Conclusion Thoughts and Future Trends for AI in Financial Lending

Conclusion Thoughts and Future Trends for AI in Financial Lending

A major goal of Upstart is to use modern data science to automate the loan process. They claim to have been able to rapidly increase the amount of loans they are able to fully automate and as as of the have reached 40 percent automation. While other companies have also automated some of the data entry, processing of paperwork, and verifying basic information most loan applications are still reviewed by a human underwriter before they can be approved. A human who checks that the information is accurate or the loan makes sense.

Upstart is a hybrid lender, which makes some loans directly and facilities loans for other lenders. This year it also started offering its technology to other companies via software-as-a-service.

Improving Customer Experience and Finding Customers

This section will look at only loan specific-uses of AI to attract and engage customers. Obviously, big banks along with a whole range of sectors are adopting general AI-powered tools such as chatbots, customer relationship management tools, and advertising analytics.

Personetic – Loan Repayment

Personetic is a cognitive banking company that provides AI applications to major banks (such as Royal Bank of Canada and Ally Bank). A recently unveiled application from the company is a tool, Personetics Act, to help individuals save money.

They use the same basic technology to help individuals pay off their student loans faster. They claim their system uses machine learning to determine analyze individual’s financial habits to determine if they can afford to pay back their student loans more quickly. The system can then automatically suggest to individuals how much more they should contribute.

Amazon – Small Business Loans

Given the dominant role Amazon plays in online retail, it has a huge amount of proprietary information on what products are sold on their site, how customers feel about those products, the economic status of the companies which make those products, and the likely future demand for these products.

Amazon is using this data in machine learning models to find companies to offer small business loans to. The program is invitation only. Amazon finds companies to give loans to and makes the application very easy. Their proprietary source of data can might provide Amazon a better understanding of what some specific companies might want a loans and their relative creditworthiness than other traditional lenders. It is possible Amazon could realize a small business could use a loan and offer them one before the small business owner even does.

The program is invitation only. Last year, Amazon lent out roughly $1 billion to small businesses that use its marketplace.

The use of machine learning to analyze alternative data in loans and credit rating is going to raise some privacy, ethical , and legal concerns. Many people might not feel comfortable with a company having access to all of this sensitive information about their life. Even if all these companies behave ethically, the more data they hold the more that can be stolen by malicious hackers in a data breach.

The use of “big data” also runs the risk of companies accidentally or purposely discriminating against groups. For example, a program might not deny applications from protected minorities, but it https://loansolution.com/title-loans-id/ might deny applications for individuals who have a dozen data markers that just happen to highly correlate with those groups.

Even with these concerns the use of machine learning to process alternative data to determine creditworthiness is likely to grow significantly. There are billions of people without real credit histories that companies may one day want to offer mortgages, payment plans for products, credit cards, or other loans. The financial appeal of these tools is obvious. It is reasonable to believe that the more information you gather about an individual, the more likely you would be able to predict their behavior, including how diligently they would pay back a loan.