Mastercard International Incorporated

Pritam Kumar Nath

Karamjit Singh

Yatin Katyal

Ankur Saraswat

Debasmita Das

Bhargav Pandillapalli

Rajesh Kumar Ranjan

Sonali Syngal

Nishant Pant

Nitish Kumar

Suhas Powar

Kamal Kant

Kshitij Gangwar

Embodiments provide artificial intelligence-based methods and systems for predicting account-level risk scores associated with cardholders. Method performed by server system includes accessing payment transaction data and cardholder risk data associated with cardholder. The payment transaction data includes transaction variables associated with past payment transactions performed at Point of Interaction (POI) terminals within a particular time window. Method includes generating cardholder profile data based on the transaction variables and the cardholder risk data. Method includes determining account-level risk scores associated with the cardholder based on cardholder profile data. Each account-level risk score of account-level risk scores is determined by a trained machine learning model. The account-level risk scores include a wallet reload risk score, an account reissuance risk score, and a transaction channel risk score. Further, the method includes transmitting a recommendation message to an issuer server associated with the cardholder based on the account-level risk scores.

Methods and systems for predicting account-level risk scores of cardholders

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Kolkata, India

Pritam Kumar Nath