Almost anything can be made simpler by applying analytics to a problem. That’s what Chad Prashad does as vice president of analytics for World Acceptance Corporation (WAC) and in his volunteer work helping foster children find stable homes.
At WAC, a small-loan consumer finance company, part of Prashad’s job is to help identify borrowers who are more qualified than indicated by traditional credit assessments. Even while complying with extensive underwriting and marketing regulations and policies, Prashad not only helps WAC identify new pools of qualified potential borrowers, but also develops creative solutions that help the company quickly identify internal challenges and best practices that can be shared throughout the enterprise. His efforts are evenly split between underwriting, marketing, and operations management—including recognizing red flags such as unusually high percentages of “bad loans” originating from a single office or individual.
“Imagine an e-portfolio for each child that helps match them to the best foster-family environment and tracks court outcomes, therapy sessions, school performance, and feedback from parents, guardians, caseworkers, and foster parents. That kind of data management would go a very long way toward taking the focus off of paperwork and processes and putting it back on the children.”
Prashad admits that analytics can easily exist within its own isolated universe, but he believes it’s much more important to use data to develop practical solutions that address real-world issues.
“If I can provide people working in the field with information that they immediately understand and that enables them to improve, that’s powerful,” he says.
“The results have to be actionable or they really have no value at all.”
Developing New Insights
Prashad brings analytics to life by leveraging what he calls “marginal informational value” and revealing hidden indicators within existing data where each new data set can offer new insights. For example, other lenders may use tangential data to determine credit worthiness through a customer’s Facebook profiles, how they portray their work histories, or even proper grammar. WAC, however, takes a more conservative underwriting approach: completing one-on-one reviews of credit reports and customer-provided information. Combined with analytics, this method can make it possible to determine whether a single late payment indicates a pattern of default or a one-time error that should not disqualify a risk-worthy borrower.
“Our decision might change based on a single attribute out of 1,200 used by traditional credit bureaus. Analytics help us find potential customers who appear too risky on paper and, therefore, un-creditworthy to any other credit originator. It creates opportunities both for borrowers and for us as a lender,” Prashad explains.
To help WAC expand its pool of potential applicants, Prashad explores additional data from companies such as FactorTrust, which provides results from its own proprietary dataset and third-party data sources. This facilitates additional perspectives on sub-prime consumers and those outside of traditional banking and lending channels.“It’s all part of a comprehensive effort to identify prospects, but also to educate them on types of loans and repayment plans, monthly budgets, and making sure that we fully understand all the aspects that impact their ability to repay a loan,” Prashad says. “The more data you bring in, the better chance you have to gain a new point of view and make better decisions.”
In addition to using analytics to assess performance at the company’s 1,200 locations, it is also used to identify the characteristics of the most successful branches and employees. In one instance, a correlation was discovered between branch manager tenure and the level of customer referrals.
“Prior to implementing analytics, it was difficult to accurately interpret the meaning of specific metrics, what was driving them, and to be able to trend them over time,” Prashad says. “Now the results are easy to interpret and immediately meaningful to operations. That’s been our greatest success so far.”
Analytics For Better Lives
In 2009, Prashad stumbled onto a new environment in which his expertise could help make improvements. He and his wife began volunteering as tutors for teen girls at a local orphanage, where they built strong relationships with many of their students. The couple also became very familiar with the social-service system after they fostered and adopted several children.
Prashad recognized that one of the most important missing elements in the system, especially for older children, is maintaining stable, long-term connections. He believes the system is entangled in processes, workloads and regulations that obscure factors that could otherwise be used to help establish relationships the children so desperately need.
That led to Prashad becoming the board chair of Fostering Great Ideas, a South Carolina non-profit that uses innovative ideas to improve the lives of teens in foster care. It’s also a new platform where analytics can be used to better support the children.
“Imagine an e-portfolio for each child that helps match them to the best foster-family environment and tracks court outcomes, therapy sessions, school performance, and feedback from parents, guardians, caseworkers, and foster parents,“ he says. “That kind of data management would go a very long way toward taking the focus off of paperwork and processes and putting it back on the children. That’s a system that would be leveraging technology to better serve their best interests.”
Prashad is also working to integrate the value of analytics in other nonprofits in South Carolina. In addition to helping Clemson University design the curriculum for an MBA with an analytics emphasis, he is also working to convince the school to institute student internships with local charities.
The Beginning of the Future of Data
In both his personal and professional lives, Prashad contends that data holds the keys to creating innovative solutions, overcoming existing challenges, and producing better results. It’s all just a matter of knowing where to look and understanding what to look for.
“There is no limit to the possibilities, especially in the finance industry as it begins to incorporate more of this type of analysis,” he says. “It can leverage the results to make better-informed, real-time decisions about credit assessments and risk appetite. And there’s certainly no shortage of what might appear to be completely unrelated data sets that will eventually come to be used to produce more beneficial opportunities—not just in finance, but in many other fields.”