Tag: automated decisioning

Changing consumer behaviors caused by the COVID-19 pandemic have made it difficult for businesses to make good lending decisions. Maintaining a consistent lending portfolio and differentiating good customers who are facing financial struggles from bad actors with criminal intent is getting more difficult, highlighting the need for effective decisioning tools. As part of our ongoing Q&A perspective series, Jim Bander, Experian’s Market Lead, Analytics and Optimization, discusses the importance of automated decisions in today’s uncertain lending environment. Check out what he had to say: Q: What trends and challenges have emerged in the decisioning space since March? JB: In the age of COVID-19, many businesses are facing several challenges simultaneously. First, customers have moved online, and there is a critical need to provide a seamless digital-first experience. Second, there are operational challenges as employees have moved to work from home; IT departments in particular have to place increase priority on agility, security, and cost-control. Note that all of these priorities are well-served by a cloud-first approach to decisioning. Third, the pandemic has led to changes in customer behavior and credit reporting practices. Q: Are automated decisioning tools still effective, given the changes in consumer behaviors and spending? JB: Many businesses are finding automated decisioning tools more important than ever. For example, there are up-sell and cross-sell opportunities when an at-home bank employee speaks with a customer over the phone that simply were not happening in the branch environment. Automated prequalification and instant credit decisions empower these employees to meet consumer needs. Some financial institutions are ready to attract new customers but they have tight marketing budgets. They can make the most of their budget by combining predictive models with automated prescreen decisioning to provide the right customers with the right offers. And, of course, decisioning is a key part of a debt management strategy. As consumers show signs of distress and become delinquent on some of their accounts, lenders need data-driven decisioning systems to treat those customers fairly and effectively. Q: How does automated decisioning differentiate customers who may have missed a payment due to COVID-19 from those with a history of missed payments? JB: Using a variety of credit attributes in an automated decision is the key to understanding a consumer’s financial situation. We have been helping businesses understand that during a downturn, it is important for a decisioning system to look at a consumer through several different lenses to identify financially stressed consumers with early-warning indicators, respond quickly to change, predict future customer behavior, and deliver the best treatment at the right time based on customer specific situations or behaviors.  In addition to traditional credit attributes that reflect a consumer’s credit behavior at a single point in time, trended attributes can highlight changes in a consumer’s behavior. Furthermore, Experian was the first lender to release new attributes specifically created to address new challenges that have arisen since the onset of COVID. These attributes help lenders gain a broader view of each consumer in the current environment to better support them. For example, lenders can use decisioning to proactively identify consumers who may need assistance. Q: What should financial institutions do next? JB: Financial institutions have rarely faced so much uncertainty, but they are generally rising to the occasion. Some had already adopted the CECL accounting standard, and all financial institutions were planning for it. That regulation has encouraged them to set aside loss reserves so they will be in better financial shape during and after the COVID-19 Recession than they were during the Great Recession. The best lenders are making smart investments now—in cloud technology, automated decisioning, and even Ethical and Explainable Artificial Intelligence—that will allow them to survive the COVID Recession and to be even more competitive during an eventual recovery. Financial institutions should also look for tools like Experian’s In the Market Model and Trended 3D Attributes to maximize efficiency and decisioning tactics – helping good customers remain that way while protecting the bottom line. In the Market Models Trended 3D Attributes  About our Expert: [avatar user="jim.bander" /] Jim Bander, PhD, Market Lead, Analytics and Optimization, Experian Decision Analytics Jim joined Experian in April 2018 and is responsible for solutions and value propositions applying analytics for financial institutions and other Experian business-to-business clients throughout North America. He has over 20 years of analytics, software, engineering and risk management experience across a variety of industries and disciplines. Jim has applied decision science to many industries, including banking, transportation and the public sector.

In order to compete for consumers and to enable lender growth, creating operational efficiencies such as automated decisioning is a must. Unfortunately, somewhere along the way, automated decisioning unfairly earned a reputation for being difficult to implement, expensive and time consuming. But don’t let that discourage you from experiencing its benefits. Let’s take a look at the most popular myths about auto decisioning. Myth #1: Our system isn’t coded. If your system is already calling out for Experian credit reporting data, a very simple change in the inquiry logic will allow your system to access Decisioning as a ServiceSM. Myth #2: We don’t have enough IT resources. Decisioning is typically hosted and embedded within an existing software that most credit unions currently use – thus eliminating or minimizing the need for IT.  A good system will allow configuration changes at any time by a business administrator and should not require assistance from a host of IT staff, so the demand on IT resources should decrease.  Decisioning as a Service solutions are designed to be user friendly to shorten the learning curve and implementation time. Myth #3: It’s too expensive. Sure, there are highly customized products out there that come with hefty price tags, but there are also automated solutions available that suit your budget. Configuring a product to meet your needs and leaving off any extra bells and whistles that aren’t useful to your organization will help you stick to your allotted budget. Myth #4: Low ROI. Oh contraire…Clients can realize significant return-on-investment with automated decisioning by booking more accounts … 10 percent increase or more in booked accounts is typical. Even more, clients typically realize a 10 percent reduction in bad debt and manual review costs, respectively. Simply estimating the value of each of these things can help populate an ROI for the solution. Myth #5: The timeline to implement is too long. It’s true, automation can involve a lot of functions and tasks – especially if you take it on yourself. By calling out to a hosted environment, Experian’s Decisioning as a Service can take as few as six weeks to implement since it simply augments a current system and does not replace a large piece of software.  Myth #6: Manual decisions give a better member experience. Actually, manual decisions are made by people with their own points of view, who have good days and bad days and let recent experiences affect new decisions. Automated decisioning returns a consistent response, every time. Regulators love this! Myth #7:  We don’t use Experian data. Experian’s Decisioning as a Service is data agnostic and has the ability to call out to many third-party data sources and configure them to be used in decisioning. --- These myth busters make a great case for implementing automated decisioning in your loan origination system instead of a reason to avoid it. Learn more about Decisioning as a Service and how it can be leveraged to either augment or overhaul your current decisioning platforms.