首页|Researchers Submit Patent Application, 'Machine-Learning Model To Predict Likelihood Of Events Impacting A Product', for Approval (USPTO 20240046347)
Researchers Submit Patent Application, 'Machine-Learning Model To Predict Likelihood Of Events Impacting A Product', for Approval (USPTO 20240046347)
扫码查看
点击上方二维码区域，可以放大扫码查看
原文链接
NETL
NSTL
From Washington, D.C., NewsRx journalists report that a patent application by the inventor Koupanou, Natalia (London, GB), filed on August 9, 2022, was made available online on February 8, 2024. No assignee for this patent application has been made. News editors obtained the following quote from the background information supplied by the inventors: " "The subject matter described relates generally to machine-learning and, in particular, to a model for predicting the likelihood of future events that impact product. "When deciding what products to offer to a consumer, providers typically use a combination of rules a human judgment calls regarding whether a given product is suitable for a particular consumer. For example, in the financial sector, lenders evaluate the likelihood of whether the consumer will default on repayments in determining whether to offer the entity a loan and on what terms the loan is offered. However, in many instances the lender is operating on limited data. This is particularly true for many financial technology companies and other non-traditional banking services, many of which have been formed in the last five to ten years and thus have limited data on loan repayments and defaults for their customers. As a result of the lack of data, many existing processes for approving loans and other products have high error rates, which increases the cost of products for consumers, reduces profits for lenders, or both. Such processes may also have biases, which further reduce business efficiency."
NETL
NSTL
