3 Minutes Read.
Artificial intelligence (AI) is expanding rapidly in the fintech industry. In particular, AI has largely affected digital lending. By 2020, as much as 5 percent of all of economic transactions will be handled by autonomous software, including loan transactions. By applying machine learning to collected borrower data, software solutions can approve or reject most loan applications automatically. This greatly reduces costs and human-hours. Read about how Artificial Intelligence is changing the digital lending:
Advantages of AI in Digital Lending
Artificial intelligence benefits digital lending in two basic ways. First, it can greatly improve the speed and accuracy of the lending process. Second, it can analyze a vastly greater amount of data than any human underwriter could possibly manage, it can use alternative data not included in conventional credit scoring to assess borrower risks.
AI allows lenders to expand their loan portfolios without significantly expanding their physical infrastructure or staff simply. This is due to the speed at which lending software solutions can operate. With AI handling all or part of the loan origination and underwriting process, a greater volume of loan applications can be handled. And all while per-application and overall costs are drastically reduced! Manual handling of loan applications is virtually eliminated, along with the risk of human errors such as mis-keying borrower information.
Banks and online lenders can reach a greater number of borrowers with AI-driven lending software solutions. It is estimated that about one-fourth of the American population is unbanked. Despite this, many of these people do have sufficient incomes and otherwise stable financial circumstances to make them good prospective borrowers. For these people and others with limited credit histories according to conventional measures like FICO, AI can use other data to build a credit risk profile. As the amount of data the system can use grows, it learns from patterns in the data. For example, certain educational backgrounds may correlate to better loan repayment histories. The AI-driven system can use this information it has learned to refine its data analysis for new loan applications.
Challenges in Implementing AI
The financial industry has traditionally been slow to change. Banks and other kinds of financial institutions have operated profitably using decades-old processes and systems. Thus may not see the need to adopt revolutionary ideas. The rapid growth of alternative lending, however, is forcing traditional lenders to change their perspective.
Apart from overcoming conventional thinking, the biggest challenge to the adoption of AI is the issue of data security. In a study by Cognizant, a majority of financial executives surveyed saw a growing role for AI in their own businesses and the industry as a whole. An even bigger number of executives, however, said data security was the biggest challenge to AI adoption.
The MonJa Solution
MonJa is at the forefront of AI-driven lending software solutions for an array of loan types originated by traditional financial institutions, as well as online lenders. It covers unsecured consumer, auto, C&I (Commercial & Industrial), CRE (Commercial Real Estate), equipment and other small business loans. MonJa offers automated underwriting, flexible, customizable loan scoring, AI-powered risk algorithm, and robust data security in a scalable package that integrates easily with your existing systems.
With automated underwriting solutions, banks, credit unions and other lenders can serve a variety of loan sizes and customer profiles, attracting and retaining more clients in less time. To learn more about how automation can benefit your lending business, download our Free e-book today.
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Our platform supports consumer term, C&I, CRE, auto and other small business loans.