1 Collections, Predictive Analytics and Taxpayer Compliance Management John McCalden McCalden Consulting john@mccalden.biz.

1

Collections, Predictive Analytics and Taxpayer Compliance

Management

John McCalden

McCalden Consulting

john@mccalden.biz

2

Agenda

• Some Collection Theory

• Decision Analytics

• Taxpayer Compliance Management

• Q & A

3

Percent of Cases Aging per Month (SC)

0%

20%

40%

60%

80%

100%

0 12 24 36 48 60

Age in Months

Per

cen

t

97 - 99

Source: South Carolina ARMS

4

Percent of Cases Aging per Month (SC)

y = 1.0489x-0.6291

R2 = 0.9988

0%

20%

40%

60%

80%

100%

0 12 24 36 48 60

Age in Months

Per

cen

t

97 - 99 Power (97 - 99)

5

Collection Rates,Based on Different Levels of Performance

0%

20%

40%

60%

80%

100%

0 12 24 36 48 60

Age in Months

Per

cen

t R

emai

nin

g

Forecast: -0.2 Forecast; -0.5 Forecast: -0.6291

Forecast: -1.0 Forecast: -2.0Forecast: -0.7

6

Effect of Raising the Level of Performance From -0.6291 to -0.7

0%

20%

40%

60%

80%

100%

0 12 24 36 48 60

Age in Months

Per

cen

t R

emai

nin

g

97 - 99 Forecast -0.7

y = 1x-0.7

R2 = 1

y = 1x-0.6291

R2 = 1

7

Average Balance by Age of Case

y = 390.49Ln(x) + 529.3R2 = 0.9334

$0

$500

$1,000

$1,500

$2,000

$2,500

0 12 24 36 48 60

Months

Ave

rag

e B

alan

ce (

$)

Average Per Case Log. (Average Per Case)

Source: South Carolina ARMS: Summary Receivables Report 12/31/2004

y = 390.49Ln(x) + 529.3R2 = 0.9334

8

Application of Aging Curve (-0.6291) and Average Balance Curve to a Hypothetical

Cohort of 10,000 Cases

Month

Aging Cases

Model 1Total $ Model 1

1 10000 $5,763,1003 5010 $4,963,7706 3239 $4,056,10012 2095 $3,171,34018 1623 $2,705,10524 1354 $2,403,70636 1049 $2,022,71248 876 $1,784,20160 761 $1,614,037

9

Percent of # and $ Collected, per Month of Aging

0%

20%

40%

60%

80%

100%

0 12 24 36 48 60

Age in Months

Per

cen

t C

olle

cted

% # Collected 1 % $ Collected 1

10

Comparison of Percent of # and $ Collected, per Month of Aging

0%

20%

40%

60%

80%

100%

0 12 24 36 48 60

Age in Months

Per

cen

t C

olle

cted

% # Collected 1 % $ Collected 1

% # Collected 2 % $ Collected 2

11

Hypothetical Improvement in Collections When Exponent Increases From

-0.6291 to -0.7

Month

Aging Cases

Model 1Total $ Model 1

Aging Cases

Model 2Total $ Model 2

# Difference

$ Difference

# Improvement

$ Improvement

1 10000 $5,763,100 10000 $5,763,100 0 $0 0.00% 0.00%3 5010 $4,963,770 4635 $4,592,230 375 $371,540 3.75% 6.45%6 3239 $4,056,100 2853 $3,572,724 386 $483,376 3.86% 8.39%12 2095 $3,171,340 1756 $2,658,173 339 $513,167 3.39% 8.90%18 1623 $2,705,105 1322 $2,203,419 301 $501,686 3.01% 8.71%24 1354 $2,403,706 1081 $1,919,059 273 $484,647 2.73% 8.41%36 1049 $2,022,712 814 $1,569,578 235 $453,134 2.35% 7.86%48 876 $1,784,201 665 $1,354,445 211 $429,756 2.11% 7.46%60 761 $1,614,037 569 $1,206,816 192 $407,221 1.92% 7.07%

12

How Do We Transition to a Higher Level of Performance?

0%

20%

40%

60%

80%

100%

0 12 24 36 48 60

Age in Months

Per

cen

t R

emai

nin

g

97 - 99 Forecast -0.7

y = 1x-0.7

R2 = 1

y = 1x-0.6291

R2 = 1

13

Use Decision Analytics!!

Use Information Intelligently to Make Business Decisions:

Optimize Collection Activity

Prioritize Audit Candidates

Supply Education to the Needy!

And Repeat

(Taxpayer Compliance Management Program!)

14

How Do We Use Information Intelligently?

• Forecast Performance (models)

• Appropriate Actions (decision strategies/treatment scenarios)

• Controlled Experiments (champion/challenger)

• Performance Reporting

15

Actual and Forecast 'Good' Probabilities for Repeat Filers (SC)

0%

20%

40%

60%

80%

100%

130 180 230 280 330 380 430 480 530

Score Range

'Go

od

' Pro

bab

ilit

y

0

1000

2000

3000

4000

5000

6000

7000

Actual Good Rate Forecast Good Rate N Cases

16

BUSINESS - Collections Decision Strategy (VA)

REASONCODE

BUSINESSCLASSCODE

DISTRICTOFFICE

ASSESSMENTS

BALANCE

RISK BALANCE

BUSINESS(existing)

LIENSOURCE

INDICATOR

FIELDAcceleratedTreatment

FLEA

BALANCE

No Action

High Value,Low Risk

BUSINESS(modified)

BEGIN

241

Other Other

Moderate

High

< $100

Yes

No

> = $100

< $1000

> = $1000

< $100

Lien after 60 days, then

$100-$1000 send to OCAs

$1000 + send to field

86

Low

> = $100

B=24133%

B-FLEA58%

B-NOACT75%

B-LOW63%

B-MOD61%

BUSINESS62%

B-CALL47%

B=FSD$45%

FilingFrequency

Field

X

B = X69%

=Data elements used to segment accounts

= Account groups for strategy implementation

Lien after 30 days, then

$100-$1000 send to OCAs

$1000 + send to field

53,523

576

179

3,914

623

30,242

5,062 2,057

10,288

582

17

Treatment Scenarios

• Allow low-risk cases to self-cure•

‘Accelerate’ high-risk cases to enforced collection actions

• Focus collector resource on medium-risk cases

• All scenarios end with enforced collection actions

18

Low-Risk Treatment Scenarios (SC)

Low Risk, Low Balance

PNOAReminder

LetterAssessment

20% Statement

Levy60 Days 60 Days45

Days

Lien

Low-BalanceHolding

OCA

Balance < $250

180 Days 10 yrs Purged

Day 1 Day 61 Day 121 Day 166 Day 186

Day 186

Day 186

Day 366+

20 Days

(No OpenLicense)

20 DaysOpen license

Balance > $250

20 DaysOpen license

Balance < $250

Balance > $250

Low Risk, High Balance

PNOAReminder

LetterAssessment

20% Statement

Call from Telecollections

Levy60 Days30

Days45

Days10

Days

Lien

Field

OCA180 Days 10 yrs Purged

Day 1 Day 61 Day 121 Day 166 Day 176 Day 196

Day 196

Day 196

Day 376+

20 Days

(No OpenLicense)

20 DaysOpen license

Call from Telecollections

30Days

19

Medium-Risk Treatment Scenarios (SC)

Medium Risk, Low Balance

PNOAReminder

LetterAssessment

20% Statement Levy40 Days 30 Days

30Days

Lien

Low-BalanceHolding

OCA

Balance < $250

180 Days 10 yrs Purged

Day 1 Day 41 Day 71 Day 121 Day 141

Day 141

Day 141

Day 321+

20 Days

(No OpenLicense)

20 DaysOpen license

Balance > $250

20 DaysOpen license

Balance < $250

Balance > $250

Call from Telecollections

Day 101

20Days

Medium Risk, High Balance

PNOACall from

TelecollectionsAssessment

20% Statement

Call from Telecollections Levy40 Days 30 Days

30Days

10Days

Lien

Field

OCA180 Days 10 yrs Purged

Day 1 Day 41 Day 71 Day 121 Day 131 Day 151

Day 151

Day 151

Day 331+

20 Days

(No OpenLicense)

20 DaysOpen license

Call from Telecollections

Day 101

20Days

20

High-Risk Treatment Scenarios (SC)

High Risk, Low Balance

PNOA Assessment20%

StatementLevy30 Days

20 Days

(No OpenLicense)

Lien

Low-BalanceHolding

OCA

Balance < $250

10 yrs Purged

Day 1 Day 31 Day 121Day 51

Day 51

Day 51

Day 231+

70 Days 110 Days

20 DaysOpen license

Balance > $250

20 DaysOpen license

Balance < $250

Balance > $250

High Risk, High Balance

PNOA Assessment20%

StatementLevy30 Days

20 Days

(No OpenLicense)

Lien

Field

OCA 10 yrs Purged

Day 1 Day 31 Day 121Day 51

Day 51

Day 51

Day 231+

70 Days 110 Days

20 DaysOpen license

Call from Telecollections

10Days

21

Treatment Scenarios in MA(Initial Design)

Treatment A

[Med. Risk](High Balance)

NOA Phone Auto-Research

Call & RP (trustee)

NOD FN & Call & RP Deem

Auto-LevyOpen or Assets

Field

FR Auto-Levy OCA

Treatment B

[High Risk](Low Balance)

Bus.

NOA Phone Auto-Research

NOD NIL Auto-LevyOpen or Assets

FR Auto-Levy OCA

Assign LIENFNCallRP

NOA Phone Auto-Research

NOD NIL Auto-LevyWageLevy

Wage Levy LIEN

CaseFR

LIENAuto-Levy OCA

CaseAssigned

Day1

Day30

Day45

Day61

Day90

Day97

Day105

Day111

Yes

No

Yes

No

Yes

No

Treatment C

[High Risk](High Balance)(Low Balance)

Ind.

Treatment D

[High Risk](High Balance)

Bus.

NOA Phone Auto-Research

NOD Open or Assets

FR Auto-Levy OCA

LIENFieldFNCall

Deem RP

Yes

No

CallRP-Propose

Day2

Day14

Treatment E

(Very High Balance)

Ind.

NOA Call

Assign

Treatment F

(Very High Balance)

Bus.

NOA Call

Assign

Low

Med

High

Low

Med

High

22

Champion-Challenger Evaluation

Primary Primary Challenger 1 Challenger 190% Grossed Up 10% Grossed Up

$ Available $450 $500 $50 $500

$ Collected $ 90 $100 $11 $110

Collection % 20% 20% 22% 22%

23

2004 State Tax Revenue

California 85,721 2,388 9 7.2 15 15,127 1

. .

. .

. .

Kentucky 8,463 2,041 21 7.7 9 1,493 23

Louisiana 8,026 1,777 34 6.8 24 1,416 24

Colorado 7,051 1,533 48 4.5 49 1,244 25

Alabama 7,018 1,549 46 5.9 42 1,238 26

South Carolina 6,804 1,621 43 6.3 34 1,201 27

Oklahoma 6,427 1,824 33 6.9 22 1,134 28

Oregon 6,103 1,698 40 6 41 1,077 29

Arkansas 5,581 2,027 23 8.4 8 985 30

Kansas 5,284 1,931 29 6.6 29 932 31

. .

. .

. .

South Dakota 1,063 1,378 49 4.8 47 188 50

U.S. Total 593,489 2,025 6.5 104,733

State

Total Taxes

($ million) Per Capita Rank

% of Pers.

Income RankTax Gap (15%)

($ million)Tax Gap

Rank

Source: FTA Web Site :- U.S. Bureau of the Census and Bureau of Economic Anaylsis.

24

Probability of Making an Assessment – PA Data

0.0

10.0

20.0

30.0

40.0

50.0

60.0

70.0

80.0

90.0

100.0

< 27

0

270

- 274

275

- 279

280

- 284

285

- 289

290

- 294

295

- 299

300

- 304

305

- 309

310

- 314

315

+

Score Range

Pro

bab

ility

ActualForecast

25

Sort Candidates by Cell and Probability (PA)

cum_Obs hours cum_yield myrank...3507 676851 196963641 3507 3508 677044 197019804 3508 3509 677237 197075967 3509 3510 677430 197132130 3510 3511 677623 197188293 3511 3512 677816 197244456 3512 3513 678009 197300619 3513 3514 678202 197356782 3514 3515 678395 197412945 3515...

26

Collection Action Transition Probabilities (Markov-Chain Analysis)

FTF

Notice

Assessment Payment

Plan

Levy Lien Field Visit Revoke Seize Responsible

Party

Cure

New 0.55 0.35 0.00

FTF Notice 0.00 0.70 0.10 0.20

Notice of Assessment 0.20

Assessment 0.20 0.20 0.05 0.25 0.30

Payment Plan 0.05 0.05 0.20 0.70

Levy 0.60

Lien 0.70

Field Visit 0.40

Revoke 0.10

Seize 0.50

Responsible Party 0.80

Fro

m

To

27

Probability of Curing by Age of CE and Type of Collection Action

1 3 6 12 18 24 36 48 60

New 0.10 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00

FTF Notice 0.20 0.10 0.00 0.00 0.00 0.00 0.00 0.00 0.00

Notice of Assessment 0.10 0.10 0.05 0.00 0.00 0.00 0.00 0.00 0.00

Assessment 0.30 0.20 0.10 0.00 0.00 0.00 0.00 0.00 0.00

Payment Plan 0.70 0.80 0.70 0.60 0.50 0.30 0.20 0.10 0.10

Levy 0.60 0.70 0.70 0.60 0.60 0.40 0.40 0.30 0.20

Lien 0.10 0.60 6.00 0.60 0.50 0.40 0.30 0.30 0.30

Field Visit 0.40 0.40 0.50 0.50 0.50 0.30 0.30 0.20 0.20

Revoke 0.10 0.10 0.10 0.10 0.00 0.00 0.00 0.00 0.00

Seize 0.70 0.70 0.70 0.70 0.70 0.70 0.70 0.70 0.70

Responsible Party 0.80 0.80 0.80 0.80 0.80 0.80 0.80 0.80 0.80

Action Age (Months)

28

InboundInformationChannels

Customer/TaxpayerInformation Sources

Tax Processing

External Sources

•Customer Contact History•Billing History•Detailed Return Data•Payment History•Filing History & Methods•Other A/R History•Original Registration Data•Registration Status Updates

•Federal Return Data•RAR, CP2000 Fed Audits•Industry Trend Data•SIC Code Standards•Other States’ Tax Data•Credit Bureau Data•Other State Agency Data

TaxpayerInteractions

•Phone Calls•Letters•Returns

•E-File•Telefile•Internet•Imaged

•Payments•Electronic•Internet•Imaged

•Office Visits•Case ManagementContact Recording•Email•Federal DataSharing Programs•External Interfaces

RESPONSE TREATMENT

TAXPAYER COMPLIANCE MANAGEMENT

Decision Information

OutboundInformationChannels

•Phone Calls•Letters•Office Visits•WEB site•Email•Field Visits•Faxes•Mailings•Other?

Customer ContactDelivery Systems

Integrated Billing &Correspondence

Supporting Systems

Audit Caseload

Collections Caseload

Non-Filer Caseload

Education Caseload

Autodialer & IntelligentCall Management

Case Managementand Workflow

ComplianceStrategy Management

Compliance StrategyDecision Engine

IntegratedPreventative/Curative

Strategies

Decision Delivery

Decisions

Education S

trategy

Registration G

uidance

Com

pliance Initiatives

Collections S

trategy

Non-F

iler Strategy

Audit S

trategy

Challenger S

trategy

ComplianceReferral Generation

Compliance Management Initiatives

Reusable ReferralGeneration Utilities

Referrals

Under-reporters

Compliance initiatives

Non-Filers

Educational needs

Non-payers

ComplianceData Warehouse

Acquisition & Cleansing

Create/Add to Customer Profile

Data Mining

CustomerProfile

Database

Data Aggregation/Performance Summary

ExtractsEvents

PerformanceReporting

BehaviorModeling

PerformanceTables

Populate/Update

Data Access

Compliance ReferralQueue

InboundInformationChannels

Customer/TaxpayerInformation Sources

Tax Processing

External Sources

•Customer Contact History•Billing History•Detailed Return Data•Payment History•Filing History & Methods•Other A/R History•Original Registration Data•Registration Status Updates

•Federal Return Data•RAR, CP2000 Fed Audits•Industry Trend Data•SIC Code Standards•Other States’ Tax Data•Credit Bureau Data•Other State Agency Data

TaxpayerInteractions

•Phone Calls•Letters•Returns

•E-File•Telefile•Internet•Imaged

•Payments•Electronic•Internet•Imaged

•Office Visits•Case ManagementContact Recording•Email•Federal DataSharing Programs•External Interfaces

RESPONSE TREATMENT

TAXPAYER COMPLIANCE MANAGEMENT

Decision Information

OutboundInformationChannels

•Phone Calls•Letters•Office Visits•WEB site•Email•Field Visits•Faxes•Mailings•Other?

Customer ContactDelivery Systems

Integrated Billing &Correspondence

Supporting Systems

Audit Caseload

Collections Caseload

Non-Filer Caseload

Education Caseload

Autodialer & IntelligentCall Management

Case Managementand Workflow

ComplianceStrategy Management

Compliance StrategyDecision Engine

IntegratedPreventative/Curative

Strategies

Decision Delivery

Decisions

Education S

trategy

Registration G

uidance

Com

pliance Initiatives

Collections S

trategy

Non-F

iler Strategy

Audit S

trategy

Challenger S

trategy

Education S

trategy

Registration G

uidance

Com

pliance Initiatives

Collections S

trategy

Non-F

iler Strategy

Audit S

trategy

Challenger S

trategy

ComplianceReferral Generation

Compliance Management Initiatives

Reusable ReferralGeneration Utilities

Referrals

Under-reporters

Compliance initiatives

Non-Filers

Educational needs

Non-payers

ComplianceData Warehouse

Acquisition & Cleansing

Create/Add to Customer Profile

Data Mining

CustomerProfile

Database

Data Aggregation/Performance Summary

ExtractsEvents

PerformanceReporting

BehaviorModeling

PerformanceTables

Populate/UpdatePopulate/Update

Data Access

Compliance ReferralQueue