How AI Is Shaping the Future of Lending

by on Apr 24, 2020, 12:46 PM

How AI Is Shaping the Future of Lending

Many mistakenly believe that artificial intelligence (AI) in lending is simply an updated version of automated credit decision-making. However, AI is much more than that. The potential benefits of AI in lending include reduced credit loss, higher revenue per loan, fewer write-offs, lower due-diligence costs, lower servicing costs, and a much-improved overall experience for both borrowers and lenders. AI and machine learning technologies have found their way through various stages of the lending process, even before the borrower submits an application. Read on to learn how AI is shaping the future of lending — and what to pay attention to.

From Casual Web Browser to Customer

Advertising actually serves as the very first critical first step to predicting a seamless experience for both parties, and AI plays a role there, too. When the right lending product is presented to the right customer at the right time, the process becomes much easier and outcomes are improved.

With AI, financial institutions can hyper-target those consumers and businesses likely to be applying for credit and present them with the best possible product. This reduces advertising spend (both print and digital), removes frustration, increases right-fit applications and improves profitability.

Before borrowers decide to begin the application process, they can use AI technologies to determine their creditworthiness. Using a research and education tool such as ScoreMaster can provide simulations of credit scores based on hypothetical payments and spending decisions, thereby helping borrowers achieve their best possible credit score. Moving on to the application process, AI can take care of manual tasks such as reviewing forms and data input. This frees up loan processors’ time, enabling them to concentrate on ensuring the process stays on track so the loan will fund in time.

AI and machine learning expedite loan decision times as well. Larger loans that once involved long and intensive reviews, such as mortgage lending, can now happen over the course of a few hours, not days or weeks. This reduction in delays leads to a stronger customer experience in the initial stages of the process, in addition to higher profitability.

AI’s usefulness continues throughout the lifetime of the loan. It can detect patterns in borrower payments, and when issues arise, the technology can present options automatically.

How AI Works: Supervised and Unsupervised AI

There are two kinds of AI: supervised and unsupervised.

With supervised AI, humans create certain rules and software can classify data based on these rules. AI can examine thousands of applications and group them by profitability or default risk. The AI learns the lender’s underwriting rules, including credit score, borrower experience, collateral value and the like, and simply applies these rules to new applications. Versions of this technology have existed in the financial services industry for decades.

Unsupervised AI is a newer methodology and approach. In unsupervised AI, humans do not create rules at the beginning. Instead, a data scientist feeds an algorithm a massive amount of data and asks that the algorithm identify patterns among potentially thousands of variables.

While traditional factors such as credit score or collateral value would be important in predicting the likelihood of funding a loan, AI can access other indicators, such as age, occupation, health and even social media posts, to determine patterns of borrower creditworthiness.

Consumers fear privacy violations when AI has access to all types of seemingly unrelated data. However, AI generally uses large pools of anonymized data in which it discovers patterns. Lenders and other financial institutions can purchase access to these large pools of anonymized data and combine that with the data the borrower knowingly contributes and grants access to the lender in the application process.

AI will continue to shape the future of lending for both borrowers and financial institutions. Often, AI is working in the background and human decisions are introduced only at critical points. This leads to not only the right match of consumer to product but also reducing the time needed for decision-making and processing. 

To learn more about how a tool like ScoreMaster can help your borrowers achieve their best possible credit score in 20 calendar days, contact ScoreMaster today.

*Legal Disclaimer – ScoreMaster is a patent-pending educational feature simulating credit utilization’s effect on credit scores via payments or spending. Your results may vary and are not guaranteed. 

References:

  1. https://www.disruptordaily.com/future-of-ai-lending/
  2. https://www.forbes.com/sites/forbesrealestatecouncil/2019/10/30/three-ways-ai-will-impact-the-lending-industry/#20d63b56899b
  3. https://www2.deloitte.com/global/en/pages/financial-services/articles/artificial-intelligence-transforming-financial-ecosystem-deloitte-fsi.html