Tomas Denemark

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www.arbes.com CREDIT SCORING It is better to count than to guess Tomáš Denemark KIEV, September 2012

Transcript of Tomas Denemark

www.arbes.com

CREDIT SCORING It is better to count than to guessTomáš Denemark

KIEV, September 2012

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Content

Credit Scoring as a key element of the Credit Granting Process

Credit Scoring Introduction

Judgmental vs. Statistical Decision

Statistical Scoring Methodology

Credit Scoring Typology

Credit Scoring Data Sources

Credit Scoring Risks

Conclusion

… Credit and behavioural scoring are some of the most important forecasting techniques used in the retail and consumer finance area……. With the connections being made between scoring for default and scoring for targeting potential sales, the scoring techniques will clearly be used to forecast the sales of products as well as the profit a company will make in the future….

Source: A survey of credit and behavioural scoring: forecasting financial risk of lending to consumers - Lyn C. Thomas* - Department of Business Studies, University

of Edinburgh,

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Retail Consumer Credit Lending Process

Application data collection Verification Pre-scoring

calculationInternal decision

Additional documents collection

Public Bureau data collection

Credit Bureau data collectionCredit scoring

Credit Risk strategy decision

Risk premium calculation

Final credit decision

Credit agreement signature

Credit account opening

Disburse money order

Manual tasks

Engine tasks

Combination

Reject

Continue

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Micro Finance Credit Lending Process

Credit product promotion

Interest of potential debtor

Detailed product

description

Application form

Pre-scoring and internal decision

Public & Non-Financial data

collection

Credit Bureau data files Collection

Data entry Credit scoringRisk Premium and collateral

calculation

Credit committee and

loan analysis

Final loan decision

Client approval announcement

Client signature and collateral authorization

Paperwork finalization

Disburse finance funds

Regular follow up

Behavioural credit scoring

On-time collection

Late payments procedure

Credit Bureau score

Soft Collection procedure

Late Collection procedure

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Credit Scoring Introduction

Credit scoring is a statistical-based technology that quantifies credit riskPrimary goal is to rank individuals, distinguishing lower and higher risks

Credit scoring was developed in order to provide quick, accurate, inexpensive and consistent credit evaluation

Credit history or “bureau-based” scores are based exclusively on credit record data from credit reporting agencies

Credit scores are widely used to:evaluate and price credit based on Probability of defaultidentify prospective borrowers for acquisitionmanage existing clients and its accounts

Scoring is heavily used in banking, consumer finance and insurance, and also in employment, utilities and marketing

JUDGMENTAL vs. STATISTICAL

???

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Decision: Statistical vs. Judgmental Scoring

BOTHAssume that the future will resemble the pastCompare applicants to past experienceAim to grant credit only to acceptable risks

STATISTICAL SCORE ADDED VALUE Defines degree of credit risk for each applicantRanks risk in relation to other applicantsAllows decisions based on degree of riskEnables tracking of performance over timePermits known and measurable adjustmentsPermits decision automation

Age

Income

Marital Status

Household

…..

# of Credit Aplications 6M

% of Avg. Credit Lines Usage

……

Total

_____________

Decision

PD

+

-

+

+

…..

-

+

……

+

______

Accept

??

10

5

7

4

…..

28

23

……

135

______

Accept

2,8%

EVALUATED VALUES JUDGMENTAL STATISTICAL

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Comparison of Individual Credit Processes

Average processing time (minutes) Variables required (data fields) Average costs per application (USD) Accuracy (Delinguent cases /1000)

0

50

100

150

200

250

300

350

400

450

500

Performace Figures

Standard Credit Loan Granting Process with Judgmental Decision Credit Loan Granting Process with Financial and Non Financial AnalysisCredit Loan Granting Process with Credit Scoring Based Decision

Source: MFI pool Research

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Statistical Scoring - Methods

LINEAR REGRESSION

LOGARITHMIC REGRESSION

CLASSIFICATION TREES

RECURSIVE PARTITIONING ALGHORITMS

LINEAR PROGRAMMING

NEURAL NETWORKS

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Credit Scoring Typology

Application Score - Application scores are a type of credit score used by banks and finance houses to decide which applicants are to be taken on, based purely on the information given in the credit application form. This scoring is heavily used during the acquisition period of a credit life cycle.

Bureau Score - A Bureau Score is a credit score which is calculated only based on the information from a detailed credit report. Sometimes there is a mixture of private and public credit reports used to obtain the „bureau score“. This scoring is heavily used during acquisition, monitoring and collection periods of a credit life cycle.

Behavioural Score – This is limited to existing client portfolio of a bank or a finance house. This score allows lenders to make better decisions in managing existing clients by forecasting their future performance. This score is heavily used for credit limit renewal, credit limit increase, up-selling, cross-selling and also for the soft collection period of a credit life cycle.

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Credit Scoring Data Sources (Retail)

Credit application

Banking credit history

Banking deposit history

Credit bureau report

Public bureau reportPublic debtor databasesRegister of pledges

Demographics

Billing file

Deal terms

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Concerns over Credit Scoring Influence on the Credit Granting Process

Credit scoring may have adverse effects on certain populations, particularly minorities

Credit scoring is not loss prevention panacea and it is neccessary to keep that in mind during credit lending process definition and design

Some factors used to estimate credit scores may have an adverse effect on certain groups

Automated technologies may disadvantage individuals with nontraditional credit experiences

Judgmental evaluations may be better able to detect errors or inaccuracies

With lending and retailing becoming more automated, risky consumers will face growing disadvantages and this may lead to some acting in the name of social justice

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ConclusionThe Credit Lending Industry is an area, where RISK is the norm rather than the exception

It is necessary to adopt many measures which may help to reduce exposure to high risk

Those who would like to win the market battle have to find a balance between risk and return on assets

Credit scoring is a pragmatic and widely proven method of risk identification and quantification

The statistical credit scoring model is much more powerful than a judgmental opinion and decision

The use of credit scoring during loan providing and monitoring is an essential feature of a modern bank and its implementation costs are quickly recovered

Companies that are confident in their models, will start cherry picking and can target the most profitable customers.

www.arbes.com

Thank you for your attention

Tomáš DenemarkFinancial Systems & Enterprise Applications Director

ARBES Technologies, s.r.o.+420 724 096 [email protected]. Arbes.com