Taking chances can be fun; it’s how many people discover new hobbies or meet lifelong friends. But when it comes to financial security, banks and financial institutions (FIs) should be as careful as possible.
In the recent webinar “Artificial Intelligence and Managing the Credit Risk Cycle,” Leslie Parrish, Senior Analyst of Consumer Lending at Aite Group, and Amyn Dhala, VP and Global Product Owner for Mastercard AI, discuss the steps that FI’s can take to protect consumers from credit risks and fraudulent activity.
Macro trends and the current credit risk environment
With all of the technological advancements made in the payments industry over the last year, there is a lot of uncertainty and potential volatility concerning the future of the credit risk environment.
Through the end of 2019, the U.S. economy was on a strong growth trajectory. The unemployment rate was historically low (under 4%), and the stock market was experiencing an all-time high. “Now though, I would say we’ve been on a bit of a roller coaster over the last 12 months,” said Parrish. “And I believe we still have many months left on that ride.”
When news of the pandemic hit the public late in the first quarter of 2020, there was an undeniable decline. By April of that year, the unemployment rate was at roughly 15%. While this number has trended back downward (7%), it remains alarmingly high (above 20%) for the lowest quartile of wage earners. The number of Americans considered to be “long-term unemployed” continues to rise. On the opposite side of the coin, some businesses and households emerged from 2020 in a better economic position than they started.
In the second quarter of 2020, gross domestic product (GDP) fell dramatically, but it rose again in Q3 and Q4. “Economists are cautiously optimistic for 2021, predicting a 4% growth rate this year, after an overall contraction of 3.5% last year,” added Parrish.
Consumer debt trend statistics from the New York Fed reveal that the first quarterly drop in consumer debt levels since 2014 occurred in Q2 of 2020. This was most likely due to a change in consumption patterns and a more conservative approach to spending. Many households also received CARES Act payments, additional unemployment benefits, and tax refunds. Presumably, consumers used some or all of these cash infusions to pay off their existing debt, and the expected upticks in delinquency rates did not hit the high levels expected.
Unfortunately, these debt levels rose again in Q3, offsetting the progress made in the previous quarter. Credit card debt has continued to decline, but student, auto, and mortgage loans are showing a year-over-year increase.
Leveraging AI for better credit risk decisions and improved customer experience
In an environment where debt is always growing, the need to provide both a good customer experience and account management is more important than ever. Banks and other financial institutions (FIs) need to invest in technologies that benefit customers and small businesses alike. Specifically, they are looking to leverage AI to mitigate credit risk, which dually serves the customer experience and account management goals.
“This is something which is really reflected in our discussions with customers globally across geographies, or even segments [and] data across a consumer or small business,” explained Dhala. Recent research suggests that backend executives favor AI investment, with 88% planning to invest over the next 2-5 years, specifically for better credit risk solutions.
One of the key benefits of AI is that the data stored can be applied across the customer’s lifecycle—which includes collections optimization, portfolio management, and application origination—all while increasing profitability and positive customer experience. Banks and FIs can then “onboard new customers with credit risk origination, monitor delinquency through portfolio management, and then optimize collections for more mature accounts in [their] portfolio[s],” continued Dhala.
AI can also detect early warning signs of credit delinquency, which allows lenders to personalize repayment strategies that prevent the borrower’s account from ever reaching collections. Additionally, it is able to detect which consumers could benefit from a higher credit limit.
Finally, AI has the capability to leverage data across an organization, which helps with processes such as making good predictions up to twelve months in advance. “One cannot really make an intelligent decision without having the right data,” concluded Dhala.
Mastercard helps banks around the globe
Mastercard has been leveraging AI for over a decade to enable their customers with security services, including transaction fraud. “For context, AI technology analyzes over 60,000 events per second across a diverse array of mission critical applications,” ellaborated Dhala. “And this amounts to more than 100 billion events annually. The impact of the technology has really improved fraud detection by three times, and generated lists of up to 10 to 20 times the existing systems or models, in terms of false positive detection.” The AI capabilities can also make real-time decisions, enabling customers to tap and pay.
The three key factors that make Mastercard’s Brighterion AI solutions so successful are:
- Smart technology – Smart agents can make real-time observations based on all user activity, allowing banks to optimize services for each card holder.
- AI’s ability to work with any data – Data can arrive in various formats from dissimilar entities, and Mastercard’s technology can process all types of data, regardless of format or point-of-origin.
- AI adaptive learning capabilities – Mastercard uses a collaborative service model called AI Express to help organizations with their greatest pain points. The program also enables organizations to smartly and efficiently deploy AI to solve business challenges, such as credit risk mitigation.
Mastercard works with banks and FIs to identify the challenges they are seeing and then execute the AI Express technology. “During the session we provide customers with hands-on experience with multiple AI modules and advised on how the same can be deployed,” said Dhala. Once the model is complete, which usually happens within the short time span of six to eight weeks, businesses will be able to deploy the program.
Mastercard enables FIs with AI using a structured approach that will help them to provide a better customer experience, reduce fraud, increase profitability, and manage credit risk for billions of transactions. It is working with banks globally to personalize how both businesses and consumers interact with the technology.
Dhala tells listeners that Mastercard industry professionals can show their customers the power of using AI for credit risk across a customer’s lifecycle and provide the proper education so that users of the technology can realize the benefits on an ongoing basis.
To learn more about how Mastercard is using AI to mitigate credit risk and improve the payments experience for all parties involved, check out the full webinar!