Company: AFRM
Filing Date: 2025-08-28
Form Type: 10-K
Source: 0001820953-25-000080
Chunk: 20

Company: Affirm Holdings, Inc.
Filing Date: 2025-08-28
Form: 10-K
Item: Item 1
Chunk 20
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 that, when triggered, are designed to send a transaction to fraud investigators.

•Credit check capabilities. Our risk model takes five top-of-mind data inputs from the user and turns them into a total of over 500 data points in order to assess the credit risk of new consumers. Our algorithms model out the repayment probability on a month-to-month basis, and combine these probabilities with the term length, purchase size, merchant, and item being purchased, in order to price and score risk. In the vast majority of cases, we can complete these checks and calculations in a matter of seconds, automating the underwriting process pursuant to our originating bank partners’ underwriting policies. We use application and transaction data to train our model, including data from approximately 343 million loans. 

•Modeling improvements. Our high cadence for modeling, retraining, and recalibration translates into rapid improvements to our models over time. New data is regularly used to retrain each model, meaning they continue to improve as the numbers of consumers, merchants, transactions, and repayments we power on our platform grow. We also perform periodic larger scale updates to our core model and algorithms. We regularly introduce new data signals to be captured by our risk analysis system and make them available to be incorporated into new model development, training, and validation. Additionally, we explore opportunities to capture data outside of our model approvals, in order to make a breadth of data available to future models. During these updates, new signals are captured, and older data interrogated and re-tested to help our models continue to evolve. We have automated the process of constructing, training, calibrating, validating, and updating our models, which allow our scientists and engineers to focus on research, flexibility, and speed. Our models are designed to enable us to adjust our models quickly and efficiently in response to changes in the environment. 

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Table of Contents

•Designed for continued innovation and flexibility. Our deep technological talent and capabilities have enabled us to strategically build core systems (including our own ledger) and infrastructure in-house, allowing us to gain what we believe is a significant competitive advantage as we continue to innovate and iterate, and develop new capabilities across multiple disciplines. The flexibility of our custom-built technological infrastructure means we can incorporate new merchants, platforms, data sources, models, capital partnerships, and other elements without necessarily adding significant overhead. 

•Data privacy and security. We store and process data while maintaining robust physical, electronic, and procedural safeguards designed to protect that data. We maintain physical security measures designed