QFIN

Also note today's event is being recorded. At this time, I'd like to turn the conference over to Ms. Karen Ji, Senior Director of Capital Markets. Please go ahead, Karen.

Thank you, Darcy. Hello, everyone, and welcome to Qfin 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. Haisheng Wu, our Chief Executive Officer, Mr. Alex Xu, our Chief Financial Officer, and Mr. Yan Zheng, our Chief Risk Officer. 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 statements 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. Haisheng Wu. 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 one-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 FPD7, 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 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 enable 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 moat 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 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 sevenfold 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 life cycle, from customer acquisition and risk 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 a 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 the 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 the new emerging markets 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 Core, Two Wings strategy with our domestic credit business as the core 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 Xu.

Thank you, Haisheng Wu. Good morning and good evening everyone? Welcome to our first quarter earnings call. It was another quarter of challenging macro condition, and a tightening 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 macro headwinds. Total net revenue for Q1 was RMB 3.91 billion, versus RMB 4.09 billion in Q4, and RMB 4.69 billion a year ago. Revenue from credit-driven service, capital-heavy, was RMB 2.96 billion in Q1, compared to RMB 3.43 billion in Q4 and RMB 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 costs declined roughly 10 basis points Q-on-Q, as we further optimized the funding mix with increased percentage contribution from ABS in Q1. Revenue from platform service, capital-light, was RMB 951.9 million in Q1, compared to RMB 660 million in Q4, and RMB 1.58 billion a year ago. The year-on-year decline was mainly due to significantly lower ICE contribution in response to the regulatory changes. The sequential increase was mainly due to better ICE take rates 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 credit line users in Q4. We took a 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 macro 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. Again, 90-day delinquency rate is a lagging indicator, and internally, it's not a metric we care much about. Day one 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. C2M2, 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 tightening measures and loan mix shift toward new loans. We saw continued modest improvement in the overall risk performance in recent months. Given current macro conditions and regulatory changes, we continue to take a prudent approach in booking provisions against potential credit losses. Total new provisions for risk-bearing loans in Q1 were approximately RMB 1.68 billion versus RMB 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 Q on Q. Write-backs of previous provision were approximately RMB 308 million in Q1 versus RMB 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 days 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 days and 180 days in Q1, as total outstanding provisions were largely unchanged Q on Q. Non-GAAP net profit was RMB 946 million in Q1 compared to RMB 1.07 billion in Q4, and RMB 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 cost, and de-leveraging in operations. Non-GAAP net income per fully diluted ADS was RMB 7.7 in Q1 compared to RMB 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 2.4x in Q1 versus 2.7x 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 RMB 2.1 billion cash from operation in Q1 compared to RMB 3.15 billion in Q4. Total cash and cash equivalent and short-term investment was RMB 10.79 billion in Q1 compared to RMB 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 $577 million in aggregate principal amount of the CB for $502 million in cash on the open market and in off-market privately negotiated transactions.

Approximately $113 million in aggregate principal amount of the CB remained outstanding. The repurchase of the CB 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 capital allocation strategy to reflect the changing macro 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 macro and regulatory environment is still unsettled. Finally, regarding our business outlook, while we are encouraged by the noticeable improvement in risk metrics, macro uncertainty and regulatory pressure will likely persist in the near future. We will continue to take a 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 one on your telephone and wait for your name to be announced. If you wish to cancel your request, please press star two. If you are 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 Xu with Morgan Stanley, please go ahead.

Thank you. Two questions from me. Just observing the average pricing of the loans, it continue a downward trend. Relative to relatively stable pricing at the peers, what was the rationale and thinking behind that? Where the average loan pricing will eventually settle later this year? 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 Xu. Let me take your first question, Alex may take your second one. In terms of pricing, first, as we currently in a rate cut cycle, lower financing costs help improve the household balance sheet and unlocks healthy consumption demand. 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 risk profile.

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 sequentially. Based on our observation so far, high-quality users tend to carry lower risk than regular segments, with higher 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. Strengthening our capabilities to serve high-quality users is a long-term play. In the short term, it requires investment.

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 healthier and better positioned to navigate a more complex and fast-changing market environment.

On the outlook of pricing. First, we increased our investment in acquisition and the conversion rate of high-quality users starting in Q4 last year. Over the past two quarters, we have seen a step change increase in the share of high-quality customer segments in total loan 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 life cycle continue 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 adjust our pricing strategy based on regulatory and market changes.

At the same time, we will continue to improve our risk model and operational efficiency to strengthen profitabilities.

Okay, Richard, I will take the second part of your question. I think the landscape changing of the consumer finance industry is still ongoing. In the near term, macro and the regulatory environments remain pretty complicated. On our side, we are actively adjusting our asset mix 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 in our ability to meet more credit need over time. However, at this stage, I would say our focus probably remain 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 continue to generate substantial profit and a healthy positive cash flow, which steadily build up our capital base. Both dividend and buybacks are considered as options for us. At this stage, we see dividend as a way to give shareholders certainty in an uncertain environment. Assuming that a 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. There is still uncertainty around the macro and regulatory environment, and our business model continue to evolve, we believe share buyback, once again, becomes a viable option for shareholder returns at this junction. Thank you.

Thank you. Your next question comes from Alex Ye, UBS, please go ahead. Pardon me, Alex, your line may be muted.

My question is regarding the loan growth outlook. Given the stabilization of asset quality, we have already shifted our customer mix toward a higher quality customer, when could we expect the company to increase its risk appetite a little bit? Shall we expect loan volume to return to some sequential growth in the coming quarters? Thank you.

Okay. Alex Ye, thank you. First, 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-tightening measures, significantly reallocating resources toward the acquisition and engagement of high-quality users. This initiative have led to a market improvement in both of our asset structure and asset quality. In two months, 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 approved and credit line rules.

Within a safe range, we improved our conversion rate and effectively served more credit demands. We've also optimized our asset distribution strategy and are working with funding partners to explore innovative compliance business model to improve the acceptance rate at partners. In addition, we're also expanding our product offerings to serve long-tail customers throughout their lifecycle, 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 operating efficiency. We won't chase volume growth blindly, and we won't rush to loosen risk 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 Wang with China Renaissance, please go ahead.

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 Q1? Second, what is the trend in customer acquisition cost? What customer acquisition channels are currently being used to acquire high-quality customers? What is the risk performance from new customers? Thank you.

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

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Okay. Let me briefly translate Mr. Zheng's answers above. Our 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. 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-scorecards 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+ decreased by 18% in Q4 compared to Q3, 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 months-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.

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Secondly, on the collection side, we also upgraded our collection scorecard over the past two quarters. 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 prepayment 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 happening going forward. Thank you.

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 bidding costs for high quality users are typically higher. Thanks to our improved marketing efficiency, we kept our blended acquisition cost roughly flat sequentially, while further improving our user mix. In Q1, our spending on higher quality users was up by about 40%, while spending on regular segments came down significantly. We leveraged similar channels such as feed ads 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 six percent points 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. 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 LTV, 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 Yujie Jing with CICC, please go ahead.

Thanks for taking my question. I have two quick questions. First, do we have further room to cut operating and funding costs? Second, any update on our overseas business? Thank you.

Okay. I will take the first part. Haisheng Wu will address the overseas expansion. First of all, regarding the funding cost, as we discussed in 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 six 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 on-balance sheet loan origination demand.

We aim to maintain sufficient funding supply in the volatile market while keeping overall funding costs stable. 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 cost as 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 those high-cost, low marginal yield strategies, and adjust our collection resource mix further improved our overall collection efficiency. For customer acquisition costs, Haisheng Wu already covered in previous questions, so I'm not going to go over detail here.

On the G&A side, we took active steps in Q1 to improve efficiency, mainly around optimizing redundant or inefficient roles. This help us make our teams leaner and execution more efficient. The positive financial impact of these initiatives will be gradually reflected into the coming quarters. We are also using AI to upgrade our organization, as Haisheng mentioned earlier. Right now we are feeding our past data, strategies, and experience into AI model. This build a qualifiable 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. Haisheng?

Okay. In terms of global market, overseas expansion is a key part of our One Core, Two Wings 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 U.K. 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.

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.