Leveraging and Predictive Modeling in Financial Aid

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Dr. Scott D. Miller
President
Wesley College

Leveraging formulas and predictive modeling programs have become popular in recent years. Using historic trends, tracking individual characteristics of aid recipients and calculating conversions and yields can be useful. College and university administrators should be cautious, however, when purchasing such services.

Financial aid is certainly an important influence in the college selection process. It would be a mistake to overestimate the impact of the amount of aid or aid structure in decision- making. So many other factors can influence college choice. Location, academic reputation, facilities, co curricular opportunities, academic support services and even the relationship built between admission counselors and prospective students and their parents can have equal or greater influence on the selection process. A review of relevant data is important and can be useful, but it should not be viewed as some magic bullet. 

The size of the institution must be taken into consideration. Modeling and other formulas often work better at larger institutions. Calculating trends and conversion for 8,000 applicants for admission might be meaningful. Attempting to calculate meaningful trends based upon much smaller application pools are not as likely to be accurate and can actually be dangerous. 

Electing to address expenditure or yield issues with formulas and models is sometimes easier than taking a closer look at the actual financial aid and recruitment practices at an institution. Making changes in internal operations can often increase enrollment yield and assist in controlling or reducing institutional aid expenditures. 

Review Strategies and Tactics in Building the Inquiry Pool 

Examine Communication Between Admission Counselors and Applicants for Admission 

Thoroughly Review Financial Aid Policies and Practices 

Reconsider the Institutional Financial Aid Award Policy 

Increase Visit Rates 

While effective enrollment management requires accurate data and analysis, administrators seeking to improve yield, conversion rates or reduce financial aid costs should begin the process by examining internal operations. Enrollment management leaders must focus efforts to make improvements on the intended results rather than limiting their options with a single tool. 

Data analysis is definitely useful in order to control financial aid expenditures and increase net revenue, but the issue is much more complicated than just applying a new formula or utilizing modeling technology. This is particularly true for smaller colleges and universities. Institutions would benefit from an approach that combines statistical analysis with a review of practices.


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