Square, Inc.

Block, Inc.

Nicholas Halpern

Joachim Bekmann

In some examples, a system may receive first merchant data for a first merchant. For instance, the first merchant data may include one or more merchant characteristics associated with the first merchant. The system may assign the first merchant to a first group of merchants based at least in part on the first merchant sharing at least one of the merchant characteristics with the first group of merchants. The system may use a machine learning model to determine a customized timing at which to provide a loan offer to the first merchant. The customized timing n ay be based at least in part on loan data associated with one or more loans previously offered to the merchants in the first group of merchants. Further, the system may send the loan offer to a computing device of the first merchant based at least in part on the customized timing.

Capital loan optimization

Techniques for optimizing capital loan offers for merchants to maximize a potential benefit of the capital loans to the merchants. A service provider may receive merchant data and/or transaction data from a merchant. The service provider may determine merchant characteristics associated with the merchant based on the merchant data and/or transaction data. The service provider may associate the merchant with a merchant group, based on the merchant characteristics. The service provider may access data corresponding to capital loans previously offered to and/or accepted by merchants in the merchant group, to determine predictive factors of successful loans. Based on the predictive factors, the service provider may generate a capital loan for the merchant with a high probability of positive impact on a merchant business. The service provider may transmit a capital loan oiler to the merchant at a time determined to maximize acceptance and optimize a growth of the merchant business.

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Oakland, CA, United States of America

Nicholas Halpern