Qifu Technology, Inc

Ladies and gentlemen, thank you for standing by and welcome to Tfue Technology's first quarter 2023 earnings conference call. At this time, all participants are in listen-only mode. After the speaker's presentation, there will be question and answer session. To ask a question during the session, you will need to press star 11 on your telephone. You will then hear an automated message advising your hand is raised. To withdraw your question, please press star 11 again. Please also note today's event is being recorded. At this time, I'd like to turn the conference call over to Ms. Karen Gee, Senior Director of Capital Market. Please go ahead, Karen.

Thank you, operator. Hello, everyone, and welcome to Chief Food Technology's first quarter 2023 earnings conference call.

Our earnings release was distributed Joining me today is Mr. Wu Haisheng, our CRO, Ms. Alex Xu, our CRO, and Mr. Chen Yan, our CRO.

Before we start, I would like to refer you to our safe harbor statement in the earnings price release, which applies to this call as we will make certain forward-looking statements. Also, this call includes discussions of certain non-gap financial measures. Please refer to our earnings release. which contains a reconciliation of the non-GAAP measures to GAAP measures. Also, please note that unless otherwise stated, all figures... Over to our CEO, Mr. Wu Haisheng.

Please go ahead.

Okay.

Thank you, Karen. Hello, everyone. First of all, I would like to thank everyone for joining us today.

Thank you for joining us.

By the end of Q1, our platform cumulatively connected approximately 46 million users with approved credit lines and a total of 150 financial institutions. Total loan facilitation and origination volume on our platform reached RMB 109.5 billion. up by 10.7% year-over-year and 4.7% quarter-over-quarter. The cumulative number of users with approved credit lines increased 15.6% year-over-year. The growth was better than our initial expectation against the back of the rate to recovery in China's macroeconomy. Since the beginning of this year, we have seen positive overall trends in our business, including credit demand from users steadily increasing and continuous improvements across multiple risk indicators.

With the optimization of our overall customer base, our average pricing has remained stable in Group 1. um um Since Q3, we have introduced the real-time data of the human card into the public risk group. The dimension of the data is more than 20,000. Therefore, it provides a very good guarantee for the value of our users. Due to the continuous improvement of the accuracy of our risk recognition, From last year to April of this year, we have decreased 37 BP in the first few days. The recovery rate of 30 days has increased by 189 BP. At present, our risk level has reached and surpassed our target. And it is still in the process of deterioration. Price remains stable during the quarter with our user base having been substantially optimized.

At the same time, we continue to upgrade our risk management models, including the release of more than 1,000 version updates. an iteration of over 30,000 strategic rules to our credit assessment models over the past 12 months. We also further upgraded our PBOC credit data assessment modules. Since Q3 last year, we have started to incorporate PBOC credit data into our ongoing post-credit assessment process on a large scale. With over 20,000 derived data dimensions, we are able to unlock the value of our existing users with enhanced credit assessment capabilities. Supported by our constantly improving ability to accurately identify risks, our day one delinquency rate in April 2023 decreased by 37 basis points from December 2022, while our M1 collection rate increased by 189 basis points for the same period. With our risk performance having substantially reached our target, we are more confident in gradually ramping up investments in customer acquisition in the near term.

从资金的角度来看,一季度色龙的增速是10%, M2的增速是12.7%,所以市场的流动性依然很宽裕。 Um, uh, uh, uh, uh, uh, The average cost of ABS is also 17BP. We will continue to optimize the structure of our organization's cooperation to maintain the strong advantage of our organization.

Liquidity in the financial system remained ample during the quarter, with total social financing and the M2 money supply increasing by 10% and 12.7% year-over-year, respectively. This enabled us to further diversify our funding sources and reduce our funding costs by 30 basis points sequentially. In addition, with our solid risk performance in the loan facilitation model, we have obtained more allocation from our financial institution partners for ABS issuance, thereby accelerating our pace of issuance. In Q1, we issued RMB 2.3 billion of ABS at 77% year-over-year, far outpacing the growth of overall consumer loan ABS issuance in China. Our funding costs associated with ABS issuance also decreased by 17 basis points sequentially, contributing to a further reduction in overall funding costs. Going forward, we will continue to deepen our partnerships with financial institutions and strengthen our competitive edge in terms of funding costs. We expect overall funding costs to remain generally stable over the next two quarters.

We have reached some cooperation agreements with Bilibili. It has become their first business partner in financial technology. At the same time, we have also completed the technical deployment of financialized hair in many head phone manufacturers. After upgrading the hair model, it has provided great help for us to optimize the customer efficiency of app stores. For example, in some app stores, um um um um

In terms of customer acquisition in Q1, we entered into a co-operation agreement with Bilibili during the quarter, becoming one of its first batch of fintech marketing partners. We also launched precision marketing with the RTA model in app stores of major mobile phones. This marketing model will help us improve our marketing efficiency on the relevant app store platforms. For example, our customer acquisition costs per credit 20% lower than it had been in the traditional model. Within our embedded finance business, we connected with additional traffic platforms, which results in new users receiving credit lines. In addition, we have been exploring innovative ways to acquire new customers. The official live streaming account for our 360 detail product was launched on a short-form video platform in April.

The marketing effect is better than our expectation.

In terms of the management of our mass users, we are constantly increasing the coverage and coverage of users, and we are also improving our operation strategy. First of all, This is a new channel that covers more than 200,000 users. This is a new channel that covers more than 200,000 users. It can bring very good performance efficiency.

We further expanded our outreach to existing users and optimized operational strategies to boost user conversion and retention. In Q1, we introduced the enterprise WeChat as a new channel for engaging with our existing users. which drives user conversion by offering a step-by-step guide through the loan application, drawdown, and submission process. As of today, we have engaged with more than 200,000 existing users. Furthermore, we also improve the user retention by optimizing our product offerings and user experience based on extensive surveys of our existing users.

We also pay attention to the need for Fan Xiaowei's group. This is a first. Therefore, we are also working hard to build the recognition and management ability of Fan Xiaowei's group. Through the improvement of the credit card, the banknote, and some of the business flows, and some of the data in the industry, we can identify the division of the Fan Xiaowei group. As the macro economy gradually recovers, we have noticed that demand has been rebounding faster

among broadly defined SME borrowers. To capture this demand, we strategically strengthen our ability to identify and manage the specific segments. We enhance our customer profiling capabilities by improving data dimensions, such as credit history, invoice, e-commerce transactions, billing, industry data, which allow us to accurately identify customers within the broadly defined SME segments. which accounts for more than 40% of our current user base. Our next step is to conduct pilot tests on a selected group of users, aimed at developing differentiated products and fine-tuning risk management strategies for the broadly defined SME segment, which we believe has the potential to drive meaningful growth for our business industry.

In the financial technology industry, The focus of this quarter is still on improving our product history. We have further enriched the technology decision-making program for institutional output. At this time, the product line is expanded from individual loans to individual business loans and agricultural loans. Based on the diversified deployment method, we should be able to better meet the needs of the financial institutions on all sides. We have also completed the standardization and productization of core technical capabilities. We have developed 18 new systems. All of them cover various business segments from customers to remote control to operations to accounts. And we have also integrated the know-how we have accumulated in the new business into this system. We should be able to let our institutional partners appear at the top of the system.

For our technology solution business, our focus in Q1 was on enhancing our product capabilities. Specifically, we extended the scope of our solutions beyond personal consumer loans to include individual business loans. Our diversified deployment methods allow us to better serve the unique needs of each finance to show institutions we work with. So far, we have developed standardized products based on our core technological capabilities and have created 18 standardized modules covering every aspect of the credit business, including customer acquisition, risk management, operations, and accounting, et cetera. We also incorporated our extensive credit industry know-how into the modules, which empowers financial institutions and expertise.

and algorithms from the moment they onboard.

In the past period of time, the emergence of chat GPT is greatly affecting all industries. For us, we also believe that deep city AI has a lot of natural application scenarios in finance. For example, in various conversational robots, it can overcome sales, acceleration, etc. It should be said that it can better understand users' emotions than the previous technology, and create a better, more natural, individualized conversation. In addition, in the wind control section, this technology can also more accurately help us to train this kind of information, which is the true report, to create an extended battery life. to improve our risk recognition model. This year, in February, our company also established a large model department of the first level department. We are determined to let this department develop all kinds of in-depth learning methods, new urban artificial intelligence technology, and commercialization applications in the field of financial science and technology. At the same time, we have also released some Qt templates. At present, We carry out analysis and training in the collection, e-mail, and customer service. With the intention of analyzing users and labeling them, we can see that different label users still have a clear difference in the collection, e-mail, and customer service. Through this technology, We also think that in the future, this kind of technology should have a very good performance for our financial institutions. We also did some research and communication with customers, and the expectations of customers for this product are very high.

Over the past few months, ChatGPT has been having significant impact on various industries since its release. We believe that generated AI technology has many natural . For example, in areas such as intelligent customer service, telemarketing, and loan collection, ChatGPT can better understand user emotions and facilitate natural, smooth, and personalized interaction with users. In risk management, It can derive useful information from credit reports and identify relevant factors for our risk management models. In April, we established a large language model department. This new strategic innovation is dedicated to developing various deep learning algorithms and generative AI technologies specifically for applications in the financial sector. We have already launched the first version of GPT for internal use, which is designed to perform semantic analysis in our loan collection and the telemarketing process. Through GPT analysis of user intention and the labeling, we can see that the users of different labels have clear variations in the effectiveness of collection and telemarketing. Apart from applying AIGC to enhance the user experience and our operational efficiency, we also plan to gradually export such capabilities to our financial partners.

From the point of view of supervision, our company's change in QE should be steadily advancing. We have already followed the plan of the supervision department. On the regulatory front, we continue to make steady progress in gaining compliance with Fan Zhilian credit agency reform in Q1.

We have substantially completed the required integration of systems with our financial partners according to the plan we submitted to the regulator. So far, our loan facilitation progress through the model has been very smooth. Given the current regulatory focus on promoting economic development, we believe the industry will be able to deliver healthy growth in a stable regulatory environment.

We look forward to the next few seasons of this year. Although it is still in the early stages of economic recovery, the trend of recovery is certain. We also believe that this year will be a year of gradual improvement in the public environment. We are confident to grasp the pace of recovery and achieve our goals in high quality.

Looking ahead, while the economic recovery is due in its early stage, but the trend for recovery is clear. We believe that the macroeconomic environment will gradually improve throughout the remainder of the year. We are also confident in our ability to capitalize on the recovery momentum and deliver on our goals effectively. 最后跟大家分享个消息。

We just passed a board meeting to promote our shareholding for shareholders. It shows that while our company is pursuing a high-end performance growth, we have been paying close attention to the voice of the market. We hope to continue to give back to shareholders and share the profits of the company's growth, and better maintain the value of our company. Finally, I have some news to share with you all. Our board of directors has just passed a resolution to increase our dividend payout ratio. As we continue to drive quality growth and create shareholder value,

It is also important to listen to the market and share the benefits of growth within our shareholders. We believe this will enable us to enhance the value of our company. Alex will share more about this later. With that, I will now turn the call over to our CFO, Alex, who will talk us through with our financial results for the quarter.

Thank you, Kaizhen. Good morning and good evening. Welcome to our first quarter earnings call. First quarter set a positive tone for recovery year. The improvement in many aspects of our operations. User activity levels continue to improve in recent months, aside from normal seasonality. Although we still want to call the recovery a modest one, things are indeed trending a little bit better than we initially thought. As I discussed earlier, with micro-conditions improving throughout 2023, we intend to focus on effort and deploy our resources to drive actual growth while maintaining desirable asset quality. In Q1, target high-quality and low-risk user base and drive further improvement in risk performance. Key leading indicators in Day 1 delinquency has been on a steady declining trend in recent quarters. was 4.1% in Q1 versus 4.3% in Q4 and further declined to approximately 4% in April. The continued improvement in day one delinquency mainly reflect the micro-improvement as well as further optimization of our algorithm. 30-day collection rate was 86.2% in Q1 versus 84.7% in Q4. This sharp rebound from the COVID disrupted Q4 mainly reflected back-to-normal collection operations. As economic recovery continues, we see further improvement in this metric. By late April, early-day collection rate already at near 87%. Total net revenue for Q1 was $3.6 billion versus $3.9 billion in Q4 and $4.3 billion a year ago.

The problem from the reference to this project, for example, was 2.6 million U.S. dollars, compared to the 2.6 million U.S. dollars and 2.5 million U.S. dollars. The result is that the sequestering cost was mainly due to overpricing in its assets at first chapter of the new loan, as well as further adjustments to the existing loans at first chapter.

New Year, spillover effect from mortgage early repayment momentum and oversupply of liquidity at the beginning of the year. Looking ahead, we expect early repayment level to stabilize in Q2 as above-mentioned matters or factors gradually easing. Our balance sheet loans continue to grow at a faster pace and account for nearly 20% of the total loan volume. And we continue to drive for better utilization of our capital as well as our micro-lending license. Revenue from platform service, Capital Light, was $969 million in Q1, compared to $1.1 billion in Q4 and $1.4 billion a year ago. The year-on-year and sequential decline was also mainly due to overall decline in expected average tenure of new loans, as well as further adjustment to existing loans' expected tenure. For Q1, Capital Light loan facilitation ICE, and other technology solutions combined account for roughly 56% of the total loan volume, roughly flat versus the prior quarter. We expect the risk ratio to be relatively stable throughout this year. In the long run, we'll continue to pursue tech-driven business model while seeking a balance among various forms of non-risk-bearing solutions based on microenvironment and operational conditions. During the quarter, average IRR prices of loans we originated and or facilitated remain stable Q and Q, well within the regulatory cap requirement, rate cap requirement. Looking forward, we expect pricing to be relatively stable for the coming quarters. Sales and marketing expenses increased marginally Q and Q. as recovery in our user activity was offset by seasonal impact of Chinese New Year. We added approximately 1.5 million new credit line users in Q1, flat versus Q4. The unit cost to acquire a new credit line user also increased marginally. While we will continue to drive for efficiency in our operations, we may adjust the pace of new user acquisition as economic recovery continues throughout 2023. Meanwhile, we'll continue to focus on re-energizing existing user base as repeat borrowers historically contribute vast majority of our growth. Although we will continue to take prudent approach to book provision against potential credit loss, we should expect increasing write-backs from provisions prior periods as overall risk profile of our loan portfolio gradually improved along with micro-conditions. Total new provisions for risk-bearing loans in Q1 was approximately $1.7 billion, and the right backs of the previous provisions were approximately $411 million. Provision coverage ratio, which is defined as total outstanding provision divided by total outstanding delinquent loan balance between 90 and 180 days, or 432% in Q1, compared to 456% in Q4. With solid operating results and stable contribution from capital life model, our leverage ratio, which is defined as risk-bearing loan balance divided by shareholders' equity, was at a historical low of 3.4 times in Q1 compared to 4.2 times a year ago. A rather stable leverage ratio for the time being until non-risk bearing contribution resume growth in the future. We generate approximately 1.8 billion cash from operation in Q1, roughly flat Q on Q. Total cash and cash equivalent was $9 billion in Q1 compared to $10.9 billion in Q4. Non-restricted cash was approximately $5.1 billion in Q1 compared to $7.2 billion in Q4. The sequential decline in cash position was mainly due to increased cash usage in our balance sheet lending. As we discussed earlier, With economic conditions improving, we may look for opportunities to deploy resources to launch new initiatives and develop new technologies and extend our service offerings. Non-GAAP net profit was $976 million in Q1 compared to $919 million in Q4. As we continue to generate healthy health cash flow from operations, we believe our current cash position is sufficient to support our business development and to return to our shareholders. Since Q3 of 2021, we have paid out a total of $1.34 billion cash dividends to our shareholders in six consecutive quarters. To generate high returns to our investors and solidify and expand our long-term investor base, the company's board of directors approved a new dividend plan yesterday. The new plan increased our dividend payout ratio to 20% to 30% from previous 15% to 20% of net profit. Also, to reduce the transaction cost for our shareholders, the new plan approves a semiannual dividend distribution schedule to replace the quarterly dividend schedule of the old plan. The first semiannual dividend payout will be declared in our Q2 earnings release. Finally, regarding our outlook for 2023, while we start to see a gradual recovery of microeconomy and our business activities are also trending a bit better than previously thought, it may still take extra time for consumers' confidence and behavior return to normal. At this junction, we still see a modest recovery in consumer credit demand, with growth rate potentially accelerating throughout the year. As such, we would like to maintain our full-year total loan volume target for 2023 at between RMB $455 billion and RMB $495 billion, representing year-on-year growth of 10% to 20%. As always, this forecast reflects the company's current and preliminary view, which is subject to material change. With that, I would like to conclude our prepared remarks. Operator, we can now take some questions.

Thank you. As a reminder, to ask a question, please press star 1 1 on your telephone and wait for your name to be announced. To withdraw your question, please press star 1 1 again. For those who can't speak Chinese, kindly ask your question in Chinese first, followed by English translation. In addition, in order to have 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 more questions. Once again, that's star 11 for questions. Our first question comes from the line of Frank Chen from Credit Suisse. Please ask your question, Frank.

Thank you, management, for taking my questions. This is Frank from Credit Suisse. I have two questions. The first one is on the strategic focus for the rest of the year. Could the management provide more color on measures, for instance, more aggressive client acquisition, optimization on existing clients, and potentially further upgrade in client segments. And second question is on operating expenses. What are some of the measures the company is taking to be operationally more efficient? Thank you. Thank you, Frank.

Let me answer the first question. And then you, Alex, prepare for the next question. And then about this customer turn, we think that in this year, new customers and current customers should be said to be our very key work. In terms of new customers, our work will be in several aspects. The first is that we will continue to improve our concept of channels and the depth of cooperation with channels. We see that there is a lot of work to be done here. We continue to make a lot of innovations on the live broadcast of the video and the RxC of the App Store this year. The results are also better than before. The second is that we have increased the recognition of our users' notification wishes through the model identification. Okay.

Thanks, Frank. And I will answer your first question, and I will pass the second question to Alex.

First, about the... Sorry.

For this year, we want to say the new customer and existing customer are equally important to us. So in terms of the new customer acquisition, our efforts will be focused on two aspects. First, we will continue to expand our partnership with different channels and increase the depth of the partnership. For example, we have been trying the live streaming on some short-form video platforms. and we innovatively utilize the RTA model into our app store marketing. The result is better than our initial expectation. And the second part, we use the RTA model to increase our recognition about the users' willingness to borrow, so we can optimize our offer and increase our users conversion ratio therefore we can increase the ltv of our users and so we will increase our competitiveness in in terms of customer acquisition this is about the new customer new new customer acquisition part um

You're getting our voice.

Existing users, actually we have a very significant user base of our existing users, so it's very important for us to increase efforts on existing users to improve the conversion effectiveness. For example, we have tried to use enterprise WeChat to cover our existing users to increase effectiveness for us to outreach our existing users. refine our risk management models to better understand our users and identify different profile of our users. For example, 40%. So later we can optimize our offer and improve our user engagement process to better engage the existing users to improve their long-term value.

Generally speaking, in terms of customer service, we believe that in the context of the need for peace and recovery, We should put more energy on efficiency, on internal work, to improve the efficiency of our customers, to innovate more of this type of technology. From what we have seen so far, and from the new technology, we have made a very leading step. uh moderate macro economy recovery uh the environment we believe it's very important for us to increase our efficiency at this stage so we

will increase our coverage in terms of the channel and the partnership. So we can better improve our marketing efficiency. So I think we are actually enjoy the competitiveness in terms of this part. And we believe we will further increase our user base when the macro further improves.

Okay.

Hi, Frank. So basically for the operating expenses trend going forward, there are a few aspects. One, some of the operating expenses are variable costs. For example, the one we use to get the credit scores cost and the one we do the transaction or sending the message through SMS. Those variable costs, we have a long-term relationship with those suppliers, and every year you can always squeeze a little bit from the cost base on a unit basis, but the room for that is not really that much. And then the other big part of the variable cost is really customer acquisition. I think we had this kind of discussion earlier or before. Last year our unit or per credit line users customer acquisition cost was about 370 or 360 RMB per user this year We intend to lower that unit cost number to somewhere around 330 The first quarter was only about 200 280 Less than 290 so The following quarters, with the kind of increased pace of a customer acquisition, you may see some increase in sales marketing spending. But overall, on a four-year basis, we will see a lowered unit cost per credit and user's acquisition cost. Other back-office-related fixed costs, we have a pretty tight internal control, including headcounts and also the IT spendings there. Thank you.

Right. Thank you. Our next question comes from the line of Alex Yeh from UBS. Please ask your question, Alex.

Hello, Ms. Guan. My question is mainly about pricing. We saw that some of the data on Hongguan this year showed a relatively mild rate of consumption recovery. As we can see, the growth of the bank's overall consumer credit, including the growth in April, is relatively weak. I would like to ask what the current situation is from the perspective of competition, including from various types of competitors. Has the current pressure on us increased? Secondly, do we need to actively increase the price of old clients to promote the growth of loan rates? In summary, what are our expectations for the next year's loan rates? So my question is mainly on the loan pricing outlook. So firstly, in terms of the competitive landscape, we have seen the overall consumption recovery and consumer credit data has been quite modifed. in April, so could you share some color in terms of what's the current trend you have seen regarding the competitive pressure from different players? And secondly, would you consider lowering your loan pricing in order to stimulate some loan drawdown demand from your existing customer base? Thank you.

Okay. Okay, Alex. I'll answer it. From the perspective of competition, I first think that for us, this company, or for this industry, the impact of user demand will be relatively greater than the impact of competition. This is the first point. Second,

Thanks, Alex.

From the competition perspective, we think for our industry, the recovery of the credit amount is more important for the competition. The impact from the recovery of user demand is more important from the impact of the competition.

From the point of view of competition, Um, um um On the other hand, we believe the segmentation of this industry is very clear at this stage.

We are actually quite differentiated from the large banks and also the smaller players. We target different target customers and the pricing segments. So there is limited overlapping among the competitors. And on the other hand, for our stakeholders, service capability, we think we can have a wide coverage of different kind of users. We can cover the lower pricing users and also the higher pricing users. So we can further refine our risk management models to provide differentiated products and offerings to better serve our users. So theoretically, as long as our model is

accurate enough, we can have very strong competitiveness.

From the price point of view, we have actually been using this tool for a long time. We will use this tool for our different customers. This will be based on the model. As long as the model And on pricing perspective,

Actually, we can try some reduced pricing to better activate and engage some of our users. As long as our model is accurate enough, we can better serve them and increase at increased value from this sort of strategy. So from the overall pricing perspective, we think the future pricing will maintain at current level, will maintain a stable level compared to the current level.

Alex, my answer is this. You didn't answer me.

All right, thank you. Our next question comes from the line of Richard Xu from Morgan Stanley. Please go ahead, Richard.

Okay, thank you. I just want to ask about the demand. I don't know what changes we've seen in terms of the demand for this product. We're seeing that the demand for this product So my question is on the long demand, particularly on the sequential change from the potential borrowers in recent months and any divergent trends among the different region groups. of borrowers in terms of loan demand, income growth, and credit quality. Thank you.

Okay. Thank you, Richard. We have also seen this trend. So we think there will be two characteristics. One is called the question and reply. The other is called the doubtful reply. The doubtful reply There will be several aspects. In terms of the area, Jiangsu, Shandong, Hebei, and Shanghai will recover faster. This is relatively consistent with the increase of the RMB loan in each region announced by the country. From the point of view of the customer group, we see that the quality of the customer group is relatively good. In terms of credit amount recovery, we have seen two trends. One is moderate recovery. The other is

Divergent recovery. So, in terms of the diversified recovery, we look at this problem in several aspects. From region perspective, Jiangsu, Shandong, Shanghai, Hebei, those regions are recovering faster than other regions, which is in line with the incremental social financing by regions published by the government in Q1. From customer segment perspective, we have seen higher quality users recovering relatively faster with increasing credit size. And on the other hand, we have seen the broadly defined SME group recovering relatively faster, especially for those from the service industries.

Thank you.

Right. Thank you. We have reached the end of the question and answer session. Thank you very much for all your questions. I'll now turn the conference back to the management team for closing remarks.

Okay. Thank you. Thank you for everyone to join us. If you have additional questions, we can discuss offline. Thank you. Have a good day. Bye-bye.

Thank you. This concludes today's conference call. Thank you for participating. You may now disconnect.