Predictive analytics is transforming how we allocate mobility funding. By analyzing historical application trends, we can now predict underspend months in advance.
The Underspend Trap
Every year, millions of pounds of Turing funding goes unspent because students drop out or costs are overestimated. Real-time budget tracking allows you to reallocate these funds to students on the waitlist before it's too late.
Targeting Support
Data shows that students from widening participation backgrounds are 3x more likely to drop out of the application process at the "Risk Assessment" stage. Intervening at this specific point with extra support can double your WP numbers.
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