Affirm Stock Surges After New AI Model Boosts Purchase Completions

Shares of Affirm Holdings Inc. (NASDAQ:AFRM) rose 5.5% in premarket trading Thursday after the company announced the launch of a new artificial intelligence model for its loan underwriting process that has already increased transaction volumes.

AI Model Increases Approvals

Affirm said it has deployed a new transformer-based AI model for making real-time loan decisions at checkout in the U.S. The model analyzes patterns in a consumer's credit history, drawing on 14 years of the company's proprietary transaction data.

In its initial deployment, the model approved additional eligible applicants that Affirm's previous system would have declined. The company reported this resulted in 3.4% more completed purchases compared to a control group. Crucially, Affirm noted that these additional loans performed better than a comparable expansion under its prior machine learning models, suggesting improved credit quality alongside higher volume.

Technology and Strategy

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The new technology is designed to better serve consumers with limited credit histories or no FICO scores. "What’s exciting about the transformer model architecture is that we can now find new information within the data we already have," said Libor Michalek, Affirm's President. "Seeing a credit history more clearly means we can responsibly say yes to more people."

Affirm stated it developed a proprietary algorithm to maintain the model's speed for real-time decisions while ensuring its logic remains explainable. The company emphasized its goal is to make responsible credit decisions, as extending loans that cannot be repaid is not a sustainable business practice.

Market Implications

The positive stock reaction suggests investors see the new technology as a key driver for growth. By expanding its approval base without sacrificing credit performance, Affirm could increase its Gross Merchandise Volume (GMV), a critical metric for payment-processing companies. The ability to underwrite a wider range of customers, particularly those underserved by traditional credit scoring, could provide a significant competitive advantage in the crowded buy-now, pay-later market.