Consumer
Lending Defined
Business of consumer
lending deals with extending credit to individuals for personal
or
household use. There is no single generally accepted definition for
consumer lending
but as broadly defined, it includes all forms of installment credit
products
such as auto loans and open-end credit products such as credit cards.
Two types
of installment loans for personal use, home mortgages and lease
programs, are
normally excluded from the consumer lending category.
Let us look at these distinctions
before we start
using the term ‘consumer lending’ throughout this book.
Traditional
installment credit products have a fixed amortization period and paid
back in
equal periodic (monthly) payments of principal and interest. Loans to
purchase
automobile or boats, education loans and personal loans etc. are some
examples.
An Open-end credit,
also known as a revolving line of credit, is a pre-approved loan and
the
account holder could use the credit repeatedly up to a certain limit.
The account
holders may payoff the entire balance each month or payoff a part of
the amount
with interest accrued on the balance outstanding. A
credit card or a line of credit offered by
retailers are two commonly available
revolving credit products.
Throughout this
text book we refer to consumer lending to denote revolving credit
products with
following characteristics.
- A pre-approved credit
limit amount.
- Open to buy (available
credit limit) decreases and increases as funds are borrowed and then
repaid.
- The credit may be used
repeatedly.
- The borrower may repay
over time (with accrued interest), or in full at any time.
Common examples of
revolving credit lines are bank credit cards, store credit cards and a
line of
credit offered in the retail stores.
Bank-type credit
cards; Visa, Master card, Discover or American Express, are issued by
various
banks, credit unions and other financial institutions. Although credit
cards
bear the logo of Visa, master card or one of the other networks, they
are
actually issued by a financial institution or a bank. The leading
U.S. Bank
credit card issuers are Bank of America,
J.P. Morgan Chase, Citigroup, Capital One, Wells Fargo and HSBC.
Private labeled
credit cards (PLCC) are issued by retailers – like Sears, Gap,
Wal-Mart, Target
with their name and logo– but usually managed by financial institutions
like GE
Money, Citibank or their own captive finance company.
Revolving lines of
credit- with or without a plastic card – are issued by retailers like
furniture
stores, home improvement or electronics shops and offered through a
financial
institution like Wells Fargo, GE Money or HSBC. SplashCard
revolving credit program designed
for retailers in above-ground pool and spa industry is a good example.
The
U.S.A
Lending
Market
The U.S.
market
witnessed an astounding growth in terms revolving credit in the last
two
decades. Federal Reserve Statistical releases show that in 1985 the
average
revolving credit outstanding was about $ 115 Billion (20% of the total
consumer
credit).In 2006, these average numbers soared
to
843
Billion (36% of total consumer credit). Survey
of Consumer Finances observed that, of the 75% households with a
revolving
credit line, 58% had a balance outstanding. This growth was noticed by
a lot of
financial institutions that led to their entry into consumer lending
business.
Source – Federal
Reserve
Statistical Releases. Jan 2007.
Within the last
decade many consolidations happened in consumer lending businesses
through
acquisitions, mergers and purchases. Bank One’s acquisition of First
USA in
1997, Chase’s purchase of Providian in 2002, HSBC’s acquisition of
Household in
2003, Citi’s purchase of Sears in 2003, Chase’s purchase of Bank One in
2004,
Bank of America’s acquisition of Fleet Bank and Bank of America’s
merger with
NBNA in 2005 were some of the major deals impacted the market share of
consumer
lending businesses. Bank of America now leads the bunch with 40 million
active
accounts and $143 billion outstanding balances. Chase, Citigroup,
Capital One
and Discover are the other four players in the top five.
Managing
by the Odds.
Over the period of
time, lending to consumers profitably proved to be one of the most
challenging
to the businesses involved. Intense competition for market share and
large
volume of small loans to service are the two major reasons prompted the
lenders
to approach the way they do business differently. Increased automation
in
decision processes and managing the portfolios by the odds (in a
statically
predictable manner) were opted by all the lenders to stay competitive.
Large
scale investments were made on rule based systems, data warehouses and
data
mining. The benefits were tangible;
increased
responses on the expensive mail solicitations, higher approval of
applications,
consistent underwriting processes,
improved fraud detection, data driven portfolio management,
comprehensive reporting and MIS ,
optimization of call
center operations, early delinquency detection and
efficient collection efforts to name a
few.
All these efforts, collectively named as ‘analytics’, hence formed an
inevitable part of the consumer lending business.
Consumer lending is
a volume
based business with millions of small loans and transactions
handled
on a daily basis with thin profit margins. In such a scenario, managers
depend
on the analytics departments to control the risk-returns statistically.
This
requires data warehousing, scorecard development, data segmentation and
pattern
analysis, tracking dashboards and comprehensive reporting systems. SAS
System
is widely used by these businesses in meeting these requirements.
SAS
in
Consumer Lending
Analytics
SAS System is
mainly used for data management, scoring and modeling, statistical
analysis and
reporting by various departments like marketing, risk management,
collections
and operations. Further, all these activities fall into one of the two
life
cycle phases of a lending business; Acquisition and Account Management.
Data Management
Every analytics
activity precedes a data preparation stage in which significant amount
of time and
efforts are spent to consolidate, clean and format data. Consumer
lending
businesses usually have a complex data environment with large data
warehouses
built to store application data, billing information and every day
transactions. Additionally, data from credit bureaus and other data
vendors are
also stored for various analytics purposes. SAS has built in modules
and
functions to handle data from various sources and convert them into a
format
required for the analytics purposes.
Scoring and Modeling
Scorecard is a
statistical model that attributes a number (score) to a customer which
corresponds to a probability that the customer exhibits certain
behavior in the
future. A most widespread type is an application scorecard which
predicts the
probability of a person default on the borrowing. Objective of the
scorecards
can vary depends on the department; A behavioral scorecard predicts the
probability of an existing account turning bad; A response scorecard
predicts
the probability of a person likely to respond to an offer; A collection
scorecard predicts the probability of a customer pays back the owed
money. Development
of scorecard is a detailed statistical procedure typically using
logistics
regression and other procedures in SAS.
Statistical Analysis
A statistical
analysis can be classified as a one-time report or diagnostics with a
specific
objective. For example, identifying the loss drivers in a portfolio or
data
segmentation for a credit line increase or recognizing a fraud pattern
etc. can
be considered as a typical analysis project. Analysis
involves dealing with large
amount of data and drawing
relationship out of them using statistical procedures.
Reporting
An accurate and
robust reporting system is an essential part of any consumer lending
business.
The management relies largely on reporting to get early pointers on
growth as
well as troubles. Regular reports
produced at various frequencies report different metrics
like number of applications,
approvals, average scores and average credit limits ; Performance
metrics like
outstanding amounts , sales, charge-offs
, bankruptcy, fraud ; Collection related metrics like delinquency
stages and
amounts , collection efficiency, roll rates and recoveries ; Vintage
analysis
of performance metrics by acquisition and account management scores ;
Strategy
tracking dashboards in a champion challenger framework ; Scorecard
validation
reports etc are some examples of standard
reports produced in a lending environment.
Now let us look at
the applications of SAS in various life cycles of consumer lending.
Acquisition
This is the initial
phase in lending where the analytics is used to target and acquire the
right
people. One of the main channels of acquisition is through the direct
mail
campaigns and often, the pre-approved (pre screened) credit cards are
mailed to
prospects. Mail campaigns are expensive
operations and so it’s important that the response rates for such
campaigns are
sufficient to balance the cost-benefit sides of the equation.
SAS System is
used
to segment the large address lists and demographic information
available in the
credit bureaus and the segments that are most likely to respond (based
on past
experience) to the campaign are selected for the mail solicitation . In
cases of
through-the-door or internet applications, the business rules developed
using
SAS – also known as data driven strategies- is used to evaluate the
applications, often online, to come out with a decision. Further,
acquisitions
and strategy tracking dashboards are developed using SAS to monitor the
acquisition process and also to compare the performance of various
strategies.
Now let us look at
how various analytics department use SAS System at the acquisition
stage; Risk
team scores the prospects based on the risk rules and does the
pre-screening to
avoid the chances of soliciting bad accounts. Marketing
department profiles the prospects
and identify the likely segments that are going to bring more sales.
Operations
team does the segmentation to maximize the response rates for the mail
campaign. All these teams develop the monitoring dashboards using SAS
to track
their objectives once the plan is rolled out and share their finding as
reports/analysis to the senior management.
We will discuss the
campaign operations and custom score card development process using SAS
further
in this books These two processes are widely used in the lending
environment
for the prospecting and acquisition.
Account Management:
Once the accounts
are acquired, authorization of repeated credit purchases, credit line
management,
fraud detection, sales promotion, cross-selling and collections are
some of the
life-cycle events that occurs in account management phase. Departments
use leverage
on analytics to effectively manage these business situations.
Risk
management
closely monitors the delinquency and utilization patterns along with
charge-offs, bankruptcies and fraud occurrences. Authorization
and credit line policies are modified
based on the learning to reduce loss or improve profitability.
Behavioral score
cards, vintage performance dashboards and reports are developed support
the
decision process.
Marketing
analyzes
activation and sales patterns and prompt the customers to buy more
through
rewards and other offers. Cross-selling of financial products like
personal loans
and mortgages to existing customers is another area marketing analytics
focuses
on.
Collections
analytics team identifies the likely defaulters using behavioral
scorecards and
based on the risk profiles, devise strategies for collections. They use
the
past experiences to improve the collection efficiency and work closely
with the
operations team to implement the data driven strategies.
Operations
analytics
team, typically aligned with customer service operations, forecasts the
call
volumes and analyzes call logs to improve the call routing and support processes. Collection efficiency of the
analysts in terms of number of calls and amount collected are some of
the
metrics monitored by this department.
To
Sum-up, SAS System provides a
variety of
tools and utilities for analysts in consumer lending environment to
perform an
array of analytics activities ranging from simple reporting to complex
statistical
modeling . Number crunching abilities of SAS in a voluminous data
environment
is much appreciated in consumer lending than any other industry.
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