Continuing the theme of tracking the late or worse vintage curves. Each curve lasts only as long as there are 250 loans in the bucket. The curves progress in time from the loan origination date. The measurement is the percentage of money late or worse. After a debt is defaulted the net default amount is used as the late or worse amount.
General Population 1 Month Late or Worse:
Zero Current Delinquencies 1 Month Late or Worse:
0 Current DQ, 0-1 Inq in last 6 months Criteria 1 Month Late or Worse:
Here is the SQL to produce the data for the general population curves (this take a while to run so you cannot run it on ProProsper as it will timeout):
DECLARE @DTD int
cast(aday-originationdate as int) as ‘PIT’,
sum(PrincipalBalance+NetDefaults) as ‘Amount’,
count(l.[key]) as ‘Count’,
sum(case WHEN (mld.DPD!=0 and (mld.DPD+(aday-observationdate))>@DTD) THEN PrincipalBalance+NetDefaults ELSE 0 END) as ‘AmountLate’,
sum(case WHEN (mld.DPD!=0 and (mld.DPD+(aday-observationdate))>@DTD) THEN PrincipalBalance+NetDefaults ELSE 0 END)/sum(PrincipalBalance+NetDefaults) as AmountLatePercentage,
sum(case WHEN (mld.DPD!=0 and (mld.DPD+(aday-observationdate))>@DTD) THEN 1 ELSE 0 END) as ‘CountLate’,
sum(case WHEN (mld.DPD!=0 and (mld.DPD+(aday-observationdate))>@DTD) THEN 1.0 ELSE 0.0 END)/count(l.[key]) as ‘CountLatePercentage’
inner join creditprofile cp on cp.listingkey=l.listingkey
inner join LoanPerformance mld on l.[key]=mld.loankey cross join alldays
mld.observationdate = ( select top 1 observationdate from LoanPerformance sub where sub.observationdate < aday and sub.loankey=mld.loankey order by sub.observationdate DESC )
and aday < getDate()
and aday >= ‘02/01/2006′
cast(aday-originationdate as int),
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