Ladies and gentlemen, thank you for standing by and welcome to the Cuban 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 G. Senior Director of Capital Markets. Please go ahead, Karen.

Thank you, Darcy. Hello, everyone, and welcome to QC 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 Haishen, our CEO, Mr. Alex Xu, our CFO, and Mr. Zhen Yan, our CRO. 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 maintain 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 lifecycle. As a result, our FPD-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, C-to-M2 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 experienced 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 FPD-7 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 allocation. 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 enables 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 insurance 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 on-balance 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-call-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.

And good evening, everyone. There was another pending regulatory scrutiny, which caused further changes in industry landscape and the participants' behavior. We continue to focus on mitigate risks, improve efficiency, and reduce cost under such micro headwinds. Total net revenue for Q4 and $12.69 billion a year ago. Revenue from credit is $2.96 billion compared to $3.43 billion in Q4 and $3.11 billion a year ago. The year-on-year decline was mainly due to 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 cost declined roughly 10 basis points Q-on-Q as the funding mix with increased percentage contribution from ABS in platform service $951.9 million in Q-1 compared to $660 million in Q-4 and $1.58 billion a year ago. The year-on-year decline was mainly due to significantly lower ICE contribution in response to the regulatory exchanges. The sequential increase was mainly due to better ICE take rate due to improve. During the quarter, average IRR of the loans we originated and or facilitated was 18.7%, 18.5% in price. 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 marketing expenses declined 17% Q1Q and 23% year-on-year. We added approximately 1.19 million new credit line users in Q1 versus 1.45 million in Q1. 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 2.7% near the end of 2025. Again, 90-day delinquency rate is a lagging indicator, and internally, it's not a metric we care much about. Day 1 delinquency rate was 5.7% in Q1 versus 6.1% in Q4. 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 our risk time, and we saw continued modest improvement in the overall risk performance condition and regulatory changes. we continue to take prudent approach in booking provisions against total new provisions for risk-bearing approximately $1.68 billion versus $1.92 billion in Q1, mainly due to lower risk-bearing loan volume, partially offsetting by increased or 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 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, unchanged. Non-GAAP net profit was $946 million in Q1, $07 billion. Significant year-on-year decline was mainly due to lower loan volume and lower pricing. Higher credit costs and deleveraging in non-GAAP net income per fully diluted ATS was 7.7 RMB in critical ETR of approximately 15 percent 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 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 fluctuated 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 in cash $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, we purchased approximately U.S. $577 million in aggregate principal amount of the CB for U.S. $502 million in cash on the open market and in-off market privately negotiated transactions, approximately U.S. $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 strengthen our financial positions and flexibility. We will continue to optimize our capital allocation strategy to reflect the changing microdynamic 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 the micro and the regulatory environment is in risk metrics. Micro uncertainty and the regulator will continue to take cautious approach in business planning for 2026 and focus on risk control, efficiency improvement, and for 2026 the company expect to generate non-GAAP net income between R&B, not in a year-on-year decline between 47% and 51%. This outlook reflects the company's current 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 comes from Richard Zhu with Morgan Stanley.

Please go ahead. 同业相对平稳的定价策略还是有所区别 就想问一下背后我们的一些原因和思考 然后展望今年4季度平均定价可以最终稳定在什么水平 还有也想再请教一下 现在管理层对业务模式调整后的需求和业务规模有什么的看法 尤其是对这个股东的回报,我们长期有哪些策略? Two questions from me, just, you know, observing the average pricing of the loans, it continued a downward trend relative to relatively stable pricing at the piers. 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 your second one. In terms of pricing, first, as we are currently in more financing cost balance sheet, healthy consumption demand. As we mentioned before, this is overall positive for the industry as it is accelerating market consolidation. Long-tier 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. Precise user profiling and better risk-based pricing capabilities are likely to take the market shares. Proactively adopted targeted pricing to optimize our user mix. Since Q4 last year, we have put more efforts to acquire high-quality users, with that by about 40% sequentially. As a result, the share of high-quality users in our new 25 percentage points from Q3. At the same time, we also optimized pricing for our existing users with better risk pipes. By giving them more competitive offers, we intended to increase their stickiness on our platform. In addition, we also expanded their borrowing capabilities reasonably to help build a stable long-term LTV. As a result of these efforts, our average pricing was down 80 basis points. observations so far. High quality users than regular segment utilization, more repeat borrowing, steady long-term demand, and therefore much healthier LTV. Going forward, we will continue iterating our models to better identify higher 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. Our capability 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 acquisition and conversion rate of high-quality users starting in Q4 last year. Over the past two quarters, we have seen a step-changing increase in a share of high-quality customer segments in total on volume, with pricing trends moving in the same direction. As a result, our pricing has declined by 2.2 percentage point over this period. Going forward, we expect to maintain a relatively steady pace on acquisition and offer strategy. As the user life cycle 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, strike a balance between risk and profit. Over the longer term, we will remain flexible and adjust 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.

So I think the landscape changing of the consumer finance industry is still ongoing. and the near term remains pretty complicated. The adjusting market demand is always there. And as we keep upgrading our capability users, we are confident that the ability of the business. In terms of shareholder returns, our balance sheet is still pretty robust in the shareholder returns. At the same time, our business continues to generate substantial profit and a healthy positive cash flow to build up our capital base. Both dividends and the buybacks are considered as options as a way to give shareholders certainty in an uncertain environment. And assuming that a stable regulatory environment, we will maintain a progressive DPS policy, achieving this through flexible adjustment. 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, business model continues to evolve, once again becomes a viable offer at this junction.

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

Thank you for giving me a chance. 問題關於這個這個資產質量的這個期穩以及這個我們當前在貨客策略上對優質客權的一個傾斜 我們什麼時候可以看到公司在風險偏好上有所回升 以及是否可以預期咱們這個 loan volume 在後續幾個季度可以回到一個環比的一個增長的態勢 So my question is regarding the long growth outlook, so given the sterilization of asset quality and we have already shifted our custom mix toward a higher quality customer, so when 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?

As the structural change we have made to risk management and our user mix have delivered clear results. Since the second half of 2025, we have implemented a series of risk-tighting and reallocating resources toward the acquisition and engagement of high-quality users. These initiatives have led to a marked improvement in both our asset structure and asset quality. In Q1, C2M2 ratio in March has returned to levels seen in July and August of last year. C2M2 ratio continues to improve marginally. While keeping risk stable and improving, we've also experimented with a solid safety margin based on our risk models. We dynamically adjusted our approved and credit line rules. We then improved our conversion rate and effectively served more credit demands. It might have been our asset distribution strategy and working with funding partners, business model, the partnership. In addition, we've also expanded our long-tailed customers throughout their life cycle to serve them while maintaining our health uncertainty around the regulatory environment, and near-term adjustments are still ongoing. We will continue to maintain a prudent approach in our overall business strategy. At this stage, from improving asset health and operating efficiency, we won't chase volume growth blindly, and we won't rush to just because of short-term improvement. By continuously improving our asset mix and overall platform resilience, we will be better positioned to navigate potential market volatilities in the future.

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是四月份五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向好吗 那第二个的话想请问一下现在目前的一个获客成本的趋势 目前采用了哪些获客渠道去获取高质量的一个客群 Now, I'll quickly read my question. 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 first quarter? Second, what is trending customer acquisition cost? What customer acquisition channels are currently being used to acquire high-quality customers? and what is the risk performance from new customers? Thank you.

Thank you. 基本达到了我们风险优化的一个目标 这主要来自于我们持续的优化风险策略和模型的一些迭代 首先我们去年下半年开始持续收紧风控措施 在底层风控能力上面我们持续升级了A卡和B卡的模型 提升模型对于优质客群和边际高风险客群的识别和区分能力 新放款的FPD30指标也随着这些优化持续得到了一些改善 Q4在Q3基础上FPD30加降低了18% Q1在Q4基础上又进一步的降低了约22% 所以目前表现的4月新放款的FPD7也基本和3月份持平 继续保持在历史比较低的一个优秀水平上面

Okay, let me briefly try Finally, Mr. Jones answers above. Our risk metrics improved meaningfully in Q1, with C2M2 ratio down 17 percent sequentially to 0.8 percent. 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. 其次呢 在代后管理环节啊 我们过去两个季度也对C卡模型进行了比较大的迭代 通过将近期市场环境和用户行为的变化的新特征纳入到模型体系里面 结合风险分层 更加精准的匹配了代后管理策略 比如优化了用户的触达 提供了更适配用户的还款方案等 这种以模型驱动的策略升级取得了还不错的效果 Q1的回收率环比提升了1.8个百分点 且趋势上也是逐月在改善的 那接下来我们会在维持回收率平稳的前提下 继续迭代策略 进一步提升待会管理效率和策略的精心化水平 至于4-5月份 我们已经观察到的风险表现 预计C-M2和3月份 在3月份基础上是保持平稳向好的 那么如果6月份一切正常 预计Q2的风险 会在Q1的基础上 进一步的得到改善 不过目前考虑到监管环境 仍然有一些不确定性 且随着一些政策落地 行业仍然会面临一些临时的调整 我们现阶段 仍然会保持仅剩的一些风险策略 持续优化编辑资产和编辑货客的渠道 为应对可能的行业风险预留一定的Buff

Secondly, on the collection side, we also upgraded our C-score card over the past two We added new features that capture recent market conditions and changes in user behaviors. Based on risk tier, 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 market headwind going forward. Thank you.

The last acquisition this year is as we aim for structural growth and constantly improving marketing efficiency. In Q1, we kept prudent marketing spending while reallocating resources for spending on regular segments. We lowered acquisition costs and focused on higher-quality users. The upfront bidding costs for high-quality users are typically higher, but thanks to marketing efficiency, we kept our blended acquisition costs roughly flat sequentially while further improving our user mix. Our spending on higher about 40% while spending on regular segments leveraged similar channels such as feed ads for 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 high-quality users among new credit line users with up 6%. High-quality users not only have better early, they also show more stable operating metrics later on, like more stable repeat borrowing rates and higher balance retention. Still in the early stage of building our know-how to serve this segment, 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. 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 CEC. Instead, for every dollar we spend, we track payback period and user LTV and measure efficiency based on API channels. The acquisition cost is more tied to loan volume, so we measure RLA 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. question.

I have two quick questions. First, do we have further room to cut operating and funding costs? Second, any updates on the 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, even though the industry is still undergoing quite a lot of changes and minimizing our funding mix by maintaining high percentage contribution from the ABS funding. In Q1, for example, ABS issuance reached R&B 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'll continue to seize these ABS issuance windows and align the pace with on-balance sheet loan origination demand, we aim to maintain sufficient funding supply in the volatile market while keeping overall funding cost. 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 needs and continue to optimize the cost structure. Take collection costs as an example. As mentioned earlier, our portfolio risk metrics improved throughout the Q1. This greatly eased pressure on the collection side. After seeing this trend, we quickly scaled back low marginal yield 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, 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 I mentioned earlier. Right now, we are feeding our past data, strategies, and experience. Going beyond just helping with the day-to-day tasks is helping our people improve 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...

The expansion is a key part of our one call to win strategy. This year, we will allocate more resources to and accelerate the pace of our international process. Extensive research into global markets, we have identified several target markets with great potential in terms of credit demand. In this market, our data-driven risk management capability will make us stand out. In markets we've already entered, like the UK and a Latin 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 steps. Overall, our international business is still in early-stage investment and capability building. But we are very patient about the long-term opportunity. We will leverage global capital, cabinet technology, and local expertise to drive substantial long-term growth in more overseas markets over 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. There are no further questions at this time. I'll now head back to management for closing remarks.

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.