Cut Off Strategies Presentation

8/7/2019 Cut Off Strategies Presentation

1/29

CUTOFF & STRATEGIESPRESENTER: IOANNA ROUSSOU

Bucharest, 20/10/2010

Main Topics

Cut Off Table

Cut Off Objectives

Profitability

Profitability Considerations

Practical Implications


2/29

Main Topics

Cut Off Table

Cut Off Objectives

Profitability



What is the result of a Score Development?

A Score DistributionA Cut-Off Table

Initial Step

Score

Total TTD -

Applications

Booked

Expected

Goods

Expected

Bads

Interval

Bad Rate

G:B

Odds TTD Above

Approval

Rate

Bads

Above

Portfolio

Bad Rate

169 1,161 1,062 99 8.5% 10.8 52,536 67.5% 2,356 4.5%

170 1,180 1,083 97 8.2% 11.2 51,375 66.0% 2,257 4.4%

171 1,198 1,103 95 7.9% 11.6 50,195 64.5% 2,160 4.3%

172 1,214 1,120 94 7.7% 12.0 48,997 62.9% 2,065 4.2%

173 1,228 1,136 92 7.5% 12.4 47,783 61.3% 1,971 4.1%

174 1,241 1,151 90 7.3% 12.8 46,555 59.7% 1,879 4.0%

175 1,251 1,163 88 7.0% 13.2 45,314 58.1% 1,789 3.9%

176 1,259 1,173 86 6.8% 13.7 44,063 56.5% 1,701 3.9%

177 1,266 1,183 83 6.6% 14.2 42,804 54.9% 1,615 3.8%

178 1,270 1,189 81 6.4% 14.7 41,538 53.3% 1,532 3.7%

179 1,272 1,194 78 6.1% 15.2 40,268 51.6% 1,451 3.6%

180 1,272 1,197 75 5.9% 16.0 38,996 50.0% 1,373 3.5%

Expected Bads at

this score

Estimated Bad

Rate at this score

Estimated Good Bad Odds

at this scoreNumber of

Goods for each BadExpected TTD

Applications at

this score

Number of

Applications

expected at this

score and above

Percent of

Applications

expected at this

score and above

Number of Bads

expected at this

score and above

Cumulative Bad

Rate at this

score and above


3/29

Key Points

Interval Bad Rate

It is the bad rate at that specific score-only if you accept all applications at

score 175

Portfolio Bad Rate

It is the bad rate of the whole portfolio-if you accept all applications from

score 175 and above

Interval vs Marginal Bad Rate

Cumulative vs Portfolio Bad Rate

Score

Total TTD -

Applications

Booked

Expected

Goods

Expected

Bads

Interval

Bad Rate

G:B

OddsTTD Above

Approval

Rate

Bads

Above

Portfolio

Bad Rate

173 1,228 1,136 92 7.5% 12.4 47,783 61.3% 1,971 4.1%

174 1,241 1,151 90 7.3% 12.8 46,555 59.7% 1,879 4.0%

175 1,251 1,163 88 7.0% 13.2 45,314 58.1% 1,789 3.9%

176 1,259 1,173 86 6.8% 13.7 44,063 56.5% 1,701 3.9%

177 1,266 1,183 83 6.6% 14.2 42,804 54.9% 1,615 3.8%

ScoreTTD

Applications

Loss From

Bads

Revenue

From Goods

169 1,161 128,130 107,474

170 1,180 125,541 109,600

171 1,198 122,953 111,624

172 1,214 121,659 113,344

173 1,228 119,070 114,963174 1,241 116,482 116,481

Cut Off table types

Various versions in the industry:Score groups in ranges At Amount Level

Observed Bad Rate vs. Predicted

Score BandIncoming

Applications

Bad Rate per

Band

170 - 179 10% 15%

180 - 189 10% 7%

190 - 199 10% 4%

200 209 10% 3%

Score TTD Applications

Interval Bad

Rate

(Predicted)

Interval Bad

Rate

(Observed)

169 1,161 8.50% 10.20%

170 1,180 8.20% 9.02%

171 1,198 7.90% 7.11%

172 1,214 7.70% 6.93%

173 1,228 7.50% 8.25%

174 1,241 7.30% 8.76%


4/29

Key Question

Bad Definition

60+ with 18 average outcome period or

90+ with 24 average outcome period

What is my Loss Rate?

X Bads Y Losses

Is it included in the table?

Relationship between Bad and Loss definition

6% Bad Rate = 2% Loss Rate

Cut-Off Objectives


5/29

Main Topics

Cut Off Table

Cut Off Objectives

Profitability



Objectives

Book Better Customers

What is a better customer?

Reduce Losses

Are less credit losses always good for the business?

Increase Market Share

Increase the approval ratewhat is optimal?

Maximise Number of Automated Decisions

Where is manual verification and assessment worthwhile?

Increase Profits

How do I measure profitability?


6/29

Objectives

What is your aim in setting a Cut-Off?

Cut-Off Table

Score

Total TTD -

Applications

Booked

Expected

Goods

Expected

Bads

Interval

Bad Rate G:B Odds TTD Above

Approval

Rate

Bads

Above

Portfolio

Bad Rate

169 1,161 1,062 99 8.5% 10.8 52,536 67.5% 2,356 4.5%

170 1,180 1,083 97 8.2% 11.2 51,375 66.0% 2,257 4.4%

171 1,198 1,103 95 7.9% 11.6 50,195 64.5% 2,160 4.3%

172 1,214 1,120 94 7.7% 12.0 48,997 62.9% 2,065 4.2%

173 1,228 1,136 92 7.5% 12.4 47,783 61.3% 1,971 4.1%

174 1,241 1,151 90 7.3% 12.8 46,555 59.7% 1,879 4.0%

175 1,251 1,163 88 7.0% 13.2 45,314 58.1% 1,789 3.9%

176 1,259 1,173 86 6.8% 13.7 44,063 56.5% 1,701 3.9%

177 1,266 1,183 83 6.6% 14.2 42,804 54.9% 1,615 3.8%178 1,270 1,189 81 6.4% 14.7 41,538 53.3% 1,532 3.7%

179 1,272 1,194 78 6.1% 15.2 40,268 51.6% 1,451 3.6%

180 1,272 1,197 75 5.9% 16.0 38,996 50.0% 1,373 3.5%

0.0%

10.0%

20.0%

30.0%

40.0%

50.0%

60.0%

70.0%

80.0%

90.0%

100.0%

0.5% 0.7% 0.8% 1.1% 1.5% 2.0% 2.6% 3.4% 4.2% 5.1% 6.0% 6.7% 7.3% 7.6% 7.8%

Approv

alRate

Portfolio Bad Rate

Strategy Curve

Strategy CurveCurrent Situation

Current:

Approval Rate: 56%

Bad Rate: 5.2%


7/29

0.0%

10.0%

20.0%

30.0%

40.0%

50.0%

60.0%

70.0%

80.0%

90.0%

100.0%

0.5% 0.7% 0.8% 1.1% 1.5% 2.0% 2.6% 3.4% 4.2% 5.1% 6.0% 6.7% 7.3% 7.6% 7.8%

ApprovalRate

Portfolio Bad Rate

Strategy Curve

Strategy CurveCurrent Situation

Strategy Curve

New Score

Current:

Approval Rate: 56%

Bad Rate: 5.2%

Setting Cut-Off-Application Scores

Can set Cut-Off based on a single criteria - a target

Approval Rate

OR

Portfolio Bad Rate

A solution which is a compromise between the two

I want to keep the Approval Rate above 55%

But I dont want the Portfolio Bad Rate to be more than 5%

Use Cut-Off Tables

Simple

Measurable


8/29

0.0%

10.0%

20.0%

30.0%

40.0%

50.0%

60.0%

70.0%

80.0%

90.0%

100.0%

0.5% 0.7% 0.8% 1.1% 1.5% 2.0% 2.6% 3.4% 4.2% 5.1% 6.0% 6.7% 7.3% 7.6% 7.8%

ApprovalRate

Portfolio Bad Rate

Strategy Curve

Strategy CurveMaintain Bad Rate

Current:

Approval Rate: 56%

Bad Rate: 5.2%

0.0%

10.0%

20.0%

30.0%

40.0%

50.0%

60.0%

70.0%

80.0%

90.0%

100.0%

0.5% 0.7% 0.8% 1.1% 1.5% 2.0% 2.6% 3.4% 4.2% 5.1% 6.0% 6.7% 7.3% 7.6% 7.8%

Approv

alRate

Portfolio Bad Rate

Strategy Curve

New:

Approval Rate: 78.2%

Bad Rate: 5.2%

Strategy CurveMaintain Bad Rate

Current:

Approval Rate: 56%

Bad Rate: 5.2%


9/29

ObjectivesMaintain Bad Rate


Cut-Off Table

Score

Total TTD -

Applications

Booked

Expected

Bads

Expected

Goods

Interval


Approval

Rate

Bads

Above

Portfolio

Bad Rate

155 773 101 672 13.1% 6.7 66,057 84.7% 3,786 5.7%

156 804 102 702 12.6% 6.9 65,284 83.7% 3,685 5.6%

157 835 101 735 12.0% 7.3 64,480 82.7% 3,583 5.6%

158 866 102 764 11.8% 7.5 63,645 81.6% 3,483 5.5%

159 897 103 794 11.5% 7.7 62,779 80.5% 3,381 5.4%

160 927 103 824 11.1% 8.0 61,882 79.3% 3,277 5.3%

161 957 104 853 10.9% 8.2 60,954 78.2% 3,174 5.2%

162 986 104 883 10.5% 8.5 59,997 76.9% 3,070 5.1%

163 1,015 104 911 10.2% 8.8 59,010 75.7% 2,966 5.0%

164 1,042 103 939 9.9% 9.1 57,996 74.4% 2,863 4.9%

165 1,068 103 966 9.6% 9.4 56,954 73.0% 2,759 4.8%

166 1,093 102 992 9.3% 9.7 55,886 71.7% 2,657 4.8%

0.0%

10.0%

20.0%

30.0%

40.0%

50.0%

60.0%

70.0%

80.0%

90.0%

100.0%

0.5% 0.7% 0.8% 1.1% 1.5% 2.0% 2.6% 3.4% 4.2% 5.1% 6.0% 6.7% 7.3% 7.6% 7.8%

Approv

alRate

Portfolio Bad Rate

Strategy Curve

Strategy CurveMaintain Approval Rate

Current:

Approval Rate: 56%

Bad Rate: 5.2%


10/291

0.0%

10.0%

20.0%

30.0%

40.0%

50.0%

60.0%

70.0%

80.0%

90.0%

100.0%

0.5% 0.7% 0.8% 1.1% 1.5% 2.0% 2.6% 3.4% 4.2% 5.1% 6.0% 6.7% 7.3% 7.6% 7.8%

ApprovalRate

Portfolio Bad Rate

Strategy Curve

New:

Approval Rate: 56%

Bad Rate: 3.9%


Current:

Approval Rate: 56%

Bad Rate: 5.2%

Objectives - Maintain Approval Rate


Cut-Off Table

Score

Total TTD -

Applications

Booked

Expected

Bads

Expected

Goods

Interval


Approval

Rate

Bads

Above

Portfolio

Bad Rate

170 1,180 97 1,083 8.2% 11.2 51,375 65.9% 2,256 4.4%

171 1,198 95 1,103 8.0% 11.6 50,194 64.4% 2,159 4.3%

172 1,214 94 1,120 7.7% 12.0 48,996 62.8% 2,064 4.2%

173 1,228 92 1,137 7.5% 12.4 47,782 61.3% 1,970 4.1%

174 1,241 90 1,151 7.2% 12.8 46,554 59.7% 1,879 4.0%

175 1,251 88 1,163 7.0% 13.2 45,314 58.1% 1,789 3.9%

176 1,259 86 1,174 6.8% 13.7 44,063 56.5% 1,701 3.9%

177 1,266 83 1,182 6.6% 14.2 42,803 54.9% 1,615 3.8%

178 1,270 81 1,189 6.4% 14.7 41,538 53.3% 1,532 3.7%

179 1,272 78 1,194 6.2% 15.2 40,268 51.6% 1,451 3.6%

180 1,272 75 1,197 5.9% 16.0 38,996 50.0% 1,373 3.5%

181 1,270 73 1,196 5.8% 16.3 37,724 48.4% 1,298 3.4%


11/29

0.0%

10.0%

20.0%

30.0%

40.0%

50.0%

60.0%

70.0%

80.0%

90.0%

100.0%

0.5% 0.7% 0.8% 1.1% 1.5% 2.0% 2.6% 3.4% 4.2% 5.1% 6.0% 6.7% 7.3% 7.6% 7.8%

ApprovalRate

Portfolio Bad Rate

Strategy Curve

New:

Approval Rate: 56%

Bad Rate: 3.9%

New:

Approval Rate: 78.2%

Bad Rate: 5.2%


Current:

Approval Rate: 56%

Bad Rate: 5.2%

Setting the Cut-Off

As a result of the new scorecard we have many options, amongst them are

But which is the best option?

Booking 22% more of the incoming applications but having the same bad rate

Reducing the bad rate by 1.3 percentage points but still booking 56% of applications

Or Is it something else?

Strategy Criteria Approval Rate Bad Rate

Current 56.0% 5.2%

Strategy 1 Same Approval Rate 56.0% 3.9%

Strategy 2 Same Bad Rate 78.2% 5.2%


12/291

Profitability

This brings us back to the first question

What is the target for the cut-off and the overall aim of business?

In most cases the business target is to maximise profitability

By balancing Risk and Reward the goal is:

Reward (revenue) and Risk (losses) BREAK EVEN POINT

Maximum Profit

Setting Cut-Off-Application Scores

Setting the Cut-Off based on maintaining approval or portfolio bad rate is

straightforward but difficult to optimise:

Still reject profitable business

or

Accept unprofitable business

The answer is to correctly balance Risk and Reward!But what does this mean?

Optimise profitability by use of:

Profitability Analysis

Modeling


13/291

Profitability

Main Topics

Cut Off Table

Cut Off Objectives

Profitability




14/291

Profitability

The principles are straightforward:

In correctly developed scores we have two categories of accounts:

Goods

Bads

Each individual score has an associated probability that an applicant, if

booked, will become Bad

Therefore if we know

The Reward from a Good

AND The Risk from a Bad

We can use this information to decide on the cut-off

Setting The Cut-OffProfitability

Steps:

Use Bad Definition to create Profit & Loss Accounts for the two sub-

portfolios

Portfolio of Good Accounts

Portfolio of Bad Accounts

Find the Profit and Loss for each at the account level

Use resulting Good/Bad ratio to set score cut-off


15/291

Setting The Cut-OffProfitability

Required Information

Either:

All variables in Profit & Loss accounts calculated on an account by account

basis

Or:

Portfolio Information for all variables

and

Flow Rates and Delinquent Balances

Profit & Loss StatementGood Bad

Gross Interest Revenue 27,205,678 490,000

Cost of Funds 7,773,051 140,000

Net Interest Revenue 19,432,627 350,000

Fees 2,880,000 90,000

Interchange Income 4,760,000 190,000

Total Card Income 27,072,627 630,000

Marketing Costs 4,800,000 200,000

Acquisition Cost 2,400,000 100,000

Operating Expense

Premises 1,350,000 18,000Telecomms 220,000 12,000

Systems etc 420,000 10,000

Customer Service Costs 5,538,000 95,345

Credit Collection Expense 300,500 276,000

Total Expense 15,028,500 711,345

Credit Losses 4,990,370

Fraud Losses 2,332,800 97,200

Total Profits before Tax 9,711,327 -5,168,915


16/291



Cost of Funds 7,773,051 140,000


Fees 2,880,000 90,000





Operating Expense

Premises 1,350,000 18,000

Telecomms 220,000 12,000

Systems etc 420,000 10,000



Total Expense 15,028,500 711,345


Fraud Losses 2,332,800 97,200


Accountsdesignated asGood in Scoredevelopment



Cost of Funds 7,773,051 140,000


Fees 2,880,000 90,000





Operating Expense

Premises 1,350,000 18,000Telecomms 220,000 12,000

Systems etc 420,000 10,000



Total Expense 15,028,500 711,345


Fraud Losses 2,332,800 97,200


Accounts

designated as

Bad in Score

development


17/291

Profit & Loss Statement Account LevelGood Bad

Gross Interest Revenue 283.4 122.5

Cost of Funds 81.0 35.0

Net Interest Revenue 202.4 87.5

Fees 30.0 22.5

Interchange Income 49.6 47.5

Total Card Income 282.0 157.5

Marketing Costs 50.0 50.0

Acquisition Cost 25.0 25.0

Operating Expense

Premises 14.1 4.5

Telecomms 2.3 3.0

Systems etc 4.4 2.5

Customer Service Costs 57.7 23.8

Credit Collection Expense 3.1 69.0

Total Expense 156.5 177.8

Credit Losses 0.0 1247.6

Fraud Losses 24.3 24.3

Total Profits before Tax 101.2 -1,292.20

Cut-Off Set at Score Yielding

12.8 Goods:Bad Odds

1,292.2/101.2 = 12.8

At the score equivalent to Good:Bad Odds of 12.8:1 it is breakeven

At Odds below 12.8:1 bookings are unprofitable

Above Odds of 12.8:1 bookings are profitable

At Score Range Level

Score

Estimated Revenue

From

Goods

Loss From

Bads

Net Profit

At ScoreTotal TTD Goods Bads Bad Rate G:B Odds

169 1,161 1,062 99 8.5% 10.8 107,474 128,130 -20,655

170 1,180 1,083 97 8.2% 11.2 109,600 125,541 -15,942

171 1,198 1,103 95 7.9% 11.6 111,624 122,953 -11,329

172 1,214 1,120 94 7.7% 12 113,344 121,659 -8,315

173 1,228 1,136 92 7.5% 12.4 114,963 119,070 -4,107

174 1,241 1,151 90 7.3% 12.8 116,481 116,482 0

175 1,251 1,163 88 7.0% 13.2 117,696 113,893 3,802

176 1,259 1,173 86 6.8% 13.7 118,708 111,305 7,403

177 1,266 1,183 83 6.6% 14.2 119,720 107,422 12,298

178 1,270 1,189 81 6.4% 14.7 120,327 104,833 15,493

179 1,272 1,194 78 6.1% 15.2 120,833 100,951 19,882

180 1,272 1,197 75 5.9% 16 121,136 97,068 24,068


18/291

Approving only above Good:Bad Odds of 12.8:1 yields the Maximum Total Profit

At Odds below 12.8:1 the portfolio is less profitable

Above Odds of 12.8:1 the portfolio is less profitable

At Portfolio Level

Score T TD AboveApproval

Rate

Goods

Above

Bads

Above

Portfolio

Bad Rate

Revenue

From

Goods

Loss From

BadsTotal Profit

169 52,536 67.5% 50,180 2,356 4.5% 5,078,216 3,049,229 2,028,987

170 51,375 66.0% 49,118 2,257 4.4% 4,970,742 2,921,100 2,049,642

171 50,195 64.5% 48,035 2,160 4.3% 4,861,142 2,795,558 2,065,584

172 48,997 62.9% 46,932 2,065 4.2% 4,749,518 2,672,606 2,076,913

173 47,783 61.3% 45,812 1,971 4.1% 4,636,174 2,550,947 2,085,227

174 46,555 59.7% 44,676 1,879 4.0% 4,521,212 2,431,877 2,089,335

175 45,314 58.1% 43,525 1,789 3.9% 4,404,730 2,315,396 2,089,334

176 44,063 56.5% 42,362 1,701 3.9% 4,287,034 2,201,502 2,085,532177 42,804 54.9% 41,189 1,615 3.8% 4,168,327 2,090,198 2,078,129

178 41,538 53.3% 40,006 1,532 3.7% 4,048,607 1,982,776 2,065,832

179 40,268 51.6% 38,817 1,451 3.6% 3,928,280 1,877,942 2,050,338

180 38,996 50.0% 37,623 1,373 3.5% 3,807,448 1,776,992 2,030,456

-1000000

-500000

0

500000

1000000

1500000

2000000

2500000

107 117 127 137 147 157 167 177 187 197 207 217 227 237 247

Total

Profit

Score

Portfolio Profit

Score 174

At Portfolio Level

So is it possible to set the best cut-off without considering profitability?


19/291

Cut-Off Table

Score TTD AboveApproval

RateG:B Odds Bads Above

Portfolio

Bad RateTotal Profit

161 60,954 78.2% 8.2 3,174 5.2% 1,739,263

174 46,554 59.7% 12.8 1,879 4.0% 2,089,335

176 44,063 56.5% 13.7 1,701 3.9% 2,085,532

Scenarios

Market ShareIncrease

Reduce Losses



20/292

Main Topics

Cut Off Table

Cut Off Objectives

Profitability



ProfitabilityIs it Easy?

Risk is easy...

0.0%

5.0%

10.0%

15.0%

20.0%

25.0%

Up to 139 140 - 149 150 - 159 160 - 169 170 - 179 180 - 189 183 - 189 190 - 199 200 - 209 210+Application Score

Ever 90+ Bad Rate


21/292


Product TypeBank PoliciesApproval Rate

Delinquency LevelCollections

Frauds MarketingTerms &

Conditions

Existing

Customers

Cross SellNew

ClientsLimits

UsageAttrition

Account Maintenance


Profitability is not - reality!

735

689

531491

530

427 389366

342309

0

100

200

300

400

500

600

700

800

Up to 139 140 - 149 150 - 159 160 - 169 170 - 179 180 - 189 183 - 189 190 - 199 200 - 209 210+

Application Score

Average Total Revenue by Application ScoreCredit Cards


22/292



0.0%

10.0%

20.0%

30.0%

40.0%

50.0%

60.0%

70.0%

80.0%

90.0%

100.0%

0

100

200

300

400

500

600

700

800

900

1000

Up to 139 140 - 149 150 - 159 160 - 169 170 - 179 180 - 189 183 - 189 190 - 199 200 - 209 210+

%

Inactive

AverageBalance

Score

Inactivity Rate and Average BalanceCredit Cards

Average Balance% Inactive



7,164

3,340

1,632

830

0

2,000

4,000

6,000

8,000

10,000

12,000

96 48 24 12Tenor

Instalment Interest Income By TenorLoans Portfolio

Gross Interest Income

Net Interest Income

CoF


23/292

Key Questions

Over What Period do you consider Costs and Revenues?

For Tenor Loans, actual Loan Durations are easy to calculate

For Revolving Loans how long should be considered?

Profitability over 3 or 5 years will be very different to 20 years!!

Many Credit Cards will have active life of 20+ years

Key Questions

What is the Real Value of a Customer?

Should we consider Renewals?

How should we consider the propensity of a customer to desire further

products in the future?

Handling of these questions greatly affects the cut-off decision Profitabilityrenewals, multiple products and greater time period

Type of Applicants we want to approve

Young applicants have greatest potential for growth


24/292

Cut-Off Strategy

Main Topics

Cut Off Table

Cut Off Objectives

Profitability




25/292

Single Score Cut-Off Strategy

0.0%

0.2%

0.4%

0.6%

0.8%

1.0%

1.2%

1.4%

1.6%

1.8%

107 117 127 137 147 157 167 177 187 197 207 217 227 237 247

PercentofPopulation

Application Score

Score Distribution

AcceptReject

Multiple Score Cut-Off Strategy

0.0%

0.2%

0.4%

0.6%

0.8%

1.0%

1.2%

1.4%

1.6%

1.8%

107 117 127 137 147 157 167 177 187 197 207 217 227 237 247

PercentofPopulation

Application Score

Score Distribution

Reject AcceptGrey Area


26/292


In the Grey Area customers are referred for additional underwriting

It generally shows a Lack of Confidence in Score

It can make Sceptics more comfortable

Can be useful as a temporary measure when the applicant distribution or

performance is not known for instance:

Generic scorecard

- New Products

- New Sources


Considerations to be taken into account with this strategy are:

What additional criteria are being considered?

Are they already in the scorecard?

Is it judgmental or can these be converted in to rules?

Can underwriters make a better decision than the score?

Can it be appropriately tracked and monitored?

Are there comprehensive reject and approval codes?


27/292

0.0%

5.0%

10.0%

15.0%

20.0%

25.0%

Up to 139 140 - 149 150 - 159 160 - 169 170 - 179 180 - 189 183 - 189 190 - 199 200 - 209 210+

BadR

ate

Score Ranges

Probability of Default

Cut Off

Implications

0.0%

5.0%

10.0%

15.0%

20.0%

25.0%

Up to 139 140 - 149 150 - 159 160 - 169 170 - 179 180 - 189 183 - 189 190 - 199 200 - 209 210+

BadR

ate

Score Ranges

Probability of Default

Cut Off

Implications

Low Sides PerformanceGrey Area objectives


28/292

Implications

Significant Profitability Implications:

Your cut-off strategy effects your populations of customers

Depending on the score type

Attrition

Risk

Usage, etc.

The score cut-off will impact

Balances

Delinquency Risk

Ultimately, each score cut-off will impact your Profitability!!

Additional Aspects

1. Complicated Structures of 2 or 3+ Scores

2. Risk Based Pricing

3. Limits

4. Macro Environment

5. Basel II RequirementsPDE, LGD, EAD


29/29

Thank you!!

Cut Off Strategies Presentation

Documents

Transcript of Cut Off Strategies Presentation