When a customer overdraws their account and their balance is negative they are assessed an overdraft fee. Americans pay approximately \$15 billion in unnecessary overdraft fees a year, often in \$35 increments; users of the Mint personal finance app pay approximately \$250 million in fees a year in particular. These overdraft fees are an excessive financial burden and lead to cascading overdraft fees trapping customers in financial hardship. To address this problem, we have created an ML-driven overdraft early warning system (ODEWS) that assesses a customer's risk of overdrafting within the next week using their banking and transaction data in the Mint app. At-risk customers are sent an alert so they can take steps to avoid the fee, ultimately changing their behavior and financial habits. The system deployed resulted in a \$3 million savings in overdraft fees for Mint customers compared to a control group. Moreover, the methodology outlined here can be generalized to provide ML-driven personalized financial advice for many different personal finance goals--increase credit score, build emergency savings fund, pay down debut, allocate capital for investment.
翻译:当一个客户超额透支其账户,其余额为负数时,他们被评估为透支费。美国人每年以不必要的透支费支付大约150亿美元,经常是35美元的递增额;Mint个人金融应用程序的用户每年支付大约2.5亿美元,特别是收费额。这些透支费是一个过度的财政负担,导致透支费的累累,使客户陷入财政困境。为了解决这个问题,我们建立了一个由ML驱动的透支预警系统(ODEWS),用以评估客户在下周内利用Mint应用程序中的银行和交易数据透支的风险。有风险的客户受到警告,以便采取步骤避免费用,最终改变其行为和财务习惯。所安装的系统导致与控制集团相比,Mint客户透支费节省了300万美元。此外,这里概述的方法可以推广,为许多不同的个人融资目标提供由ML驱动的个人化金融咨询,建立紧急储蓄基金,支付下调投资资本。