Date post: | 22-Jan-2018 |
Category: |
Data & Analytics |
Upload: | abhishek-m-shivalingaiah |
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Abhishek M Shivalingaiah
Pallavi Vijay
Swaroop Prince
Suraj Shyamasunder
Vicky Wu
Good Data
Junk Data with Monthly income NA
Outliers Data with Debit ratio> 20 & <0
.05 12%
Records
Good Data Junk Data with Monthly income NA Outliers Data with Debit ratio> 20 & <0 .05
-0.029424585
-0.01518111
-0.000401427
0.279798296
0.285326919
0.308343759
-0.05 0 0.05 0.1 0.15 0.2 0.25 0.3 0.35
NumberOfOpenCreditLinesAndLoans
NumberRealEstateLoansOrLines
RevolvingUtilizationOfUnsecuredLines
NumberOfTime30.59DaysPastDueNotWorse
NumberOfTime60.89DaysPastDueNotWorse
NumberOfTimes90DaysLate
Correlation between ‘Financially distressed in next 2
years variable’ and ‘all other variables’ individually
60%
40%
Among people who have
crossed 90 days past Due date
63%
37%
Among people who have
60-89
days past due date
Probablity of Non Default Probablity of Financial distress in 2 next years
76%
24%
Among people with Revolving
Utilization of Unsecure lines>0.96
81%
19%
Among people who have 30 -59
day past due date
It can be observed that ,statistics drawn out of data also supports the correlation observed in the previous slide
with an accuracy of 40%,37%,24%,19% respectively, when calculated individually.
When each relevant variable is individually check for correlation with ‘Financially distressed in next 2
years’ variable
DECISION TREEWhen all the variables are considered together, the below decision tree model can be used
in predicting who might face financial distress in next 2 years (Indicated by Red rectangle)
39%
61%
Probabilitty that a person DOESN't default
Probability that a person defaults