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Cango Inc. Reports First Quarter 2025 Unaudited Financial Results

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Cango Inc. Reports First Quarter 2025 Unaudited Financial Results

Mr. Yongyi Zhang, Chief Financial Officer of Cango, stated, “We are pleased to report another solid financial performance this quarter, highlighted by total revenue of RMB1.1 billion and a strong balance sheet. We also continued to reduce our credit risk exposure, further bolstering our financial position and flexibility. Supported by this robust foundation, we are well-positioned to expand the Bitcoin mining business and holistically drive the Company’s growth.”

First Quarter 2025 Financial Results

REVENUES

Total revenues in the first quarter of 2025 were RMB1.1 billion (US$145.2 million), compared with RMB64.4 million in the same period of 2024. The significant year-over-year increase was primarily driven by the Bitcoin mining business launched in November 2024.

Revenue from the Bitcoin mining business was RMB1.0 billion (US$144.2 million), with a total of 1,541 Bitcoins mined in the first quarter of 2025.

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Revenue from automotive trading-related income[1] was RMB7.6 million (US$1.0 million), compared with RMB64.4 million in the same period of 2024.

OPERATING COSTS AND EXPENSES

Total operating costs and expenses in the first quarter of 2025 were RMB1.2 billion (US$166.7 million). These costs were primarily associated with our Bitcoin mining business.

  • Cost of revenue in the first quarter of 2025 was RMB955.1 million (US$131.6 million), compared with RMB29.1 million in the same period of 2024.

  • Sales and marketing expenses in the first quarter of 2025 were RMB415,981 (US$57,324), compared with RMB3.5 million in the same period of 2024.

  • General and administrative expenses in the first quarter of 2025 were RMB92.5 million (US$12.8 million), compared with RMB37.9 million in the same period of 2024.

  • Research and development expenses in the first quarter of 2025 were RMB324,991 (US$44,785), compared with RMB1.1 million in the same period of 2024.

  • Net gain on contingent risk assurance liabilities in the first quarter of 2025 was RMB5.3 million (US$726,124), compared with RMB15.0 million in the same period of 2024.

  • Net recovery on provision for credit losses in the first quarter of 2025 was RMB28.7 million (US$4.0 million), compared with RMB66.3 million in the same period of 2024.

INCOME (LOSS) FROM OPERATIONS

Loss from operations in the first quarter of 2025 was RMB155.5 million (US$21.4 million) compared with income from operations of RMB74.2 million in the same period of 2024.

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NET INCOME (LOSS) AND NET INCOME (LOSS) PER ADS

Net loss in the first quarter of 2025 was RMB207.4 million (US$28.6 million) compared with net income of RMB90.0 million in the same period of 2024. Basic and diluted net loss per American Depositary Share (the “ADS”) in the first quarter of 2025 were both RMB2.00 (US$0.28). Each ADS represents two Class A ordinary shares of the Company.

ADJUSTED EBITDA

Adjusted EBITDA in the first quarter of 2025 was RMB27.6 million (US$3.8 million) compared with RMB108.4 million in the same period of 2024.

BALANCE SHEET

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  • As of March 31, 2025, the Company had cash and cash equivalents of RMB2.5 billion (US$346.7 million) compared with RMB1.3 billion as of December 31, 2024.

  • As of March 31, 2025, the Company had short-term investments of RMB5.2 million (US$715,049) compared with RMB1.2 billion as of December 31, 2024.

Business Outlook

We currently maintain a deployed hashrate of 32 EH, demonstrating our operational resilience. As part of our continued commitment to growth and scaling our capabilities, we are targeting a substantial increase in our hashrate over the coming months. We are on track to grow our deployed hashrate to approximately 50 EH before the end of July. This increase is expected to be driven by the closing of our share-settled acquisition of Bitcoin mining assets, positioning us to strengthen our competitive advantage and increase operational efficiency.

Share Repurchase Program

Pursuant to the share repurchase program announced on April 23, 2024, the Company had repurchased 996,640 ADSs with cash in the aggregate amount of approximately US$1.7 million as of April 25, 2025, the day on which the program expired.

Conference Call Information

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The Company’s management will hold a conference call on Wednesday, May 14, 2025, at 9:00 P.M. Eastern Time or Thursday, May 15, 2025, at 9:00 A.M. Beijing Time to discuss the financial results. Listeners may access the call by dialing the following numbers:

International:

+1-412-902-4272

United States Toll Free:

+1-888-346-8982

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Mainland China Toll Free:

4001-201-203

Hong Kong, China Toll Free:

800-905-945

Conference ID:

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Cango Inc.

The replay will be accessible through May 21, 2025, by dialing the following numbers:

International:

+1-412-317-0088

United States Toll Free:

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+1-877-344-7529

Access Code:

8016651

A live and archived webcast of the conference call will also be available at the Company’s investor relations website at http://ir.cangoonline.com.

About Cango Inc.

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Cango Inc. (NYSE: CANG) primarily operates a leading Bitcoin mining business. Cango has deployed its mining operation across strategic locations including North America, Middle East, South America, and East Africa. Cango expanded into the crypto assets market in November 2024, driven by the development in blockchain technology, increasing prevalence of crypto assets and its endeavor to diversify its business. Meanwhile, Cango has continued to operate the automotive transaction service in China since 2010, aiming to make car purchases simple and enjoyable. For more information, please visit: www.cangoonline.com.

Definition of Overdue Ratios

The Company defines “M1+ overdue ratio” as (i) exposure at risk relating to financing transactions for which any installment payment is 30 to 179 calendar days past due as of a specified date, divided by (ii) exposure at risk relating to all financing transactions which remain outstanding as of such date, excluding amounts of outstanding principal that are 180 calendar days or more past due.

The Company defines “M3+ overdue ratio” as (i) exposure at risk relating to financing transactions for which any installment payment is 90 to 179 calendar days past due as of a specified date, divided by (ii) exposure at risk relating to all financing transactions which remain outstanding as of such date, excluding amounts of outstanding principal that are 180 calendar days or more past due.

Use of Non-GAAP Financial Measure

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As part of our review of business performance, we present adjusted EBITDA as Non-GAAP financial measure to help assess our core operating results. Adjusted EBITDA is defined as net income before interest, taxes, depreciation, and amortization, and further excludes share-based compensation expenses and other non-operating income and expenses. We believe Adjusted EBITDA can be an important financial measure because it allows management, investors, and our board of directors to evaluate and compare our operating results, including our return on capital and operating efficiency from period-to-period by making such adjustments.

While adjusted EBITDA is not a measure defined under U.S. GAAP, management uses it to evaluate performance, make strategic decisions, and set operating plans. Management believes it also helps investors gain a clearer understanding of our underlying performance by excluding certain costs and expenses that management believes are not indicative of its core operating results. The presentation of these non-GAAP financial measures is not meant to be considered in isolation or as a substitute for results or guidance prepared and presented in accordance with U.S. GAAP.

The Company compensates for these limitations by reconciling the Non-GAAP financial measure to the nearest U.S. GAAP performance measure, all of which should be considered when evaluating the Company’s performance. The Company encourages you to review its financial information in its entirety and not rely on a single financial measure.

Reconciliations of Cango’s Non-GAAP financial measure to the most comparable U.S. GAAP measure are included at the end of this press release.

Exchange Rate Information

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This announcement contains translations of certain RMB amounts into U.S. dollars (“US$”) at specified rates solely for the convenience of the reader. Unless otherwise stated, all translations from RMB to US$ were made at the rate of RMB7.2567 to US$1.00, the noon buying rate in effect on March 31, 2025, in the H.10 statistical release of the Federal Reserve Board. The Company makes no representation that the RMB or US$ amounts referred could be converted into US$ or RMB, as the case may be, at any particular rate or at all.

Safe Harbor Statement

This announcement contains forward-looking statements. These statements are made under the “safe harbor” provisions of the United States Private Securities Litigation Reform Act of 1995. These forward-looking statements can be identified by terminology such as “will,” “expects,” “anticipates,” “future,” “intends,” “plans,” “believes,” “estimates” and similar statements. Among other things, the “Business Outlook” section and quotations from management in this announcement, contain forward-looking statements. Cango may also make written or oral forward-looking statements in its periodic reports to the SEC, in its annual report to shareholders, in press releases and other written materials and in oral statements made by its officers, directors or employees to third parties. Statements that are not historical facts, including statements about Cango’s beliefs and expectations, are forward-looking statements. Forward-looking statements involve inherent risks and uncertainties. A number of factors could cause actual results to differ materially from those contained in any forward-looking statement, including but not limited to the following: Cango’s goal and strategies; Cango’s expansion plans; Cango’s future business development, financial condition and results of operations; Cango’s expectations regarding demand for, and market acceptance of, its solutions and services; Cango’s expectations regarding keeping and strengthening its relationships with dealers, financial institutions, car buyers and other platform participants; general economic and business conditions; and assumptions underlying or related to any of the foregoing. Further information regarding these and other risks is included in Cango’s filings with the SEC. All information provided in this press release and in the attachments is as of the date of this press release, and Cango does not undertake any obligation to update any forward-looking statement, except as required under applicable law.

Investor Relations Contact

Yihe Liu
Cango Inc.
Tel: +86 21 3183 5088 ext.5581
Email: ir@cangoonline.com

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Helen Wu
Piacente Financial Communications
Tel: +86 10 6508 0677
Email: ir@cangoonline.com

[1] Revenue from automotive trading related income consists revenues generated from loan facilitation income and other related income, guarantee income, leasing income, after-market services income, automotive trading income and others.

 

CANGO INC.
UNAUDITED INTERIM CONDENSED CONSOLIDATED BALANCE SHEET
(Amounts in Renminbi (“RMB”) and US dollar (“US$”), except for number of shares and per share data

 As of December 31,
2024 

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As of March 31,
2025

 (Audited) 

(Unaudited)

(Unaudited)

 RMB 

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 RMB 

 US$ 

ASSETS:

Current assets:

Cash and cash equivalents

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1,289,629,981

2,515,712,358

346,674,433

Restricted cash – current

10,813,746

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11,210,722

1,544,879

Short-term investments, net

1,231,171,751

5,188,899

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715,049

Accounts receivable, net

22,991,951

15,801,108

2,177,451

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Finance lease receivables – current, net

20,685,475

19,332,969

2,664,154

Financing receivables, net

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5,685,096

3,722,236

512,938

Short-term contract asset, net

33,719,944

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19,860,987

2,736,917

Prepayments and other current assets, net 

226,352,004

362,016,043

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49,887,145

Receivable for bitcoin collateral, net

617,057,765

1,464,654,137

201,834,737

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Total current assets

3,458,107,713

4,417,499,459

608,747,703

Non-current assets:

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Restricted cash – non-current

287,425,602

161,939,581

22,315,871

Long-term investment

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400,000,000

55,121,474

Mining machines, net

1,772,319,041

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1,619,608,093

223,187,963

Property and equipment, net

6,634,509

6,205,894

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855,195

Intangible assets, net

47,425,617

47,259,479

6,512,530

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Long-term contract asset, net

17,551,040

348,864

48,075

Finance lease receivables – non-current, net

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9,309,227

3,648,111

502,723

Operating lease right-of-use assets, net

40,788,977

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38,789,517

5,345,338

Other non-current assets, net

329,761,833

359,761,832

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49,576,506

Total non-current assets

2,511,215,846

2,637,561,371

363,465,675

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TOTAL ASSETS

5,969,323,559

7,055,060,830

972,213,378

LIABILITIES AND SHAREHOLDERS’ EQUITY

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Current liabilities:

Short-term debts

124,584,293

790,393,522

108,919,140

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Accrued expenses and other current liabilities

1,348,300,779

1,999,990,186

275,606,016

Deferred guarantee income

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11,787,712

7,974,712

1,098,945

Contingent risk assurance liabilities 

31,190,425

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20,979,625

2,891,070

Income tax payable

311,130,341

314,258,152

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43,305,931

Short-term lease liabilities

7,912,420

7,639,264

1,052,719

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Total current liabilities

1,834,905,970

3,141,235,461

432,873,821

Non-current liabilities:

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Deferred tax liability

10,724,133

10,724,133

1,477,825

Long-term operating lease liabilities

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37,044,466

35,769,502

4,929,169

Other non-current liabilities

19,118

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18,131

2,499

Total non-current liabilities

47,787,717

46,511,766

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6,409,493

Total liabilities

1,882,693,687

3,187,747,227

439,283,314

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Shareholders’ equity

Ordinary shares

199,087

199,087

27,434

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Treasury shares

(756,517,941)

(754,199,105)

(103,931,416)

Additional paid-in capital

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4,725,877,432

4,749,907,787

654,554,796

Accumulated other comprehensive income

152,882,024

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114,572,087

15,788,456

Accumulated deficit

(35,810,730)

(243,166,253)

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(33,509,206)

Total Cango Inc.’s equity

4,086,629,872

3,867,313,603

532,930,064

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Total shareholders’ equity

4,086,629,872

3,867,313,603

532,930,064

TOTAL LIABILITIES AND SHAREHOLDERS’ EQUITY

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5,969,323,559

7,055,060,830

972,213,378

 

 

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CANGO INC.
UNAUDITED INTERIM CONDENSED CONSOLIDATED STATEMENTS OF
COMPREHENSIVE INCOME (LOSS)
(Amounts in Renminbi (“RMB”) and US dollar (“US$”), except for number of shares and per share data)

 Three months ended March 31 

2024

2025

 (Unaudited) 

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 (Unaudited) 

 (Unaudited) 

 RMB 

 RMB 

 US$ 

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Revenues

64,422,494

1,053,883,166

145,228,984

Bitcoin mining income

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1,046,266,997

144,179,448

Loan facilitation income and other related income 

13,821,022

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(829,251)

(114,274)

Guarantee income 

30,259,581

4,043,650

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557,230

Leasing income

4,939,712

2,088,483

287,801

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After-market services income 

11,637,788

776,803

107,046

Automobile trading income

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3,445,040

70,796

9,756

Others

319,351

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1,465,688

201,977

Operating cost and expenses:

Cost of revenue

29,058,868

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955,091,082

131,615,070

Sales and marketing

3,548,273

415,981

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57,324

General and administrative

37,923,531

92,536,718

12,751,901

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Research and development

1,098,105

324,991

44,785

Net gain on contingent risk assurance liabilities

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(15,018,246)

(5,269,261)

(726,124)

Net recovery on provision for credit losses

(66,339,084)

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(28,702,162)

(3,955,264)

Loss from change in fair value of receivable for bitcoin collateral

194,957,999

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26,865,931

Total operation cost and expense

(9,728,553)

1,209,355,348

166,653,623

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(Loss) income from operations

74,151,047

(155,472,182)

(21,424,639)

Interest income

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16,503,965

2,152,469

296,618

Net investment income

10,984,524

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Interest expense

(9,517,781)

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(1,311,585)

Foreign exchange gain (loss), net

131,689

(818,002)

(112,724)

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Other income

832,551

13,609,872

1,875,491

Other expenses

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(535,390)

(54,180,931)

(7,466,332)

Net income (loss) before income taxes

102,068,386

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(204,226,555)

(28,143,171)

Income tax expense

(12,041,600)

(3,128,968)

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(431,183)

Net income (loss)

90,026,786

(207,355,523)

(28,574,354)

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Net income (loss) attributable to Cango Inc.’s shareholders

90,026,786

(207,355,523)

(28,574,354)

Earnings (losses) per ADS attributable to ordinary shareholders:

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Basic

0.85

(2.00)

(0.28)

Diluted

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0.80

(2.00)

(0.28)

Weighted average ADS used to compute earnings per ADS attributable to
ordinary shareholders:

Basic

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105,521,018

103,783,087

103,783,087

Diluted

112,786,810

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103,783,087

103,783,087

Other comprehensive income (loss), net of tax

Foreign currency translation adjustment

20,894,928

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(38,309,937)

(5,279,250)

Total comprehensive income (loss)

110,921,714

(245,665,460)

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(33,853,604)

Total comprehensive income (loss) attributable to Cango Inc.’s shareholders

110,921,714

(245,665,460)

(33,853,604)

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CANGO INC.
RECONCILIATIONS OF GAAP AND NON-GAAP RESULTS
(Amounts in Renminbi (“RMB”) and US dollar (“US$”), except for number of shares and per share data

 Three months ended March 31 

2024

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2025

 (Unaudited) 

 (Unaudited) 

 (Unaudited) 

 RMB 

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 RMB 

 US$ 

Net (loss) income

90,026,786

(207,355,523)

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(28,574,354)

Add: Interest expense

9,517,781

1,311,585

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Add: Income tax expenses

12,041,600

3,128,968

431,183

Add: Depreciation and amortization

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927,576

155,503,915

21,429,012

Cost of revenue

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154,944,205

21,351,882

General and administrative

879,591

559,710

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77,130

Research and development

47,985

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Add: Other expenses

535,390

54,180,931

7,466,332

Less: Other income

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832,551

13,609,872

1,875,491

Add: Share-based compensation expenses

5,717,422

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26,187,822

3,608,778

Cost of revenue

254,391

58,766

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8,098

Sales and marketing

1,046,659

339,524

46,788

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General and administrative

4,416,372

25,783,442

3,553,053

Research and development

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6,090

839

Non-GAAP adjusted EBITDA

108,416,223

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27,554,022

3,797,045

Non-GAAP adjusted EBITDA attributable to Cango Inc.’s shareholders

108,416,223

27,554,022

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3,797,045

 

 

Cision

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SOURCE Cango Inc.

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Finance

4 Smart Ways to Use Your Tax Return for Financial Planning

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4 Smart Ways to Use Your Tax Return for Financial Planning

(Image credit: Getty Images)

In my work helping people think through retirement planning decisions, I often see people focus heavily on preparing their tax return but spend very little time reviewing it afterward.

By the time tax season ends, most people treat the document like a receipt: They file it, save a copy somewhere and move on.

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The CFO who turned Adobe’s finance department into an AI lab | Fortune

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The CFO who turned Adobe’s finance department into an AI lab | Fortune

Finance chief Dan Durn is turning Adobe’s finance organization into an early proving ground for agentic AI—using autonomous software agents to forecast results, scan contracts, and even answer hundreds of thousands of emails.

The push mirrors Adobe’s broader strategy around agentic AI. For customers, the company lets them choose models, combine them with their own data and Adobe’s, and point agents at specific business outcomes.

Internally, Durn, who is also in charge of technology, security and operations, has taken a similar approach to finance: pairing a rules-based, data-heavy function with AI, within a structure where finance, IT, and security report to one leader so pilots can move to production quickly. “Accuracy is non-negotiable,” he adds; that’s why Adobe is investing in structured data and governance so it can move fast without sacrificing precision, he says. 

The rise of AI is rapidly reshaping corporate leadership, accelerating turnover and elevating executives who can deliver fast, tangible results. Even long-tenured leaders face increasing pressure from investors to move aggressively on AI. Recent leadership changes, including the announced retirement of Adobe CEO Shantanu Narayen, highlight how little patience markets now have for perceived hesitation. At the same time, Adobe reported that annualized revenue from its AI-first products more than tripled year over year in its first quarter of fiscal 2026, which ended Feb. 27. Across Fortune 500 companies, this dynamic is creating a new internal proving ground where executives are judged by how effectively, and how quickly, they deploy AI to drive growth, efficiency, and innovation.

Using AI in finance

Inside finance, Durn groups AI use into three buckets: forecasting, anomaly detection, and general productivity.

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For forecasting, AI uncovers patterns and signals in data that would be difficult for humans to detect quickly, he explains. Anomaly-detection agents flag performance that’s unexpectedly strong or weak—“things that can get lost in the sea of data”—so finance can intervene faster, he says.

However, Durn says the best examples now sit in productivity, citing three use cases:

1. Extracting information from PDFs

One of the most developed use cases involves “containers” of information—collections of PDFs such as investor transcripts, quarterly reports, and analyst research. Finance teams use Adobe’s PDF Spaces to load documents into a shared digital workspace and use an agentic AI assistant to surface themes, insights, and messaging cues in minutes rather than hours.

A recent Forrester TEI study found Acrobat’s agentic AI Assistant increases efficiencies in document summarization and analysis by 45%. Durn says that matters because “the world’s information lives in PDF,” and AI that turns static content into insights that can be used.

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2. Cutting contract review time in half

Adobe is also using agentic AI to overhaul contract reviews across finance and procurement functions including revenue assurance, contract operations, product fulfillment, and vendor management. Instead of finance professionals combing through every clause, an AI assistant scans thousands of contracts, highlights provisions relevant to each function, and flags non-standard terms.

The system has cut review time roughly in half, speeding individual reviews and allowing teams to query the entire contract repository—for example, identifying which contracts include auto-cancellation features or foreign-exchange adjustment windows, Durn says. Adobe built its first prototype by April 2024 and began onboarding teams in January 2025.

3. Automating “common” inboxes

A third area is the “common inboxes” that handle high-volume internal and external email—shared addresses for sales, treasury, finance, and supplier questions. Adobe deployed an agentic AI assistant that auto-tags, prioritizes, routes, and, when criteria are met, auto-responds to emails. Typical queries include supplier billing issues or standard credit-quality questions coming into the treasury from Salesforce.

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“In 2025 alone, the system auto-responded to about 300,000 emails across 19 inboxes, saving more than 5,000 hours of manual work and freeing teams to focus on more complex issues,” he says. The tool took about six months to build; beta teams began using it around August 2024, with full rollout in January 2025.

The payoff, he stresses, isn’t headcount cuts but the ability to scale more efficiently as Adobe grows.

Grassroots ideas, decade-long build

Durn traces these finance use cases to Adobe’s long AI journey and a bottom-up idea pipeline. The company has invested in machine learning and AI for more than a decade, initially to understand customer usage patterns and embed intelligence into products—work that laid the groundwork for generative and agentic AI.

Many of the best applications come from “reaching down into the organization” and asking employees where AI could remove friction or make their jobs easier, he says. There are more ideas than capacity, so the team prioritizes those with the greatest impact.

When deciding whether to green-light AI investments, Durn focuses on organizational velocity—the ability of back-office functions to keep pace with faster product innovation. If finance doesn’t adopt AI, he argues, it risks becoming a “rate limiter of growth.”

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The actual spend is modest, he adds; much of the work involves change management and process redesign layered onto Adobe’s technology.

Durn’s perspective on change management coincides with new research from McKinsey. To capture the full value of AI, organizations need to go beyond “a piecemeal approach and push for a double transformation—both technical and organizational—that includes reimagining how work gets done across functions and workflows,” according to the report. While 88% of organizations surveyed are now experimenting with AI, fewer than 20% report tangible bottom-line results,, the research finds.

How AI is changing his own job

For his own workflow, Durn relies on AI primarily for insight generation. Ahead of earnings, his team loads pre-earnings research reports, Adobe filings, and peer transcripts into an AI-powered workspace to surface themes and likely investor questions.

Scripts and Q&A preparation are then run through models with guardrails to test whether messaging addresses those themes and to ask, “If I were an investor, what are my key takeaways?”

He sees it as a useful check on clarity and consistency—using AI to validate instincts and sharpen how Adobe communicates with the market.

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UST Finance Students Compete on Global Stage in CFA Research Challenge

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UST Finance Students Compete on Global Stage in CFA Research Challenge

A select team of students from the University of St. Thomas’ Cameron School of Business has officially launched its bid for the FY 2025–2026 Texas Region CFA (Certified Financial Analyst) Institute Research Challenge, a prestigious competition often referred to as the “Investment Olympics” for university students. 

The CFA Institute Research Challenge is an annual competition that provides university students with hands-on mentoring and intensive training in financial analysis. The competition tests students’ analytical, valuation, report writing and presentation skills, challenging them to take on the role of real-world research analysts. The 2025–2026 cycle involves more than 6,000 students from more than1,000 universities worldwide. 

Representing UST, the team is comprised of Team Captain Chih Jung Ting, MSF; Vice-Captain Daria Kostyukova, BBA/MSF; Reginald Paolo Laudato, BBA/MSF; Simon Wong, BBA in Finance; and Anjali Sebastian, BBA in Finance. 

Anjali Sebastian

The team of five students has been selected to conduct an exhaustive equity analysis of a target company, competing against top-tier universities from around the Texas area. 

“Taking part in the CFA Research Challenge has been the most intense and rewarding experience of my academic career,” said Chih Jung Ting, team captain. “We aren’t just reading case studies anymore—we are digging into real balance sheets, forecasting real economic shifts, and learning how to defend our ideas under pressure. It’s given us a true taste of what it means to be an analyst.” 

The team is supported by Department Chair of Economics and Finance Dr. Joe Ueng, CFA, and faculty advisor Dr. Dan Hu. Assisting the team was industry mentor Matt Caire, CFA, CFP®, CMT from Vaughan Nelson, a seasoned professional who provides guidance on the intricacies of equity research. 

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“Our participation in the CFA Research Challenge is a testament to the caliber of our students and the strength of our curriculum,” said Dr. Ueng. “By applying advanced financial theory to a live market scenario, our students demonstrate that they are not just learners, but emerging professionals ready to contribute to the global financial community. We are incredibly proud of their dedication to academic excellence.” 

Dr. Sidika Gülfem Bayram, the Cullen Foundation Endowed Chair of Finance and UST associate professor of Finance said participating in the CFA Research Challenge this year creates a pivotal moment for UST students.  

“I’m impressed to see our students apply their curriculum knowledge to meet the depth and vast nature of the analysis required in such a fierce competition,” Dr. Bayram said. “I’m so proud of the effort the students put into the challenge.” 

This year, the team has been tasked with analyzing Green Brick Partners, a publicly traded company in the consumer cyclical sector. During the past several months, the students have dedicated more than 150 hours to conducting a deep-dive analysis of the company’s business model and industry position, interviewing company management and financial experts, building complex financial models to determine the stock’s intrinsic value, and compiling an “Initiation of Coverage” report with a buy, sell or hold recommendation. 

“Participating in the CFA Research Challenge allows our students to bridge the gap between classroom theory and the fast-paced world of investment management,” said Dr. Hu. “It demands a level of rigor and professional ethics that prepares them for the highest levels of the finance industry.” 

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The team will presented its findings and defended its recommendation before a panel of judges from leading investment firms at the CFA Society local final in late February. Winners of the local competition will advance to the subregional and regional rounds, with the goal of reaching the global finals in May 2026. 

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