Impact of Artificial Intelligence on Credit Scores in Lending Process

R. Dhaigude, N. Lawande
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Abstract

The credit scoring remains always concerned about developing an empirical model to support the financial decision-making process for financial institutions in the most efficient manner. Currently, the use of technology for credit score is not universally adopted by financial institutions because there is lack of evidence to ensure the effectiveness of this alternate method. Thus, the aim of this research is to recognize the impact or effect on the financial institutions which they have experienced post integrating AI in their institution for generating credit scores for the lending process. The data was collected from 68 Credit Officers/Credit Managers working in Financial Services Provider companies. The semi structured questionnaire was used to understand the use of AI and the perception of Credit Managers towards using AI in the lending process. The primary and secondary data were analysed to evaluate the impact of using AI in calculating Credit score. The research suggested that the financial institutions consider time saving with lesser workforce, Increase in Revenues and Business, Default rate reduction and Skill upgrade along with not breaching privacy of their customers. The FinTech companies can understand the factors in a better manner to develop their products for the financial services providers. And the financial institutions can make a better use of AI to reach out to more prospective customers and provide better.
人工智能对贷款过程中信用评分的影响
信用评分一直关注的是建立一个实证模型,以最有效的方式支持金融机构的金融决策过程。目前,由于缺乏证据来保证这种替代方法的有效性,金融机构并没有普遍采用技术进行信用评分。因此,本研究的目的是认识到他们在将人工智能集成到他们的机构中为贷款过程生成信用评分后所经历的对金融机构的影响或影响。数据收集自68名在金融服务提供商公司工作的信贷主任/信贷经理。使用半结构化问卷来了解人工智能的使用以及信贷经理对在贷款过程中使用人工智能的看法。分析了主要和次要数据,以评估使用人工智能计算信用评分的影响。研究表明,金融机构在考虑不侵犯客户隐私的同时,还会考虑减少劳动力、增加收入和业务、降低违约率和技能升级。金融科技公司可以更好地了解这些因素,从而为金融服务提供商开发产品。金融机构可以更好地利用人工智能来接触更多的潜在客户,并提供更好的服务。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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