Poor consumers in credit-scarce economies are not easy to serve. These borrowers can be vulnerable to shocks, such as natural disasters or illness, and may not be able to provide documentation, like salary records, bank statements, or credit histories. Because it is expensive and complicated to provide credit in these markets, it isn’t being done. A potential solution is predictive cash flow modeling (PCM), or the use of statistical models to forecast income and expenses for defined population segments. This knowledge can tell lenders what size loan suits each segment, and it can also inform decisions on timing and risk. The basic concept of PCM is not new: Financial institutions have used a similar process in commercial real estate portfolios, and microfinance institutions have experimented with a similar idea. While building these cashflow models will likely be complex and expensive, philanthropic capital could step in to help with data collection and provide technical support.
