Download Small Business Credit Default

Loan Default Model
Saed Sayad
www.ismartsoft.com
1
Data Mining Steps
1
• Problem Definition
2
• Data Preparation
3
• Data Exploration
4
• Modeling
5
• Evaluation
6
• Deployment
www.ismartsoft.com
2
1. Problem Definition
Build loan default prediction model for
small business using the historical data to
assess the likelihood of default by an
obligor.
www.ismartsoft.com
3
Data Mining Team
Modeler
Domain
Expert
DBA
Analyst
www.ismartsoft.com
4
2. Data Preparation
•
•
•
•
•
No of Cases: 35,500
No of Defaults: 2,500 (7%)
Number of Variables: 25
Total balance for all cases: $554,000,000
Total balance for defaults: $58,000,000 (10.4%)
www.ismartsoft.com
5
3. Data Exploration
Univariate
Analysis
Frequency,
Average, Min,
Max, ...
Bar, Line, Pie, ...
Charts
Data
Exploration
Correlation
Bivariate
Analysis
www.ismartsoft.com
Z test, ...
Combination
Charts
6
Data Exploration - Univariate
Months in Business
www.ismartsoft.com
7
Data Exploration - Bivariate
Months in Business and Default
Default%
www.ismartsoft.com
8
4. Modeling
Classification
Regression
Clustering
Bayesian
Linear
Regression
Hierarchical
Decision
Tree
Robust
Regression
K-Means
Logistic
Regression
Neural
Network
Association
A Priori
SVM
www.ismartsoft.com
9
Modeling - Classification
Logistic Regression
Age
f
www.ismartsoft.com
Default
Y or N
10
Logistic Regression Model
Linear Model
1
Logistic
Model
Default
0
Months in Business
www.ismartsoft.com
11
5. Evaluation
Charts
Stats
Gain Chart
Confusion
Matrix
Lift Chart
Mean Square
Error
K-S Chart
Variables
Contribution
www.ismartsoft.com
12
Evaluation – Variables Contribution
Variables Contribution - Top 10
Maximum Number of Delinquency
Maximum Line Usage
Number of Delinquent Days
Credit Score
Total Number of Deliquency
Total Number of Deliquent Days
Business Type
Months in Business
Number of Line of Credit
Total Balance
0.0%
5.0%
10.0%
15.0%
www.ismartsoft.com
20.0%
25.0%
30.0%
35.0%
13
Evaluation - Confusion Matrix
Predicted
Positive
Positive Cases
Negative Cases
247
264
3%
3%
Predicted
Negative
8167
313
7343
4%
90%
www.ismartsoft.com
14
Evaluation – Gain Chart
Default%
100%
58%
10%
Population%
10%
50%
www.ismartsoft.com
100%
15
Return On Investment
•
•
•
•
Total Number of Loans = 8,167
Total Number of Defaults = 560
Total Balance for Defaults = $12,281,589
Top 10% Random
– Number of Defaults = 56
– Total Balance = $1,230,000
• Top 10% Model
– Number of Defaults = 305
– Total Balance = $7,655,772
www.ismartsoft.com
600%
ROI
16
6. Deployment
SQL
Batch
Scoring
HTML
Webbased
Scoring
www.ismartsoft.com
17
Questions?
www.ismartsoft.com
18