This is a fascinating intersection because Nollywood already generates massive amounts of data through social media engagement, streaming metrics, and audience sentiment that could easily fuel predictive modeling. By training machine learning algorithms on these digital footprint trends, investors could move beyond traditional, biased vetting processes to identify small production houses or creative agencies with the highest viral potential and economic output. While incorporating election data is trickier due to the volatility of political cycles, you could certainly analyze regional demographic shifts to predict which locations might see a surge in demand for local content. The key to making this work would be building a transparent credit-scoring model tailored to the creative economy, which often lacks the collateral required by traditional banks. If you are serious about this, I would suggest looking into open-source datasets from platforms like YouTube or local streaming services to prototype a predictive performance score for emerging creators.