Got a few of hours of spare time last week, and analyzed LC payment data to construct the transitional probabilities of the various loan status (i.e., Markov Chain --

http://en.wikipedia.org/wiki/Markov_chain). See attached.

Some things to consider:

1. Each node (state) represents a Loan Status in Lending Club.

2.

**Current** is the root state; all loan initially starts in this state.

3.

**Fully Paid** and

**Charged Off** are the sink states; once a loan comes to this state it cannot get out. This is supported by data.

4. For each state, the total percentage of all out-going transitions (out arrows) is 100%.

5. The percentages are generated using the monthly payment data. For example, loan that was

**Current** in month

*m*, and then

**Fully Paid** in month

*m+1* is included in the arrow from

**Current** to

**Fully Paid**. The number 1.61% represents the probability of loans that are

**Current** this month to become

**Fully Paid** the following month.

6. Looking at the out-arrows of initial state

**Current**, there is a 97.59% probability the loan will stay

**Current** next month, 1.61% will be

**Fully Paid** next month, etc.

There are a lot of interesting "transitions" in the diagram; but I'd let the data speak for itself. Anyone with payment data should be able to reproduce this. Naturally, this chain will change slightly every month as additional payment data becomes available.

Hopefully, this is useful to some of the Forum readers.

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