Tracking your Data for Success

​Tracking Pre-­Purchases in Different Ways

People always stress preparation and with reason. Being organized is really the window to an organized mind. Think about it; most people feel like a mess when they are out of control or lacking control in a situations since it is a type of organization. Preparation, control, and organization might not precisely mean the same thing but they all tie together one way or another. We emphasize these words because in note buying you use all three. When you make multiple purchases and are handling many notes you want to be organized to avoid losing documents, to keep tracking of transfers and open accounts, etc. There are a number of different ways to track pre-­purchases to predict possible outcomes and returns, of which we’ll discuss a few.

One tracking method looks at fair market value (loan to value and combined loan to value are important metrics to keep in mind). People usually track FMVs from sites like Zillow, but it is wise to keep in mind that it’s values tend to be inflated. To find the baseline FMV we need to figure out just how inflated these are, the deviation. When selling a note with negative equity, if the FMV of the property went down from X to Y the loan is devalued and is now worth what the market says it’s worth.

Then there is tracking by the borrower’s credit profile, in which we are looking at how a purchase has been performing based on credit. The only way to figure out these deviations is to tie that back with how the asset actually performs overtime. Therefore, start to statistically track from the first dollar received and in how many days. Think about when you first bought the asset. What was the loan to value? What was the credit score? How long has it been open? With due time, you will start to see just how an asset class performs or how certain loans in certain buckets perform to determine how an unpurchased pool may perform.

Risks can also be tracked. For example, you can track risk in owner versus non­owner occupied properties by looking at loans that end up in foreclosure. What percentage of those were owner occupied? What percentage were not?

By tracking these and other metrics, you can slowly start to predict what will be the estimated return on a pool. And remember to process map the methodologies used in your prediction models!