Company: RSKD
Filing Date: 2025-03-06
Form Type: 20-F
Source: 0001851112-25-000006
Chunk: 9

Company: RISKIFIED LTD.
Filing Date: 2025-03-06
Form: 20-F
Item: Item 3
Chunk 9
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 are inherently difficult to predict or are otherwise beyond our control, such as social engineering and other methods of perpetrating fraud, including through the use of generative artificial intelligence or other emerging technologies, that do not lend themselves well to risk-based analysis. Material errors or inaccuracies in such machine learning models could lead us to make inaccurate or sub-optimal operational or strategic decisions, which could adversely affect our business, financial condition and results of operations. Our inability to train our models or develop new technology that can detect new fraud schemes may also result in significant chargeback expenses, which would materially and adversely impact our business, financial condition, and results of operations.

The data gathering for, and development of, our machine learning models havepredominantly occurred during a period of sustained economic growth, and our machine learning models have not been extensively tested during a down-cycle economy or recession. For example, consumer spending patterns, transaction volumes and fraud patterns experienced during a down-cycle economy or recession may differ from those experienced during periods of sustained economic growth. There is no assurance that our machine learning models can continue to accurately detect fraud under adverse economic conditions. If our machine learning models are unable to accurately detect fraud under such economic conditions, the performance of our product may be worse than anticipated and we may be required to issue a significant amount of credits as a result of valid chargebacks, which would adversely affect our business, financial condition and results of operations.

Our CTB Ratio and gross profit margin have historically and may in the future fluctuate from quarter-to-quarter, which makes these metrics difficult to predict. These metrics are managed, and should be analyzed, on an annual basis.

Our CTB Ratio, which we use to evaluate the performance of our business operations and the effectiveness of our models, and gross profit margin are managed, and are best analyzed, on an annual basis. Historically, our CTB Ratio and gross profit margin have fluctuated between periods, and we expect that these financial metrics will continue to fluctuate between periods in the future, based on a number of factors, including changes in the mix of our merchant industry base, our entry into new geographies and industries, changes in the mix of credit and debit card transactions and transactions made via alternative payment methods, the risk profile of orders approved in the period, technological improvements in the performance of our models, seasonality, large-scale merchant fraud events or security incidents, expansion into other use-cases and other factors. For example, our CTB Ratio and gross profit margins are sometimes negatively impacted in the first several quarters