Intelligence Analytics Society's Analytics Challenge 2016

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