‘Small banks will have smaller losses, big banks will have bigger losses,’ says Klarna CEO

Key Concepts

• Klarna's Financial Performance: Net loss, provisions for credit losses, revenue growth, merchant growth, transaction margins.
• Underwriting and Credit: Issuance of credit, basis points for losses, loan duration, cost booking.
• Business Strategy: Investment phase, profitability timeline, licensing (Europe vs. US).
• Klarna Card: Debit and credit functionality, perks (cashback), user demand, waitlist.
• Artificial Intelligence (AI): Compute needs, data compression, proprietary data, cost optimization, potential market implications.

Klarna's Post-IPO Performance and Financials

Klarna, a fintech company, has experienced a significant stock price decline of 9% shortly after its initial public offering (IPO) on the New York Stock Exchange in September. This drop occurred despite the company reporting record third-quarter revenue of $903 million and achieving 4 million sign-ups for its debit card. The primary driver for the stock plunge was the company's net loss of $95 million, coupled with a substantial increase in provisions for credit losses, which climbed to $235 million.

Sebastian Siemiatkowski's Perspective on Klarna's Financials

Klarna CEO Sebastian Siemiatkowski highlighted positive growth metrics, particularly in the US, with 50% growth on an annual open quarter basis, and 28% group-level growth. He addressed the company's continued losses by emphasizing their underwriting success. Klarna has issued over half a trillion dollars in credit, with average losses below 70 basis points, a figure Siemiatkowski claims is superior to traditional banks. He explained that while absolute loss numbers may increase with scale, the portfolio remains healthy.

Siemiatkowski also discussed the shift in lending duration, noting a 140% growth in loans with durations of one to two years. He clarified that Klarna books costs upfront and recognizes revenue over the loan's term, leading to a planned profit lag on the bottom line due to provisioning for a growing loan book.

Merchant and User Growth

The transcript mentions significant growth in Klarna's merchant base, with 235,000 new merchants added, bringing the total to 850,000. Despite these positive numbers, investor sentiment has been negative, prompting questions about Klarna's path to profitability and the timeline for achieving it.

Klarna's Investment Phase and Profitability Outlook

Siemiatkowski stated that Klarna has been in an investment phase for the first 14 years of its existence (2005-2019). He asserted that gross margins, specifically transaction margins, have consistently been around 50% to 60%, and are in the "2030s" in the US, indicating a solid and profitable underlying business. The current losses are attributed to provisioning for their book and short-term implications. He expressed confidence in the business's momentum and financial improvements, anticipating future profitability.

Licensing and Expansion

Klarna currently holds a banking charter in Europe but not in the United States. Siemiatkowski acknowledged the increasing importance of licensing in the AI-driven world and indicated that obtaining a US banking license is a likely future development, aligning with market trends. He noted that Klarna has crossed market thresholds in New York, with the exception of the UK, and is pursuing more licenses in the US.

The Klarna Card and User Demand

The Klarna Card, launched with a significant waitlist, has seen immense popularity with 4 million cardholders. Siemiatkowski explained the card's dual functionality (debit and credit) and its evolution to include perks like cashback, making it highly attractive. He described the overwhelming demand, with customers physically bringing in old cards to be cut up, highlighting the success of the launch and the high number of active users.

AI and Investor Anxiety

Siemiatkowski shared his perspective on Artificial Intelligence (AI), acknowledging its value and the potential for many companies to thrive. However, he expressed anxiety regarding the massive investments in computing power for AI. He pointed out the paradox of highly complex AI models fitting onto small devices due to data compression, which can lead to a loss of precision and accuracy.

He raised concerns about the implications of this compression when applied to proprietary data, suggesting it might reduce the need for extensive computing power. While not suggesting a drastic reduction in computers, Siemiatkowski is sensitive to the potential for AI's impact on computing needs to be less significant than some anticipate. This sentiment echoes concerns voiced by other industry leaders, such as Alphabet's CEO, and is reflected in a market shift in sentiment.