk optimization targets. This was mainly driven by our continuous optimization of risk strategies and the iteration of our models. First, we started tightening risk standards since the second half of last year. At the underlying capability level, we kept upgrading A and B scorecards to better separate high-quality users from high-risk ones. As a result, the FPD30 metric for new loans has continued to improve. FPD30 plus decreased by 18% in Q4 compared to Q3, and further decreased by approximately 22% in Q1 compared to Q4. Moreover, based on early performance of new loans issued in April, FPD7 was roughly flat versus March. continuing to stay at a desirable level. Meanwhile, our average loan tenor is around 10 to 11 months. As new loans with lower risks take a larger share and legacy loans gradually roll off, our asset quality will improve eventually. And this cycle usually takes about two to three quarters. Given this timeline, our turnaround in Q1 asset quality was fully expected.

On the other hand, in the back-to-back management part, we have also made a major change to the C-CAN model in the past two seasons. By including new characteristics of change in the recent market environment and user behavior into the model system, and combining risk division to more accurately match the back-to-back management strategy, such as optimizing the user's response, providing a more suitable user response plan, etc. This is a good result of the upgrade of the model drive strategy. The recovery rate of Q1 has increased by 1.8%. And the trend is also improving. Next, we will maintain the recovery rate stable. Continue to take measures to further enhance the efficiency and strategic level. As of April and May, we have observed the risk performance. It is expected that C-M2 and March In March, it remained stable and good. In June, everything was normal. It is expected that Q2's Secondly, on the collection side,

We also upgraded our C scorecard over the past two quarters. We added new features that capture recent market conditions and changes in user behaviors. Based on risks here, we also matched collection strategies more precisely, including better user reach out and more tailored repayment solutions. This data-driven approach has worked very well. Our collection rate improved month by month, with Q1 collection rate increased by 1.8 percentage points sequentially. Going forward, we will continue to refine our strategies to make collection management more efficient while keeping collection rates steady. Based on the risk performance we currently observed in April and May, we expect the C2M2 ratio to remain generally stable with a positive trend compared to March. If everything proceeds normally in June, we will anticipate further risk improvement for Q2 compared to Q1. However, regulatory uncertainty remains and the industry will also face some adjustments as certain policies take effect. Therefore, we will stay cautious on risk policy for now. We will keep optimizing marginal assets and acquisition channels to build some buffer against potential markets happening going forward. Thank you.

And in terms of customer acquisition, our overall strategy this year is to spend cautiously as we aim for structural growth and constantly improving marketing efficiency. In Q1, we kept prudent marketing spending while reallocating resources. We cut back our spending on regular segments, for which we lowered acquisition costs and focused on higher quality users. The upfront billing costs for high quality users are typically higher. But thanks to our improved marketing efficiency, we kept our blended acquisition costs roughly flat sequentially, while further improving our user mix. In Q1, our spending on higher quality users was up about 40%, while our spending on regular segments came down significantly. We leverage similar channels such as to acquire high-quality users while using upgraded acquisition models to help us precisely identify users with strong credit profiles and stable repayment ability. Meanwhile, we have higher tolerance for bidding prices for acquiring these customers. As a result, the share of high-quality users among new credit line users was up 6% sequentially. High-quality users not only have better early risk performance, they also show more stable operating metrics later on, like more stable repeat borrowing rates and higher balance retention. That said, we are still in the early stage of building our know-how to serve this segment. Going forward, we will keep iterating our risk model based on user behavior and use more refined operations to steadily improve their lifetime value. Looking ahead, we will stick to this acquisition strategy by focusing on high-quality users and keep optimizing marginal channels and assets. And I want to emphasize that customer acquisition cost is just a number, which is heavily impacted by channels and acquisition mix. Therefore, we don't simply chase a low absolute CAC. Instead, for every dollar we spend, we track payback period. and user LGV, and measure efficiency based on ROI. For API channels, the acquisition cost is more tied to loan volume, so we measure ROI on each loan to ensure every single loan is profitable. At the end of the day, we want to make sure every dollar we spend delivers solid returns. Thank you.

Thank you.

Your next question comes from Eugene with CICC. Please go ahead. I have two quick questions. First, do we have further room to card operating and funding costs? Second, any updates on our overseas business? Thank you.

Okay. I'll take the first part, and then Haisheng will address the overseas expansion. So, first of all, regarding the funding cost, as we discussed in prior previous comments, even though the industry is still undergoing quite a lot of changes and we do face a little bit liquidity pressure, we are optimizing our funding mix by maintaining high percentage contribution from the ABS funding. In Q1, for example, ABS issuance reached RMB 2.9 billion, up 16% sequentially. The portion of ABS in our external funding went up 6 percentage points sequentially. With a more optimized funding mix, we were able to reduce our funding costs by about 10 basis points sequentially. Looking ahead, in the coming quarters, we will continue to seize ABS issuance windows and align the pace with unbalanced loan origination demand, we aim to maintain sufficient funding supply in the volatile market while keeping overall funding cost stable. And regarding the operating cost, since the end of 2025, we have been improving operating efficiency across all functions, including front, middle, and back office operations. On the direct cost side, our core approach is to dynamically manage operating resources. We align them with business need and continue to optimize the cost structure. Take collection costs as an example. As mentioned earlier, our portfolio risk metrics improved throughout Q1. This greatly eased pressure on the collection side. After seeing this trend, we quickly scaled back those high-cost, low-marginal yield strategies and adjusted our collection resource mix, further improved our overall collection efficiency. As for customer acquisition costs, Haisheng already covered in previous questions, so I'm not going to go over details here. On the G&A side, we took active steps in Q1 to improve efficiency in mainly around optimizing redundant or inefficient roles. This helps us make our teams linear and execution more efficient. The positive financial impact of these initiatives will be gradually reflected into the coming quarters. And we are also using AI to upgrade our organization, as Haicheng mentioned earlier. Right now, we are feeding our past data, strategies, and experience into AI model. This builds a quadruple knowledge base to support all our teams. This going beyond just helping with the day-to-day tasks is help our people improve skills, improve the decision quality, and professional capability across the board. As we use AI more, the cost efficiency that the market cares about will come naturally as a byproduct where we evolve to a true AI native company. I assume. Okay.

In terms of global market, the overseas expansion is a key part of our one call to win strategy. This year, we will allocate more resources to overseas business and accelerate the pace of our international process. Based on extensive research into global markets, we have identified several target markets with great potential in terms of credit demand. In these markets, our data-driven risk management capability will make us stand out. In markets we've already entered, like the UK and a large American country launched in Q1 this year, our current focus is on localizing risk models by gradually adding local credit data, open banking data, to improve our risk-based pricing. Early results are broadly in line with our expectations. In other high-potential regions, such as Southeast Asia, we are actively planning for the next step. Overall, our international business is still in early stage investment and capability building, but we are very patient about the long-term opportunities. We will leverage global capital, cabinet technology, and local expertise to drive substantial long-term growth in more of the markets over the the next several years while keeping risk under control. We are confident that with solid execution over the next three to five years, we will become a truly global fintech company. Thank you.

Thank you. There are no further questions at this time. I'll now head back to management for closing remarks.

Okay. Thanks again for everyone joining us today. Let's conclude our conference call. If you do have any additional follow-up questions, please contact us offline. Thank you.

Thank you.

Thank you. That does conclude our conference for today. Thank you for participating. You may now disconnect.