An environmental model of risk in consumer credit

AN ENVIRONMENTAL MODEL OF RISK IN CONSUMER CREDIT Bernie

Grablowsky'

THEORY DEVELOPMENT As behavioralists

in many fields

knowledge

of man and his

researchers

in several

or synthesized (14:10-14) of datd

on behavioral

and the

problem

behavior that the

adaptation

ledge

of consumer

been devoid

of

place.

research

various

behavior;

of any integrated

yet,

the

(3:29-33)

gap between

narrowly

defined models

is now some evidence in the

received the

integrated

to more general

and consumer have

field

theorization

our

environment,

theories.

specific,

There

advanced

his

have successfully

to bridge

findings

of marketing

have

with

application

operations

of

Many areas

into

research

of their

business

study

of business

have begun

in the market

both

areas

new knowledge Theorists

of

interdependerce

theory

cases and agreement from

sciences.

benefits

(27:27-32)

of our

of consumer of its

plethora

of consumer

can benefit

behavioral the

(12:22-27) the

credit

subject

knowhas

matter.

Although the marriage of research and practice, taken place, the hoped for offspring of theory

in some cases, has has not previously

However,

an original

been forthcoming.

this

paper

ceptualization of a viable theoretical credit. The proposed model is based 'Bernie Old Doninion

Grablowsky University,

now presents model of risk on a concept of

is an Assistant Professor Norfolk, Virginia.

con-

in consumer credit character

of Business

Management

at

108

and is developed from

finance,

combined

from

a synthesis

marketing,

with

of knowledge

psychology,

industry

practice

on consumer

and sociology.

and knowledge

to

credit

This

is then

produce

the

suggested

model. The theory the concept,

and its

which

credit

scoring

Risk

Measurement

model,

The problem

transaction.

based

and profitably

evaluate

is an application awarded credit

Usually, through

attention

quantitatively

research

of personal

(18:799-806) numerical

to which relative by an analysis

This

can serve

based

on a sound

variables

that

produce paper

as the

basic

the

credit based

businessman

a

effectively used today

numerical

information

scores

provided

models

are

by the

concept more

of the consistent for

and

is replete with data type of model. A

a person's

development

underpinnings

use financial

values are assigned in a experience in granting credit

literature of this

influence the

the

he could The method

point of past

a better,

presents

credit

since

decisions.

where

scoring

system possibly

a

(25:327-340)

scoring

risk.

of

in extending to extend

credit

by which

good and bad risks. Credit the inconsistent performance

could

Then

form

own judgement,

to providing

system

to both showing

psychological

first.

in the

businessman

ability

previous

applicants.

these

demographic data manner determined

the

credit

items

involved the

creditor's

has turned rating

(9)

Generally,

risk

of operations

to certain applicant.

the

upon the

gained

Recently,

be advanced tested

has been with

has depended

upon experience

will

be presented.

borrower

credit

profitably

will

of determining

to a particular first

development

has been successfully

basic

sociological

credit prediction

of a general such a credit

and

performance of theory scoring

credit which model.

109 The Need for

Theory

From the three

C's

early

writings

of credit

--

important

concepts.

textbooks

on consumer

in consumer

character,

capacity,

They have credit

credit

today,

and capital

persisted

from

until

in claiming

the

early

1900's

the

--

have

space to the

remained

in most present

time. Typically, applicant's the

capacity personal

lender

however,

and capital

balance

an idea

of the

relatively

easy

to make him appear

a better

obtaining

bureau

a credit

of most of the However, nearly credit

sheet

for

half of checks. To determine

banks

applicant risk

with

the

offering

estimate

The term

"character"

presents

meanings

to different

people.

to supply than

lender

character,

from

very

Because

of the

of the

three

the

any,

validity

has had to information.

because it has different deal depends on the evaluator's and his life of character

experiences. is a very

nature of present evaluative and because of the general

character, C's character

that

additional

is

the most

research

important

in this

area

processes agreement

(4:59), is

will

study reveal

of psychological

it

necessary.

several

accepted

and sociological theories

on character

is,

information By

Theory

A thorough sources

intangible

to credit

seems logical Behavior

is.

concept.

as applied that

It

make these

lender if

gives

Association,

do not

the

limited,

problems A great

This debts.

of accuracy.

Bankers

cards

sociological and psychological background (7:196) Thus, a minimum acceptable level nebulous

degree

credit

erroneous

can check

American

credit

the

he actually

a reasonable by the

an applicant's

make a subjective

to pay his

the

to a study

the (5)

statement.

ability

credit report,

from

and income

borrower's

information

according

are determined

literature formation.

110

As might

be expected,

these

theories

are

closely

related

to one

another and may be viewed with equal amounts of credulity. the development of our credit literature seems to be very aligned

and consistent

of character Relevant are

with

formation. portions

presented

here

what

of the

in order

is called

the

environmental to lay

the

environmental

theory

realistic

sense

Environmental ---

Theory

One of the influences

of the

earliest

on man's

on behavior

foundation

writers

behavior

and molded consisted

groupings

for

its

of his

Man's

groups.

group

vations

was not

importance

profound

(26)

were

He theorized

viewed

to the

social

and his Thus,

as being

face-to-face

behavior

standards

was

of an individual's

membership. first

for

partially of the

Veblen's of sociology, attitudes environment, reference

environmental

investigator

of

social

influences

and, in fact, many of his conclusions could hardly to much of our society today. However, Veblen's were

studies

the

Both so that

an individual's

in general,

of conformity

Veblen

wherein

his

seen to be a result

of

Veblen.

actions

culture

present

and aspired

subject

was Thorstein

peer

extension

be evident.

on the

by society,

or specifically

behavior applicable

will

in the marketplace.

influenced contacts

theory

theory

of character

to a more specific environmental theory of credit risk. theoretical references and empirical tests are correlated the

However, closely

his

because

time

and can be recognized

of the

stimulus

he gave

on be obser-

for

their

to further

subject. model

of man drew

cultural and behavior consisting groups,

on what

anthropology, are viewed of his

and face-to-face

are

now called

and social as being

culture, groups.

psychology.

influenced

subculture, (13:40)

the by his social

fields Man's social classes,

111

A more modern ment can be seen

treatise in the

researchers

indicate

character:

a persisting

produce

a rather

that

ment,

Peck and Havighurst are set into school,

and peer

Family Influences - -~-__ Character appears emotionally outside guide

powerful the

behavior

child's

character

to Peck,

"to

and act,

and mother

learned

Although there or inherited,

passed which

from

mirror

by the

child

but

each as just

tend

and

interaction.

A

character. child

does

According

learns

the

relationship

character

Forces

to shape

to feel

kind

of

with

him."

has been discussion as to whether it does not seem to be a trait but

intimate,

and parents.

they

a parent's degree,

and morally,

to child;

may be

segments:

person

his

(19:177)

character genetically

is

seem to be a trait

may be learned. Evidence

conclusion. though

it

by Rettelheim (21)(22)

is possible

improved

personalities,

treatment.

(19:179)

School

influences

by parent-child

have been in their

parent

and organization

shaped

between

startling

psychologically

father

content

develop-

influences.

formed

may indeed

an almost

although

of character

identifiable

negligible,

previously

as

which

behavior,

Cultural

to be predominately

are not

of study

readily

relationships

family

such a thing

and motives

the

(19)

but

group

is

attitudes

that

culture.

broad,

These

a lengthy

conclude

by the

develop-

and quality

After

three

of character

by Peck and Havighurst.

show there of

kind

inconsistencies.

classified family,

studies

predictable

are

influences

reported

pattern

there

of values

on social study

and by Red1 and Wineman

Many therapists to

teach it

children

requires

support

have demonstrated to have different, exhaustively

long,

this

that

even dramatically

intensive

Influence? An additional

environmental

influence

is felt

in the

classroom

112 as an individual evidence

has not

to whether induced Yet, it that

it

from

been able

merely

schools

to reinforce

discriminate

character

of doubt

character

as

structure

already

and on-going family experiences. empirical evidence and observation

between

maturity

The available

curtain

the

children

who outwardly

who show good character.

show poor

Possibly

seems to be highly

as a result

correlated

with

grades. Peck and Havighurst

possess social

precisely which of their

are

likely

likely

of outside

influence.

Peer ---

Influences

Group

The evidence

upper

of peer

end of

structure,

even after

Usually, behavioral

achievers

character

to the knowledge

in school

scale

also

tend

to

able to use it effectively. in anything they undertake.

goals

character

informal

is, than

influence then, than

group

and do it

independently

the

peer

period

partly,

what

peer their

group

already

a supporting

relationship

peer

group

of

that

is

interaction

j%fundamentalchanges

a lengthy

conclusion

tendencies force

the

their

to produce

and more effective can

antagonism or to assimilate

and they are to do well

whether

strong

parents

character

(19:151)

sufficiently this

poor

instability,

to make them poor

to achieve

is questionable

behind

of

with

intelligence.

have superior intelligence; They have an active incentive They are more

people

to concentrate

native

at the

that

qualities

and inability

regardless Subjects

report

those

system,

rationally,

causal

to adolescent.

to sweep away the

tends

and those

of this,

It

child

by the child's previous is fairly obvious from

character school

matures

group

influence

and,

child

gets

the

forces present. force

are partly,

peer

can be seen acting The peer in the

a force

The reasoning

influences from

clear.

is

in character

influence.

family

less

group

development

earlier because

group. to reinforce

is of

less

a

character.

113

This discussion emphasizing the primacy influences in character development is not to as indicating that the peer group is never a in character development. On the contrary . probable that the peer group might have been skillful guidance of interested adults, as a to change their character . . . (19:141) This

kind

of human influence

character,

although

Asch notes a person's "outward fact,

opinions force"

Riesman

increasingly the

Less

is

developed,

which

or reshaping

by their

peers,

values. the

that

do tend

in effect

character.

make up the

(1:151-162)

(6:430)

individuals rather

to influence In

are becoming than

by parents,

in

(23:4) influence

research

does

has a fairly

of peer indicate

permanent

groups

that

on an adult's

character,

structure

once

throughout

a

life. Consistency

Inter-temporal have tended subjects

new social to maintain toward

memberships

to signs

known about However,

-Character

the

group

of a person's

of their

way of shaping

an uncommon method.

and attitudes,

influenced

character. person's

is

informal

has pointed

definition

firmly

it

that

is a possible

of the family be interpreted formative force . . it seems used, under the treatment agency

life,

studies

on character

to show a stable, reached

adolescence.

and intellectual very

persistently

development

and maintenance

predictable pattern of character once Although many subjects learned

skills

as they

their

and in the mode of

deeply

reacting;

grew older, held that

feelings is,

their

they

appeared

and attitudes character

structure. In short, the ratings and the actual case histories both suggest that whatever pattern of moral behavior and character structure a child shows at ten years of age, he is far more likely than not to display into late adolescence; Both the case and, our belief is, for the rest of his life. records and the ratings which were based on them show that

114

there is room for change in later life; but, . . . they suggest that prolonged deep-going influences would be necessary to effect such a change, and that such influences are not likely to occur in the average person's life. (19:157) The evidence early his

in life

suggests

and once

direction

that

of character

simply

makes him more of

is the

possibility

of

or relationship

on the

is

kind

from

relatively

of

person.

of the

very

childhood

fixed.

Growth

emotional

emotional

changes

begins

early

An exception

due to a deeply

order

Basic

development

passes

growth that

change

child relationship. circumstances.

character

an individual

experience

intensity

in character

to this

of the

may occur

parent-

under

these

CHARACTER DEFINED

less

Character, permanent

which

in general, may therefore structure of an individual's

are reflected

is based

in his

on a cause-effect

dividual's

character.

of social

forms;

In this

concept credit

must

Cole

for

be oriented

toward

provides

is apparently "Character

the

between

context itself,

specific

this

definition

and an in-

character

purposes

credit

a starting speaking

social

This society

man is made by his

of character

However, textbooks

sense

as the more or attributes

and satisfactions.

relationship

in that

For a discussion definition.

drives

be defined personal

is

society.

the product (23:4)

is a satisfactory of this

character.

study

the

An examination

of

point. generally

is an intangible

when he says:

sum of

personal

attributes

. . .

(7:194) Beckman and Bartels The character and moral qualities

state

that:

of an individual which identify

is the aggregate him . . .

Character thus becomes credit character qualities combine to make one conscientious debts. (4:54)

of mental

when these concerning his

115 More specifically, Character comprises those makes him want or intend

which (4:54) With the

these

specific

credit

definitions

model

of

qualities of a credit risk to pay when a debt is due . . .

in mind,

credit

character

we will as it

now proceed

to develop

may be used to evaluate

risk. PERTINENT CREDIT CLASSIFICATION In a description

character,

Bartels

of those provides

qualities

a concise

that statement

VARIABLES make better valuable

credit for

future

reference. Positions of responsibility, trust, professional certification, and mental and physical skill generally engage people with qualities This is due largely to the personal which make for better credit risk. integration, and group development . . . as well as to the continuity, references which they involve. (2:312) debtors through

Willingness to pay is related to the social class of . . . Relations with groups affect credit character the attitudes toward debt which they engender . . .

What occupation may not reveal about credit character other activities of an individual sometimes do . . . Activity with welfare, cultural, educational, political, religious, and recreational groups, while it may not produce good credit character, evidences conspicuous involvement, which is generally compatible with debt responsibility. (2:314) In addition,

Bartels

gives

some evidence

of credit

capacity.

As ability to buy and to pay in a continuing existence is dependent primarily upon continually incoming purchasing power, earnings and the ability to sustain and increase them are of major importance in credit capacity . . . Information concerning earnings alone, however, is insufficient basis for determining personal credit capacity. Factors underlying earnings must be considered. Earnings are a reflection of one's ability and capacity to earn . . .; the type of employ-

116

ment in which one is engaged, occupational position for advancement, . . . industriousness, continuity and attitudes toward work. (2:316) In addition evidence

to these

of the

marketing

researchers

a new vantage

statements

relevancy

of

and opportunity of employment,

of a theoretical

behavioral

data

and psychologists

is

nature,

empirical

now available

explore

consumer

as

credit

from

point.

Plumner

has investigated

life

styles

and credit

card

usage

through Activity, Interest, and Opinion (AIO) research. (20:35) Life style research is designed to indicate the difference between heavy

users

and light

purposes.

The heavy

profile. light

In this users A wide

in life

membership,

and light

study

and community.

Opinions

were

the

study

of who uses

credit

questions

rather

indicates

than

a movement

others

and opinions

travel, areas

is basically cards

work,

style

heavy

and

are covered as club

and entertainment.

as interest

in home,

as economics,

politics,

the

indication

of a definite

chological

variables

the

family, and

factor

profiles

significant

variables,

relationship card

credit

was used for

between usage.

card

income

users.

to variables groups

by Plumner

and since analysis,

and and

similar there

sociological Further

AI0

variables

are similar

of low

analysis

segmentation

style

as independent

of classifying

up as significant and credit

marketing

use of life

used by Plumner

to build

Since

keep turning

now.

a descriptive

and why,

demographics

variables

researchers

to determine

is presented

into

such activities

in the method

bankrupts.

variables

market

interests,

such

segmentation

by some life

measured

on such topics

pure

The independent used by other

the

market

investigated.

Although

personal

for

are identified

organization, include

usually

segregated

Plummer

represented

business

users

Plummer

research. community

Interests

of a product,

of credit cards. range of activities,

style

study

users

evidence

is an and psyof this

117 According man is simply

toMartineau, economic models of man assume a rich a poor man with more money. Economics overlooks psydifferences between individuals which may result from

chological different

social

class

Martineau differences

memberships.

suggests between

that

past

different

the use of money. (15:122-123) richer dimension than income As a result of past work Martineau has identified Dolphin,

held by the bankrupt's linked to the choice difficulty. tudes the

project.

and little

study

desire

found

and relatives as an escape of the

touched

of

personal

the

troubles,

of desire

study

evidence

Goble

lack

to take

the

attitudes

debtor's

not

for

low

the

atti-

focus

of

a credit He built

behavior

on a combination

of biographical,

aptitude,

tests.

factor

Goble

number

low income

user reported

and Matthews

of factors of

credit. by Plumner

in their

major

bankruptcy

that bankruptcy screened.

a large

based

analysis,

money

or budgeting,

Matthews concluded could be effectively

groups.

bank-

and creditors'

ledge

By using

Other

toward

debt,

found

in handling

rating. planning

toward

in 1967 that income

of thrift action

of financial

to pay or attitude

hypothesized

be obtained

to those

work, classes.

that

Matthews

a good credit

debtor

collection actions. (16:283-284) cases due to attitudinal factors

a smaller

view

were possibly from financial

on and were

brankrupts,

little

to maintain

influencing

were marital lack

only

to have established

factors

bankrupts,

limitations

were

way they

(8:107)

In another rupts

of consumer

of

credit

are psychological

and the

area and his own original traits of various social

peer groups of bankruptcy

Because toward

show there

classes,

Social class, therefore, becomes a class in which to view a person's actions

in this several

in a study

studies

social

profile

and credit was able

could

set of questions know-

to separate

which effectively identified the typical Many of his factors were very similar in his

bankruptcy

life

studies.

style

study,

and by Dolphin

118 The applicability through method type

answers,

the

applicant

would

be unable

as he can now do with

of credit

mation

for

application.

reliability,

A correctly the

few attempts

at credit

classification

attitude measurement seems to hold promise as a possible of classifying potential credit users. The usefulness of this of measure would be even more important if a test could be set

up so that type

of these

worded

necessity

the

presently

Although it

costs

attitude

used

a creditor

bureau

could

bias

his

financial-demographic can check

money to obtain

measure

of a credit

to consciously

credit

possibly

this

infor-

bureau

reduce

reports.

or eliminate

report.

AN ENVIRONMENTAL MODEL OF CREDIT CHARACTER This model

paper

based

earlier, described.

the

A brief several

applications

paper

structure

will

This

somewhat

theory study,

consisting

of this forces.

as they concept paper.

the

to the

an attitude

patterns. flow

present

As noted

diagram

detailed

credit

on character

divergent

concepts,

However, as the

will

be

empirical granting

for

this

formation

each with study

one most applicable

its

the

process

attributes of parents,

which school,

is

apparent

as a foundation

formed

and peer

personal and actions

theories

environmental

of credit character may be built. credit character will be defined

which are reflected in the individual's responsibility as shown by his intent obligations

behavior

interaction

literature

of an individual's forces

for

structure.

of the

has been selected

mental

induced

and devotees.

on which a relevant Thus, for this

foundation

contributions

market

review

basic

model's

beneficial

in a dichotomous

theory

general

A subsequent

and its

reveals

the

on environmentally

only

model

now presents

as that

by environgroups,

concept toward

and

of debt payment

of

come due. of credit

Character

The environmental

character is assumed forces

are

broadly to

describes

be a function

listed

as parents,

the

nature

of environmental school

and

119

peer

groups,

process. his

in that

order

concept

is assumed debts

evidence

in the

character

is assumed

toward

payment

of an individual's

by that

as they

importance

character

of responsibility that

may be represented his

of

The individual's

person's

of debts. concept

intentions

formation

to be mirrored

by

Finally,

of credit

and actions

it character

in meeting

come due.

Mathematically,

the

definition

individual's concept of debt responsibility

may be seen as shown below: individual's character

=f(

credit

L-11

1

where individual's If

we combine

proposals

submitted

for

credit

equation

risk Czl,

credit

character

existing

theory

here

on character,

may be completed.

= f (environmental

on credit the Thus,

capacity

with

functional equation

forces) the

relationship Cl1 now becomes

such that concept = f ( individual's of debt responsibility

;r"e;;l";y;;s

)

individual's ability to pay

+f(

c21

1

where individual's in equation individual's ability to Figure character

1 combines to give

the

concept of debt Cll, and

pay

=f(

responsibility

non-behavioral mental

the

effects

of credit

total

model

relationship

environforces

is given

1

capacity to credit

with

credit risk,

as

-------

peer

groups

Forces

- 4-I

1

1

matters (a) income (b) budgeting (c) responsibility Education (a) mental ability (b) self (c) children Self Image (a) moral values

.-_ from existing theory on credit capacity

f

BEHAVIORAL MODEL OF CREDIT RISK

Figure

character

Credit Character and Capacity

L------------___

r ---

and other members

parents family

,+@

school

r

Environmental

Variables Representing Individual's Concept of Debt Responsibility and Capacity to Pay

121 expressed in equation C21. An examination of the not

now used

a graphic

in credit credit

by credit

risk;

analysts

reveals

evaluation

representation

determining

model

presence

of variables

decisions.

of

influential

the

theory

in their

the

quest

The model provides variables involved in

encompasses for

a reliable

many areas risk

neglected

model.

HYPOTHESES The previous of this

few pages

have

thus

suggested

the

first

hypothesis

paper. Hypothesis I: Sociological be used as discriminating segregating active credit "bad" credit risks.

Hypothesis

I will

test

the

model.

In order

proposed results

model, obtained

its discriminating by using financial

provides Hypothesis variables applicants variables.

the

to test

second

effectiveness

&SOZU~~

scoring

comparison

and psychological data can variables for effectively card users into "good" and

the

relative

of the

effectiveness

proposed

of the

ability will be compared to the and demographic variables. Th

hypothesis.

II: A credit scoring model using behavioral will provide better discrimination of credit than a model based on financial and demographil

TESTING THE MODEL Data

Sources In order

were

collected

response of

to test

from

people

associations credit

from

the

two groups

questionnaire

who had recently for

theoretical

model

of people

with

a Likert

borrowed

home mortgage Group investigations.

of credit

via

risk,

data

a self-administered Group I consisted

scale.

money from

loans and were I received their

savings

and loan

subjected to thorough questionnaires via

122

U.S.

mail.

In addition,

collected

on each

behavioral credit

financial

respondent

questionnaire. card

ultimately

returned,

The 9 unusable

Each member of Group mailed

misunderstanding

Group

data

II

are considered

criteria.

Group

cases

also

to the

risks

II

based

Group

who were

being

counseled

poor

on their for

out

their

of

being

purchase.

or defaulted

questionnaires

and demographic

rating

exclusively

position

one credit

of

these

by most credit

financial

the

Because

credit,

to be composed

least

at the

Columbus.

risks

present at

Financial

sessions.

credit

considered

have many delinquent

on their recent records. Group II members filled counseling

of Greater

both

selected

to pre-select

people

thus

II members

to return were bank.

of over-extending

study.

answers,

or failure respondents

was no attempt

Service

112 were

the

the data

very

or in default

for

incomplete

into

of

is

usable

from

questions,

There

I members,

inclusion

experiences

people

delinquent

study.

Counseling

past

103 were

100 complete

before

consisted

Credit

one or more

of poor

of the

in the the

Consumer

were

I was an active

to Group

resulted

The first

inclusion

or screen

out

and of those

questionnaires

questionnaires. for

data attached

user.

Of 130 questionnaires

obvious

and demographic

by a questionnaire

In most purchases

at one of information

their

of the

types usually requested for credit applications was also available for each subject. Each member of Group II was also an active credit card

user

up to the

soon as the

results

was halted. included

There

time

his

from

100 respondents

was no attempt

in the Group

The Oiscriminant The collected

counseling

II

sessions

were

were available,

to pre-select

the

initiated.

As

data

collection

respondents

sample.

Function data

were

randomly

separated

into

an analysis

123

sample

of 75 observations

from

each of Groups

I and II;

a validation

sample of 25 observations from each group was also formed. in accordance with the split-sample approach for validating equations as reconended The analysis sample multiple

discriminant

analysis

tically significant step of the program adding the

most

second;

explanatory

contributing

power next

ability,

two were

examination

of

their

selection.

Eight

Variable

best

the

model

entered

first;

power

independent further

should

of the

were study. the

entered the equations,

others.

selected,

based

Of the

equations

"best"

clarify

statis-

At each variable

had been entered into produced 36 behavioral

considered

selected

classification

is presented

models.

the

on

An

reasoning

efficiency

with

as equation a minimum

Cal was able validation

discriminant

model

and several

two equations

several

procedure. with the

most explanatory

for

eventually

(11:250-258) via a

behind

Equation

The first Equation

produced

of the

necessarily

was examined

classificatory

examined,

in the

the

each one was not

Each equation

the

which

and so on until all variables This procedure, in effect,

equation. although their

program

and Morrison. was analyzed

equations using a stepwise a new variable was entered,

to the

variable

by Frank, Massey, of 150 observations

This is predictive

power

to correctly classify Only one other sample. as equation

Cal.

zh = eAl - eA2 eA1 + A2

number

Csl.

It

had

of variables.

48 of 50 observations equation had as good a

124

where:

A, = -38.12

+ 4.71X1

+ 4.07X,4

+ 0.07X,,

+ 2.61X2o

+ 2.08X12

+ 3.05X28

+ l.83X34

- O.38X35 A2 = -19.41

+ 3.80X1

t 1.40X14

+ 0.9SXll

+ l.92x2o

+ 0.60X12

+ 2.36X28

+ 0.41X34

+ l.lox35 e = natural The value the

of Zrritical

subject

than

each

the

the

observation,

had been correctly is

be classified

0.00

By examining for

= 0.00.

should

to or less

presented

log

subject

confusion it

of 2.72.

Thus,

if

Zh is greater

as a good risk. is considered matrix

If

to determine

The confusion

than

0.00

Zh is equal

a bad risk.

and posterior

was possible

classified.

as Table

value

probabilities which

matrix

for

observations equation

C31

1. Table

1

CONFUSION MATRIX OF VALIDATION SAMPLE-EIGHT VARIABLE EQUATION

True Classification Group Group

I (Good Risk) II (Bad Risk)

Number Classified As Group I Group II (Good Risk) (Bad Risk) 24 1

2:

Total

I:

125

By normalizing total)

it

will

is

Table

possible

be classified

1 (dividing

to

show the

under

each table probability

any of the

listed

Table

that

Group Group

I (Good Risk) II (Bad Risk)

the

probability

are due to real be tested

of correct classification by using since both samples are of equal size,

classification

is only

50 percent.

results

of using

differences data,

in the the

F-test

two groups

(17:156-163) equation

C31

and not due to chance

is performed.

The hypothesis

to

is: There is no difference and Group II. [31 with

52.09.

is significant

This

a 1 percent have occurred

between

8 and 141 degrees

probability by chance.

at

1 percent.

that the results The hypothesis

that the equation represents To test the significance 3.

1.00 1.00

classification

the

For equation

Table

0.04 0.96

that

of the Ho:

is

Total

of correct

To make sure occurrences

SAMPLE--

of Classification Group II (Bad Risk)

0.96 0.04

There is a 96 percent probability equation C33. By chance alone,

row

2

Probability Group I (Good Risk)

Classification

by its

any observation

groups.

NORMALIZED CONFUSION MATRIX OF VALIDATION EIGHT VARIABLE EQUATION

True

value

the means of Group

of freedom, Thus,

the there

F value is less

I is

than

indicated by Table 1 could is rejected and the conclusion

a true difference in the two groups. of each variable in the equation see

126

Table

3

F VALUES FOR EQUATION VARIABLES-EIGHT VARIABLE EQUATION

Degrees Variable Number

Variable

1

:;: 32: 35

values

that C33

= 1141

Name

the

have a high variables'

are

because

level

of

to the

variables

0.03

4.92 8.11 10.98 43.76 3.67 3.56 6.56 9.68

significance

contributions the

Significance Level

F Value

education budgeting expense planning savings and checking accounts living beyond means increasing income achievements determining course of life

;:

All

of Freedom

0.01 0.01 0.01

0.06 0.06 0.01 0.01

and the

conclusion

explanatory

represent

true

power

differences

is

of equation in the

two

groups. All equation rather

the

preceding

C33

represents

than

We should equation

differences be able

C33

with

Seventeen --._ _-.. Variable -.- -...In addition efficiently variables

true

were

made to statistically

differences

resulting

to get

equally

similar

data

from

in Group chance

prove I and Group

occurrences

good classification collected

II

of the

of data

in a similar

that data.

by using

manner.

Equation -___ to equation

discriminate were

tests

required

[al,

between by the

equation the

C41

two groups,

function

zh = eA1 - %2 eA1 + A2

to attain

also

was able

although

to

additional

such a good dichotomy.

127

where:

A, = -69.41

+ 3.03X,

- 0.02X3

+ 2.46X7

- 3.16X,o

+ 1.13X,,

+ 2.07X12

+ 4.92X14

t o.39X,5

+ 3.O6X,g

- 3.02Xzo

+ 3.48X2,

t 5.55Xz2

t 0.96Xz6

+ 1.87Xz8

- O.52X34

t 1.O8X35

+ 3.42X36

A2 = -50.65

- 1.76X,

- 0.69X3

+ 3.51X7

- 2.61X,o

+ 1.84X,,

t O.5OX,2

+ 2.56X,4

+ 0.10X,5

+ 4.35X,g

+ 2.44Xzo

+ 3.17X2,

+ 4.92Xz2

+ 1.40Xz6

+ 0.76Xz8

- 1.65X34

+ 2.49X35

+ 2.72X36 Z

The confusion validation

= 0.00.

critical

sample

matrix

showed

that

two observations

from

the

were misclassified. Table

4

CONFUSION MATRIX OF VALIDATION SAMPLE-'SEVENTEEN VARIABLE EQUATION

True Group Group

Classification I (Good Risk) II (Bad Risk)

Number Classified Group I (Good Risk) 24 1

As Total 1 24

25 25

128 By normalizing

Table

4 the

classificatory Table

efficiency

can easily

5

NORMALIZED CONFUSION MATRIX OF VALIDATION SEVENTEEN VARIABLE EQUATION

True Group Group

I (Good Risk) II (Bad Risk)

Equation

['r]

50 percent

also

Classification

As Group II (Bad Risk)

by chance

Total

0.04 0.96

has a 96 percent

the

classification

1.00 1.00

efficiency

versus

alone.

significance

of the

equation,

the

F-test

procedure

used. There is no difference and Group II.

Ho: For equation 26.51.

with

C41

This Ho is

rejected

Group

I and Group To test

Table

6.

the

These

exceptions.

Equations variables

level

represents

the of

true

F value

I is

significance. differences

in

of each variable have a high

even with

equation

the

itself

four is

in equation

significance variables

still

C43,

level,

highly

see

with

four

of questionable significant

and has

efficiency. C31

these from

means of Group

freedom,

1 percent

equation

significance

the

of

the

II.

variables

discriminating

indicating

at the

and the

However,

significance,

between

17 and 132 degrees

is significant

Thus,

high

of

SAMPLE--

0.96 0.04

expected

To test is

Probability Group I (Good Risk)

Classification

be seen.

and [Q] two subjects

the

other

both

misclassified were

48 subjects.

remarkably

the

same two observations,

different

in the

relevant

129 Table

6

F VALUES FOR EQUATION VARIABLES-SEVENTEEN VARIABLE EQUATION

Degrees Variable Number

Variable

:

of

Freedom

= 1132

Name

Significance Level

F Value

student education ability

2.05 6.73

0.15 0.01

1;

ability spending

4.09 1.01

0.32 0.05

;: 14 :9"

budgeting expense planning savings and checking accounts record of expenses of importance budgeting

9.85 2.89 30.76 4.36 0.50

0.09 0.01 0.01 0.04 0.48

2': 22 26 28

importance living beyondof means credit rating acceptability of bankruptcy secure job increasing income

0.53 1.92 1.87 0.91 6.54

0.17 0.47 0.17 0.34 0.01

3": 36

determining achievements course success in carrying

3.45 6.52 1.79

0.07 0.01 0.18

Of the the

better

variables

Risk

two equations model

and is,

from

on the

average,

Class-Variable Because

of the of risk

equation

relationship class

of life out plans

reviewed

above,

an operational

therefore,

The variables

c41. level,

toplanlearn

than

point

simpler

in equation those

equation

[33

of view.

and easier also

C31

It

has less

to use than

have a higher

in equation

seems to be equation

significance

CLII.

Relationship [33

between

is presented.

was the

best

behavioral

its significant This will help

equation,

a discussion

variables and the prediction to show the importance of the

130 individual's the

environments

difference

sample

the

direction

By comparing variables,

as factors

between the direction

of answer

of each

equation

coefficients,

it

variables

and their

influence

instrumental

1

group's

each net

the

:;: 28 zz

A person's credit

risk;

converse higher

education the

result

credit

is his

presented

credit

in Part

The amount expenses I spent

risk.

Net Result Group I Group II (Good Risk) (Bad Risk)

surface,

this

be raised

risk.

of time

time

11)

t

budgeting

is contrary is the

a person inversely their to the

effectiveness

is

related

better

educated

the the

in agreement influences

spends

expenses proposed of Group

to his

risk.

The

subject

with

the

is,

the

relationship

on character.

on budgeting

related

t

t t t t t t

positively

the

The less This

is

1) is

education,

I on environmental

(variable less

the

the

FOR EACH RISK GROUP

Name

be stated.

of

7

(variable

better

may also

of the

equation

education budgeting expense planning savings and checking accounts living beyond means increasing income achievements determining course of life

::

to

and the

RELATIONSHIP

Variable

for

to analyze

on each Table

Variable Number

scores

question,

is possible

DIRECTION OF VARIABLE

in explaining

distributions.

to his than risk II’s

or planning risk

Group

class. II.

model. budgeting

Group

On the

The question methods.

131

Group

II may have expended

but with

less

competence.

contradictory

results.

additional

more

time

This

is

planning a reasonable

Although it presented below

evidence

their

expenditures,

explanation

for

the

may not be the correct explanation, does tend to confirm this con-

clusion. The relationship to pay all

his

one.

This

indicates

they

cannot

spend

so that

they

expenses

as they especially Group

the

of

The latter

money is

a direct

make so much money that themselves

income range

sufficiently

to cover

explanation

wide

enough class

their

seems more rea-

of incomes

represented

II. control

income

a checking risk.

budgeting

of a person's

risk

budget

from

of the

to credit to live to risk

either

they

money left

in both

related

The ability directly related his

or else

in view

a balance

importance

measure

good risks

come due.

having

12) and his

that

to successfully

is directly

respondent

all,

I and Group

Ability maintain

it

the

(variable

have enough

sonable, in both

between

expenses

and a savings This

ability

one's This

financial

income

(variable of

health. 20) is also

be considered

and willingness

therefore,

evidence

(variable

could

and,

account

is additional

to a person's within class.

and expenses

another

to successfully

budget

expenses. Change

related, a better end result has,

in income

with risk of

income

change

his education, ambition, The ability of a person

directly

related

to education, factors determine related

(variable

to risk. mental

not measured the to risk

28) and credit

risk

are directly

a person whose income has been steadily rising than a person whose income has not been rising.

course class.

ability,

could

be due to the

type

of job

being The a person

and other factors. to achieve his goals (variable 34) is This, like variable 28, could be related

here.

ambition, The ability

of his

life

(variable

perseverance, of the subject 35) was also

and other to independently directly

14)

132 Except [a]

were

for

variable

positively

congruent

with

11,

related

the risk

all

the

significant

to risk

model

class

proposed

variables

and the

in Part

in equation

relationships

I.

The discrepancy

with variable 11 may be more illusory than real; expecially, effective results of the subjects' time spent in budgeting that

is,

his

real

In order

to

time,

rather

than

his

were

expended

time,

if the expenses,

were

measured

directly. probe

the

very

basic

causes

here, a researcher would have to interview more extensive psychological testing than The variables used use. for more basic underlying tested. to probe both

For a credit these

federal

and state

on variable-risk

are

forces.

rarely Present

sponsored,

tends

relationships

are

contained

only

surrogates

of the

individuals

are the

resources

truth-in-lending to legally

is detrimental

to better protect Within the scope

results

possibly

and motives model,

The legislation

but it does serve users of credit.

available legislation,

prohibit to credit

such research

the rights of active and potential of this paper, the above observations sufficient.

I

The most accurate equations possible

study

drives

scoring

underlying

investigations.

Hypothesis

in this

of the

subjects in depth using this author was able to

and most

have been discussed to draw a conclusion

statistically

significant

behavioral

and tested for validity. for the first hypothesis

It is now of this paper.

Hypothesis I: Sociological and psychological data can be used as discriminating variables for effectively segregating active credit card users into "good" and "bad" credit risks. Based on the (equations their

high

hypothesis

results

of the

C31 and C41) with level should

of significance, be accepted.

their

first

two behavioral

accuracy the

equations

of classification

conclusion

is that

and the

first

133

THE FINANCIAL The first order

hypothesis

to test

the

and financial provided

of

second

this

paper

hypothesis,

discriminant

and tested

DISCRIMINANT

for

has now been proven.

the

models,

FUNCTION

comparison

a financial

statistical

In

of behavioral

model

must first

be

significance.

The scoring model used as a base for the proposed financial discriminant equation was obtained from a local company which has had many years has revised

experience

with

and updated

The company's classifying

its

approximately

credit

their

models.

times rode1

applicants.

does

a model

applicable

equations

model

are the

same, not

as a starting excess

financial

used by the

data

the

point

population

on the

Fifteen

subjects

analysis containing

procedure. 13 variables,

behavioral

equations.

functions

which

were

is not

mentioned

coefficient

equations

as

basic model is fairly However, in order to

to the

equation

company

in order

number of questions that possibly also contributed

of has

specific

sample

in

as required produced

and C41.

C31

The resulting exact

decade.

company

this paper, the variable coefficients have been modified by using the same discriminant analysis technique which behavioral

last

a good job

the

Columbus'

proper to say their used in this study.

The company

in the

Since

of metropolitan

it is sample

produce

several

feel card

50 percent

active card users, applicable to the

own scoring

models

representatives their

more clearly

its

values. to eliminate

used

were produced After examination produced Equation statistically

study.

the

the

variables

model

necessity

was required questionnaire

This

was used

of collecting reduced

the

to answer response

and rate.

using the stepwise discriminant of the data, only one equation,

results [s]

Only

An existing the

in this

each subject to the high

now, therefore,

above.

close

was also significant.

to those

one of the

of the

two

few financial

134

z

= eA1 - eA2 h

where:

A, = -79.67

+ 3.8OY, + l.43Y6

t 0.50Yg

t l.07Y,o

A2 = -53.72

+ 1.78Y4

+ 1.98Y7

+ 0.19Y8

+ 0.46Y,,

+ 0.73Y,2

+ 2.22Y,5

+ 2.78Y1

+ 0.29Y2

+ 0.53Y5

+ 1.33Y6

+ 0.31Yg

+ 0.42Y,o

+ 0.06Y14

+ 2.05Y4

•t 1.79Y7

- 0.14Y8

+ 0.32Yll

+ 0.29Y,2

+ 2.47Y15

= 0.00.

Z critical The confusion

+ 0.69Y2

+ 0.67Y5

+ 0.18Y,4

dichotomous

c51

eA1 + A2

matrix

relationship

in Table of

the

8 shows the

financial

Table

fairly

well

defined

data.

8

CONFUSION MATRIX OF VALIDATION SAMPLE-THIRTEEN VARIABLE EQUATION

Number Classified True Group Group

Classification I (Good Risk) II (Bad Risk)

(G%?~i~k) 24 2

As Group II (Bad Risk)

2:

Total

E

135

By normalizing ificatory

Table

efficiency

8 it

is easier

of equation

to view

the

Table

Group Group

I (Good Risk) II (Bad Risk)

It both This

is

0.96 0.08

possible

to see the

from a pure classification equation will classify of the

good risks

of 12 percent

versus

8 percent

is compounded

when the

costs

The null

hypothesis

is

because

of true

discriminating of

chance Ho:

For equation

C51 with

35.81. and the

This

because

of true

is

that

Total 1.00 1.00

of this

as bad risks, the

or a total

behavioral to insure

differences

in the

results

in Group

of each variable

equation

[51

two groups

is

and not

data. between

at 1 percent. the

The error

are considered.

tested

of the

misclassification

equations.

of misclassification again

function,

and from cost viewpoint. of the bad risks as good risks

13 and 136 degrees

differences

The significance

efficiency

is no difference I and Group II

is significant

conclusion

lower

for

occurrences

There Group

As

0.04 0.92

ability 8 percent

and 4 percent

because

SAMPLE--

Probability of Classification Group I (Good Risk)

Classification

class-

9

NORMALIZED CONFUSION MATRIX OF VALIDATION THIRTEEN VARIABLE EQUATION

True

relative

C51.

the means of

of freedom,

the

The hypothesis indicated

I and Group is tested

in Table

F value

8 occurred

II. in Table

is

is rejected

10.

136

Table

10

F VALUES FOR EQUATION VARIABLES-THIRTEEN VARIABLE EQUATION

Degrees Variable Number

of

Variable

Name

0.01 0.01

dependent ofstatus

5.08 2.54

0.03 0.11

1.31 1.61 1.73

0.25 0.21 0.19

loan

4.68 8.42

0.03 0.01

ofwithsecond non-local loan stores with credit jewelers

27.13 1.91 1.90

0.01 0.17 0.30

accounts purpose accounts

two variables is highly

have

children

loan

source ofof second purpose first

but

a high

(equation accurate

hypothesis

of this

a financial

and statistically

equation

CSI) which

and highly than

significance

level.

are both

in dichotomizing paper, model,

that the

(equation highly the

There

are

as

of the

and a financial

statistically

data.

a behavioral

results

[sl)

significant

To prove

model

the

second

is more accurate

two models

must be compared

tested.

COMPARISON OF BEHAVIORAL AND FINANCIAL

and financial

The equation

significant.

We now have a behavioral equation

Significance Level

F Value

14.83 10.72 62.37

weekly telephone earnings status source of first

All

= 1136

type bills ofpaidbank accounts length of time at residence marital number

a whole

Freedom

several

criteria

on which

functions

could

be examined.

the

ANALYSES

efficacy The first,

of the

behavioral

and of the

137 greatest

importance,

classifies in the

subjects sense

contained Relative

that

would from the

in the

be the

accuracy

an independent

functions

validation

with

which

validation

themselves

were

not

their

from

data

sample.

Classificator_y_Efficiency --I----._

into

correctly

independent

built

_

From Table 2 and Table g it is obvious that the eight-variable equation has a slightly better ability subjects

the model

sample;

correct

groups.

The degree

is 8 percent versus 12 percent for On the surface this difference model.

of

behavioral to classify error

equation [57, is interesting,

C31

the

for

equation

financial but not con-

clusive evidence in itself that there is any real difference in the discriminating ability of the two functions. However, by using the Kilmogorov-Smirnov to determine Using the

null

if the

calculated

one function

"D"

by using behavioral

is

is that the

better

there

behavioral function is,

than

the

it

is possible

other. by Siegel

(24:130),

"D"

is

less

proportion of errors C31 and equation Csl. than

1.0.

With

"D"

of significance.

=

less

than

as presented

in the equation

if

Jp

samples,

is:

level

1.36

large

test

is rejected

=

Since

is truly

to be tested

a 1 percent

D = 1.36

conclusion

for

There is no difference resulting from using

hypothesis for

test

Kolmogorov-Smirnov

hypothesis Ho:

The null

two-tailed

J

1.0,

is a real

1.36

5o 625

the

da1

=

c61

0.575

hypothesis

difference

is rejected in the

model rather than the financial therefore, more accurate than

results

and the obtained

model. The the financial

138

function

and the difference

pelative

Cost

investigation

However,

it

is

is also

cost

consequences

of using

data

available

are not

generally good loans

(27:g-13) that

to cover

loans,

for

nearer

of

is

of while

would

if

credit

and he is allowed

only

be the

sold,

C53

ratio

for

in-

not

unlike

equally

misclassifies

misclassified

a greater equation

C31 is

which

misclassifies

basis.

we could

profit

from

the

purchaser

if

research,

the

in addition

The exact

maximization

to this

to

one bad loan.

probably

two functions, have a model

to make credit

At any rate,

expenses

action. for

possible

goods

payments. other

It

four

loans. C31

cost

some infor-

a higher proportion of as a bad risk, he is

and the profit which would have been made on credit However, if a true bad risk is classified as a good

risk of the

Even though is from

cost is

possible

costs.

from

a higher proportion of good risks rather than bad risks. If a true good risk is classified refused credit sales is lost.

other.

profit

on the

academic

the

there

the

to loss

equation

on a relative

the

resulting

equation

Of the

be better

over

reporting

consumer

most purely

to examine

takes

of profit

bad risks.

to optimal It

level.

misclassification

it

losses

2 and g show that

good and bad risks; proportion

the

ratio

types

for

researcher,

relative that

Zaegel the

other

Tables

to this

by Zaegel

Although

stallment

sufficient interesting

one equation

known about

has been reported five

0.01

I

cost mation

at the

Efficiency

The above purposes.

is significant

the will lost

ratio

of subjects depends

a part

of

sale

but

should

seller to the

of profit not

purchases,

this

the also

default

loss the

incur

collection on the

to reject study.

(10:406)

value

credit costs

credit

in each factors

not

entire

on his

profits

on other

will

not

risk

and trans-

class

available

139

Hvoothesis

II

A decision

is now possible

paper.

II: A credit scoring model using behavioral will provide better discrimination of credit than a model based on financial and demographic

Hypothesis variables applicants variables. The evidence

II of this

on Hypothesis

indicates

that

this

hypothesis

should

be accepted

as

true. CONCLUSION The first hypothesis be used as classificatory

tested

using

Several

equations

equations

Two equations results. were

tested

for

significance levels

further

promise

of offering as well

variable

acceptable

levels.

as the

base

general the

equations groups

two best

which question

the

shows they

of questions. behavioral

for

items groups

Table

are contained

0.06

the

results

in the

two

each of the

variables question

questionnaire.

to each equation

best from

was chosen

against

from

11 shows the final

the

levels

included

and the major

on the

have contributed

items

of

had significance

equation

are

equations,

had a level

variables

comparison which

significant

in the

equation.had

contain

equations

and highly

themselves

This

program.

and testing.

significance

obtained from financial models. An examination of the variables behavioral

positive

The individual

with

testing

analysis

An eight-variable

areas

analysis

as each variable

The equations 0.01.

to 0.01.

within

additional

for

discriminant

two functions,

in all

well

paper--that behavioral data can in a credit risk model--was

a stepwise

examined

validity.

0.49

results

to 0.01, for

were

of at least

from

test

from

showed

These

of this variables

and the

used group

three in in

All significant

variables are fairly well distributed The financial and demographic

throughout each group. variables produced only one equation

which

and had high

was both

statistically

valid

classification

power.

140

Table BEHAVIORAL VARIABLES

Equation

Variable Number

EightVariable

1 :: :i 5: 35

SeventeenVariable

1 : 10 :: ii :i I: fi z9 36

Variable

11

USED IN SIGNIFICANT

Name

education budgeting expense planning savings and checking accounts living beyond means increasing income achievements determining course of life education student ability ability to learn spending plan budgeting expense planning savings and checking accounts record of expense importance of budgeting living beyond means importance of credit rating acceptability of bankruptcy secure job increasing income achievements determining course of life success in carrying out plans

EQUATIONS

General Classification Formal Schooling Philosophy II of Life II II Achievements II I, Formal

in Lil

Schooling II II Philosophy of Life ,I II II 0, ,I II II 10 Achievements in Lil 0 II I, lb

141

Since

this

is not the

function

surprising

was based to find

15 variables--l3

variables

this

variable significant risks

behavioral as the

than

in misclassifying had equal is not

the

not

Solely

result

because

bad risks

both

but

a cost

it

inclusion

is

better

The conclusion the behavioral

and a classification

eight as

is contrary usually

involved equations

good and bad risks. than

13

as the

more bad

The behavioral

both

of

variables

this

losses

it

all of

as well

financial

basis,

higher

for

model, nearly

to misclassify

on a cost

rates

equation. test, that from

the

tended

of the

the

subjects

as good risks.

methodology,

15 variable contains

Even with classify

also

misclassification best

equation

nor, were variables.

equation

from the financial Kolmogorov-Smirnov equations

did

equation; behavioral

good risks.

desired

best

to be exact. equation

The financial to the

on an existing

the

that

This

resulting

was, as confirmed by the equations were better basis.

142

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