Qifu Technology : 2025 Q1 Presentation

QFIN

Published on 05/19/2025 at 18:43

May 2025

1Q2025 Result Presentation

Strictly Private and Confidential

Our Mission

To Enable a Better Life for People by Facilitating Safe, Convenient and Inclusive Financial Services through Technology Empowerments to Financial Institutions

3

What We Have Achieved in 1Q25

A Leading AI-empowered Credit-Tech Platform in China

Cumulative Users with Approved Credit Lines(1)

Cumulative Financial Institution Partners(1)

RMB88.9 billion

Loan Facilitation Volume in 1Q25

YoY Increase

RMB1,926 million

Non-GAAP Net Income in 1Q25(2)

59.9%

YoY Increase

32.7%

Non-GAAP ROE(3)

5

Notes: (1) Data as of March 31, 2025. (2) Excluding share-based compensation expenses. (3) Non-GAAP ROE refers to (i) the annualized 1Q25 Non-GAAP net income attributed to the Company, divided by (ii) the average shareholder's equity of December 31, 2024 and March 31, 2025.

Significant share count reduction by repurchases

Authorized Repurchase Value and Actual Repurchased Value

(US$ million)

US$905 million

Worth of ADSs repurchased Cumulatively

677

450

350 350

(2)

(1)

150 150

178

227

2023 Plan

2024 Plan

2025 Plan (Ongoing)

2025 Plan (CB, Ongoing)

Authorized repurchase value Actual repurchased value

21.0%

Share count reduction through share repurchase plans(3)

Growing dividend payout

Dividend per ADS

(US$)

1.30

1.08

0.72

0.54

2021

2022

2023

2024

Note: (1) Represents repurchase made from January 1, 2025 to May 19, 2025. (2) Represents the execution of the concurrent share repurchase upon the pricing of the Convertible Senior Notes on March 25, 2025. (3) Share count

reduction refers to (i) the total number of ADSs repurchased from June 20, 2023 to May 19, 2025, divided by (ii) the number of outstanding ADSs as of June 19, 2023, excluding the effects of ESOP. 6

58.4 million

Users with Approved Credit Lines(2)

Our Solutions

163

Financial Institution Partners(2)

Consumers

National Banks

SMEs

Convenient Process

Instant Access to

Credit

Technology

Capital-heavy

facilitation Capital-light

Credit

Borrower Acquisition

Credit Assessment

City/Rural Commercial Banks

Consumer Finance Companies

Personalized Products

ICE(1)

facilitation

Technology solutions

Post-facilitation Services

...

Notes: (1) Refers to Intelligence Credit Engine. (2) Cumulative number as of March 31, 2025. 7

Age

69%(1)< 40

Credit card, mortgage &

auto loan holders

60%(1) (3)

Geography coverage

~81% from tier

3/4 cities(1)

Repeated borrowers'

loan volume contribution

95.1%(2)

Average drawdown

RMB8.6k(2)

Weighted average

contractual tenor

10.2 months(2)

Groceries Electronics

Home improvement

Clothing

Borrowers

Entertainment

Travel

8

Notes: (1) Data based on cumulative users with approved credit lines as of March 31, 2025. (2) 1Q25 data. (3) Refer to the users who possess a credit card or have a mortgage or auto loan, and have made at least one repayment within 6 months prior to the date when the credit line was granted.

Credit-driven Services 2016

Service fees from financial institution partners or interest fees from borrowers for loans funded by Fuzhou Microcredit

Capital-light Model

Intelligent Credit Engine

Technology Solutions

Services Provided

2018 2019

More tech-empowered models

2020

User Acquisition & Preliminary Credit Screening

Matching & Referral

Advanced Credit

Assessment

Credit Risk Taking

Post-facilitation Services

Revenue Model

Service fees from financial institution partners

Service fees from financial institution partners

Technology service fees or consulting fees from financial institution partners

No Involvement High Involvement

9

AI-powered Online Advertising

Partner with leading internet traffic platforms

RTA-DMP Marketing System enables efficient user acquisition

Acquire users across all online life and business scenarios

Embedded Finance

63 embedded finance channel partners, including leading internet traffic platforms / payment / ecommerce / ride-hailing / smart phone companies

/ financial institutions

cumulative users with approved credit lines

cumulative borrowers

Borrower Referral and Offline Promotion

Robust borrower referral programs

On-the-ground sales force targeting users with more sophisticated credit demand

Note: Data as of March 31, 2025. 10

Our Track Record

Loan Facilitation Volume(1)

(RMB billion)

180 Day+ Delinquency Rates by Vintage (2)

(As of March 31, 2025)

4.00%

330.7

322.0

246.8

199.1

96.0

31.0

356.5

369.1

3.50%

3.00%

2.50%

2.00%

1.50%

1.00%

0.50%

2017 2018 2019 2020 2021 2022 2023 2024

0.00%

MOB7 MOB8 MOB9 MOB10 MOB11 MOB12 MOB13 MOB14 MOB15 MOB16 MOB17 MOB18 2020Q1 2020Q2 2020Q3 2020Q4 2021Q1

2021Q2 2021Q3 2021Q4 2022Q1 2022Q2

2022Q3 2022Q4 2023Q1 2023Q2 2023Q3

2023Q4 2024Q1 2024Q2 2024Q3

Note: (1) Refers to the total principal amount of loans facilitated and originated during the given period, including the loan volume under credit driven services, capital-light model, Intelligence Credit Engine ("ICE") and total technology solutions. (2) a percentage, which is equal to (i) the total amount of principal for all loans facilitated by our Group in a fiscal quarter that become delinquent for more than 180 days, less the total amount of recovered past due principal for 11 all loans facilitated by our Group that were delinquent for more than 180 days in the same fiscal quarter, divided by (ii) the total initial principal amount of loans facilitated by our Group in such fiscal quarter; loans under Intelligent Credit

Engine and total technology solutions are not included in the delinquency rate calculation.

Superior AI-driven Credit Assessment Engine (Argus)… … Reinforcing Flywheel Effect

200 mm+ multimodal

customer insights

2,400+ models enabled

with cutting-edge technologies

Proprietary credit

score system output

Fraud detection F-Score

Initial credit assessment A-Score

Behavior monitoring & credit re-evaluation

B-Score

Collection C-Score

Numbers

Texts

Images

Voices

Videos

……

More Borrowers & Loans

More Accurate Credit Assessment

High-quality Growth

More Insights & Training Data

Deeper Collaboration with Financial Institutions

99%+ of loan applications

processed automatically

660k data dimensions

200+ model iterations

Notes: Data as of March 31, 2025 unless otherwise specified. (1) GBST refers to optimized distributed gradient boosting survival trees library that is implemented by Qifu based on XGBoost. (2) MLP refers to 12

Multilayer Perceptron. (3) CNN refers to Convolutional Neural Network. (4) GAT refers to Graph Attention Network.

Machine Learning

Deep Learning

Logistic

Regression

MLP(2)

XGBoost

CNN(3)

GBST(1)

GAT(4)

Random Forest

DragonNet

……

……

Xiao Qi

Intelligent Marketing

74% of graphics & 27% of videos for marketing are generated by AIGC

40% ad placements are automated

25% improvement in user outreach efficiency

10% reduction in average cost per credit line user

User Acquisition

7x24 Personalized Intelligent Services

Accurately understands and predicts users' financial and non-financial needs

Loan Application / Drawdown

Loan Monitoring/ Collection

Copilot

Seamlessly support post-credit service team

Smart user profile recognition

Talking points recommendation

84% usage rate among agents

96.3% recall rate and 98.8% accuracy rate in key information extraction

Research and Development

30% of codes are auto-generated

13

Note: All operating data shown on this page is for the year ended December 31, 2024 unless otherwise specified.

Massive data in digitally available form

for AI-powered business enablement

Millions of repeating credit / repayment events

to train for constantly improving credit assessment

Frictionless customer

experience with

automated loan process

Dramatic

economic wins

for both lenders and consumers

14

Our Vision: Becoming a Respected Global Fintech Company

Fintech Solutions for FIs Overseas Expansion

Core Credit Business in China

15

Consistently Expanding User Base

Cumulative Users with Approved Credit Lines

(million)

Cumulative Borrowers

(million)

35.5

34.4

35.5

31.2

58.4

58.4

52.3

56.9

1Q24 1Q25 4Q24 1Q25 1Q24 1Q25 4Q24 1Q25

17

Loan Facilitation Volume Grew by 15.8% YoY

Loan Facilitation Volume (1)

(RMB billion)

Outstanding Loan Balance (2)

(RMB billion)

53.1%

56.1%

58.1%

56.1%

% of platform services' contribution % of platform services' contribution

49.6%

49.3%

53.2%

49.3%

88.9

89.9

88.9

76.8

140.3

140.3

133.0

137.0

1Q24 1Q25 4Q24 1Q25 1Q24 1Q25 4Q24 1Q25

Notes: (1) Refers to the total principal amount of loans facilitated and originated during the given period, including the loan volume under credit driven services, capital-light model, Intelligence Credit Engine ("ICE") and total technology

solutions. (2) Refers to the total amount of principal outstanding for loans facilitated and originated at the end of each period, including the loan balance under credit-driven services, capital-light model, Intelligence Credit Engine ("ICE")

and total technology solutions, excluding loans delinquent for more than 180 days. 18

Solid Profitability Driven by Optimized Efficiency

Total Net Revenue

(RMB million)

Non-GAAP Net Income (1)

(RMB million)

1,926

1,972

1,926

1,205

4,691

4,482

4,691

4,153

1Q24 1Q25 4Q24 1Q25

1Q24 1Q25 4Q24 1Q25

Notes: (1) Excluding share-based compensation expenses. 19

Operating Expenses

Facilitation, Origination and

Servicing Expense

(% of Loan Facilitation Volume(1))

Sales and Marketing Expense

(% of Loan Facilitation Volume(1))

User Acquisition Costs(RMB)(2)

General and Administrative Expense

(% of Loan Facilitation Volume(1))

285

384

312

384

0.96%

0.80%

0.82%

0.80%

0.67% 0.67%

0.54%

0.58%

0.22%

0.22%

0.14%

0.17%

1Q24 1Q25 4Q24 1Q25

1Q24 1Q25 4Q24 1Q25

1Q24 1Q25 4Q24 1Q25

Note: (1) Refers to the total principal amount of loans facilitated and originated during the given period, including the loan volume under credit driven services, capital-light model, Intelligence Credit Engine ("ICE") and total technology

solutions. (2) Acquisition cost per user with approved credit lines. 20

Robust Risk Performance

92.3% 92.0% 91.7%

88.5%

89.6% 90.4% 90.3% 90.8% 89.3%

87.5%

87.1%

86.0% 85.8%

86.4%

86.2% 87.2% 86.7%

84.0%

84.7%

84.9% 85.1%

86.3% 87.4% 88.1% 88.1%

7.3%

6.4% 6.4% 6.4% 6.8%

6.2%

5.3% 5.2% 5.0% 5.0% 5.1% 5.4% 5.2% 4.9%

4.5% 4.3% 4.1% 4.2% 4.6%

5.0% 4.9% 4.8%

4.6%

4.8% 5.0%

18.0% 100.0%

15.0% 90.0%

12.0% 80.0%

9.0% 70.0%

6.0% 60.0%

3.0%

1Q19 2Q19 3Q19 4Q19 1Q20 2Q20 3Q20 4Q20 1Q21 2Q21 3Q21 4Q21 1Q22 2Q22 3Q22 4Q22 1Q23 2Q23 3Q23 4Q23 1Q24 2Q24 3Q24 4Q24 1Q25

50.0%

D1 Delinquency Rate (1) 30 Day Collection Rate (2)

21

Notes: (1) D1 delinquency rate is defined as (i) the total amount of principal that became overdue as of a specified date, divided by (ii) the total amount of principal that was due for repayment as of such date. (2) 30 day collection rate is defined as (i) the amount of principal that is repaid in one month among the total amount of principal that is overdue as of a specified date, divided by (ii) the total amount of principal that is overdue as of such specified date.

Disclaimer

Qifu Technology Inc. published this content on May 19, 2025, and is solely responsible for the information contained herein. Distributed via Public Technologies (PUBT), unedited and unaltered, on May 19, 2025 at 22:42 UTC.