YesBank - Loan Prediction

With an increasing focus on retail customers, Yes Bank is now churning data to understand customer behaviour and offer a right mix of products based on a predictability model. The data analytics capabilities at YES BANK enables us to serve our customers and clients with greater depth, sophistication and efficiencies through innovations such as artificial intelligence, machine learning, natural language processing and bots. But, we understand that not all innovation can come from within the bank.

YES BANK has launched DATATHON, which invites participants from across the world, who will join us in our quest of Data driven Innovation and develop models for the appropriate sourcing and usage of data across businesses.

Classification Problem

The data given is of credit records of individuals with certain attributes. Please go through following to understand the variables involved:

Data Dictionary

SNo.	Variable	Definition
a.	serial number	unique identification key
b.	account_info	Categorized details of existing accounts of the individuals.
c.	duration_month	Duration in months for which the credit is existing
d.	credit_history	This categorical variable signifies the credit history of the individual who took loan
e.	purpose	This variable signifies why the loan was taken
f.	credit_amount	The numerical variable signifies the amount credited to the individual
g.	savings_account	This variable signifies details of amount present in savings account of the individual
h.	employment_st	Categorical variable that signifies the employment status of everyone who has been alloted loans
i.	poi	This numerical variable signifies what percentage of disposable income spent on loan interest amount
j.	personal_status	This categorical variable signifies the personal status of the individual
k.	gurantors	Categorical variable which signifies if any other borrower involved with an individual loan
l.	resident_since	Numerical variable that signifies for how many years the applicant has been a resident
m.	property_type	This qualitative variable defines the property holding information of the individual
n.	age	Numerical variable that signifies age in number of years
o.	installment_type	This variable signifies other installment types taken
p.	housing_type	This is a categorical variable that signifies which type of housing does a applicant have.
q.	credits_no	Numerical variable for number of credits taken by the person
r.	job_type	Signifies the employment status of the person
s.	liables	Signifies number of persons dependent on the applicant
t.	telephone	Signifies if the individual has a telephone or not
u.	foreigner	Signifies if the individual is a foreigner or not (considering residence country of the bank)

Data Details

b.:

• A11 signifies 0 (excluding 0) or lesser amount credited to current checking account. (Amounts are in units of certain currency)
• A12 signifies greater than 0 (including 0) and lesser than 200 (excluding 200) units of currency
• A13 signifies amount greater than 200 (including 200) being recorded in the account
• A14 signifies no account details provided

d.:

• A30 signifies that no previous loans has been taken or all loans taken have been payed back.
• A31 signifies that all loans from the current bank has been payed off. Loan information of other banks are not available.
• A32 signifies loan exists but till now regular installments have been payed back in full amount.
• A33 signifies that significant delays have been seen in repayment of loan installments.
• A34 signifies other loans exist at the same bank. Irregular behaviour in repayment.

e.:

• A40 signifies that the loan is taken to buy a new car
• A41 signifies that the loan was taken to buy a old car
• A42 signifies that the loan is taken to buy furniture or equipment
• A43 signifies that the loan is taken to buy radio or TV
• A44 signifies that the loan is taken to buy domestic appliances
• A45 signifies that the loan is taken for repairing purposes
• A46 signifies that the loan is taken for education
• A47 signifies that the loan is taken for vacation
• A48 signifies that the loan is taken for re-skilling
• A49 signifies that the loan is taken for business and establishment
• A410 signifies other purposes

g.:

• A61 signifies that less than 100 units (excluding 100) of currency is present
• A62 signifies that greater than 100 units (including 100) and less than 500 (excluding 500) units of currency is present
• A63 signifies that greater than 500 (including 500) and less than 1000 (excluding 1000) units of currency is present.
• A64 signifies that greater than 1000 (including 1000) units of currency is present.
• A65 signifies that no savings account details is present on record

h.:

• A71 signifies that the individual is unemployed
• A72 signifies that the individual has been employed for less than a year
• A73 signifies that the individual has been employed for more than a year but less than four years
• A74 signifies that the individual has been employed more than four years but less than seven years
• A75 signifies that the individual has been employed for more than seven years

j.:

• A91 signifies that the individual is a separated or divorced male
• A92 signifies female individuals who are separated or divorced
• A93 signifies unmarried males
• A94 signifies married or widowed males
• A95 signifies single females

k.:

• A101 signifies that only a single individual is involved in the loan application
• A102 signifies that one or more co-applicant is present in the loan application
• A103 signifies that gurantors are present.

m.:

• A121 signifies that the individual holds real estate property
• A122 signifies that the individual holds a building society savings agreement or life insurance
• A123 signifies that the individual holds cars or other properties
• A124 signifies that property information is not available

o.:

• A141 signifies installment to bank
• A142 signifies installment to outlets or stores
• A143 signifies that no information is present

p.:

• A151 signifies that the housing is on rent
• A152 signifies that the housing is owned by the applicant
• A153 signifies that no loan amount is present on the housing and there is no expense for the housing)

r.:

• A171 signifies that the individual is unemployed or unskilled and is a non-resident
• A172 signifies that the individual is unskilled but is a resident
• A173 signifies that the individual is a skilled employee or official
• A174 signifies that the individual is involved in management or is self-employed or a
• highly qualified employee or officer

t.:

• A191 signifies that no telephonic records are present
• A192 signifies that a telephone is registered with the customer’s name

u.:

• A201 signifies that the individual is a foreigner
• A202 signifies that the individual is a resident

Objective

As per predictions in the prediction problem. The objective of this problem is to predict the cluster number of serial number variable. Below are the following:

• Cluster number 1 (Correct value is 1) : When the value of credit_amount is between 4000 and 20000
• Cluster number 2 (Correct value is 2): When the value of credit_amount is between 4000 and 1500
• Cluster number 3 (Correct value is 3) : When the value of credit_amount is less than 1500

Evaluation Metric and Algorithm

• Accuracy
• Normalization_constant:100000