Best Practices in the Collection Process 190 - PwC · approach to collection process ... Use of scoring and segmentation is particularly useful for ... • The transfer of accounts

Methodology and Segmentation: The strategicapproach to collection process

Optimization of the Collection Activities in ConsumerBanking

Agenda

Introduction

Use of segmentation

Behavioral scoring

Use of behavioral scoring in collections

Collection systems

Slide 3PricewaterhouseCoopersFebruary 2009

Solutions for a Growing Collections Problem (1/2)

• With increasing delinquency rates, collections departments either need togrow at a similar rate, OR find ways to operate more efficiently with thesame resources;- The traditional approach of hiring more collections is not feasible.

- One way to increase productivity is automation.• Without automation, more time is spent on deciding what to do, and less time is

available to work on the problem cases and more loans remain unsolved.

- An automated system should help decide what to do, via:• Measuring risk: Behavioral Scores (response to each action)

• Segmenting the customers.

• Prioritizing.

• Providing this information to the appropriate collector at the appropriate time.

• Automating the actions.

Introduction


Solutions for a Growing Collections Problem (2/2)

• Priorities to;

- Increase the collected amount

• 30-60% of delinquent customers pay without any action

- Do you need to spend any resources on those?

• Could you collect more successfully from those who are less likely to pay, ifyou act sooner and more decisively?

- If a customer is on the verge of bankruptcy, you can be there first, beforeother creditors.

- Payment chance is greater before the customer’s financial problems getworse.

- Improve customer satisfaction

• Do not upset your “good” customers through unnecessary collection actions.

Introduction


Addressing Collections Issues Through a Strategic Approach

• Maximizing the use of data to predict behavior and payment ability;

scoring and segmentation.

• Using data intelligence to ‘understand the customer’ allowing

appropriate actions to be set for each individual.

• Combining quantitative information (e.g. scores) with qualitative

information (e.g. collector feedback) to drive the appropriate next action.

• Continuous learning exercises used (champion/challenger testing) to

find a better combination of actions to achieve the desired objectives.

• Monitoring, using a balance of short, medium and long-term key

performance measures to allow quantifiable evaluation.

Introduction


Use of scoring and segmentation is particularly useful forunsecured loans

• A strategy based on scoring and segmentation is best suited when thereare:- High volumes (availability of data, necessity to prioritise actions)- Small-Medium amounts to recover (otherwise no differentiation)- High loss rates, where a change in strategy can really make a

difference- Short recovery time

• Therefore applicability is mainly for retail market unsecured loans suchas:- Credit cards- Personal loans- Consumer loans

Introduction

Agenda

Introduction

Use of segmentation

Behavioral scoring


Collection Systems

Agenda


High Level Segmentation

• Collections strategies deal with this by segmenting accounts into different queues.

Segmenting customer’s accounts is useful means of prioritizing and ‘targeting’

appropriate actions.

• As a general principle, selecting the appropriate action for each segment of

customers can be done by modifying three aspects.

- Type- e.g. call, letter, SMS message

- Tone- e.g. harsh (hard), medium or soft

- Timing- at which point during the cycle

• It is typical for the collections process to be split into two functionally different areas.

These areas are:

- Early Stage delinquents – here the focus will be on rehabilitating the customer

- Late Stage delinquents – the focus will be on recovering the balance or as much of it as

possible. The customer is no longer wanted.

Use of segmentation


Early Stage Delinquency• The level of delinquency referred to here is typically one and two cycles

delinquent.• The objectives are,

- to rehabilitate the customer into a position where they can purchaseagain.• reminding customers of their obligations.• both telephone calls and letters are used.

- maximization of resource effectiveness.• physical resources will be focused first on accounts that will not pay

without a communication from the organization.• Segmentation is again a key to allocation of work and actions taken, being

used to priorities accounts for action. .- The best tool for prioritization is a behavioral score but as seen earlier

proxies can be used.

Use of segmentation


Early Stage Delinquency

Ever paid

Hard Collection

Contact Established

Letter

Days before W orkqueue

NO YES

0-5 6+

M H ML

Months on books

Percent Utilised

Stm t Msg

Risk

Current Balance

Mid Collection

0-100 101+ 0-100 101+

H

MH L MH L MH L MH L

Hard Hard Soft Med Soft Soft Hard Med Soft Hard Med Soft Hard Hard MedHard

Hard HardOvl

Med Med Med Med Hard Hard Med HardOvl

HardOvl

MedOvl

HardOvl

HardOvl

MedOvl

Hard

05 0510 25 25 25 2520 20 20 20- - -- -

NO YES

Ever paid

Hard Collection

Contact Established

Letter

Days before W orkqueue

NO YES

0-5 6+

M H ML

Months on books

Percent Utilised

Stm t Msg

Risk

Current Balance

Mid Collection

0-100 101+ 0-100 101+

H

MH L MH L MH L MH L

Hard Hard Soft Med Soft Soft Hard Med Soft Hard Med Soft Hard Hard MedHard

Hard HardOvl

Med Med Med Med Hard Hard Med HardOvl

HardOvl

MedOvl

HardOvl

HardOvl

MedOvl

Hard

05 0510 25 25 25 2520 20 20 20- - -- -

NO YES

Use of segmentation


Early Stage Delinquency

• Groups of accounts will be put into work queues at different times duringthe month as part of prioritizing collections effort.

• Within each queue however, further sequencing or prioritization will beneeded to sort the accounts into an order list for the collectors.

- A particular circumstance could be a broken promise which requiresimmediate action.

- There can still be further rank ordering within the group, based on scoreor balance.

• In general, with regard to the number of calls which strategy should beapplied will be dependent on customer risk and available resources.

Use of segmentation


Late Stage Delinquency

• Late Stage delinquency is typically defined as three or more cyclesdelinquent.

- The focus now shifts from rehabilitation of the customer to recovery of the debt.

- The allocation of work will be driven by segmentation of the portfolio, so thattreatment can be appropriate whilst maximizing the use of available resources.

• The tools that get used when working in the late stage collections will alteras the emphasis is now on recovery.

- Therefore, actions will be much harsher.

- Blocking of facilities is a recognition that, even if the account returns to ahealthy position, the organization no longer wishes to transact with the

customer.

• Sometimes, it may be appropriate to offer the customer some kind of assistance byrescheduling the debt in some way.

• The transfer of accounts to external agencies is known to have a positiveeffect.

Use of segmentation

Agenda

Introduction

Use of segmentation

Behavioral scoring


Collection Strategies

Agenda


Behavioral scoring is a useful tool for different purposes

• Behavioral scoring helps to predict the future performance of a customerbased on their past payment performance.

• It is a useful tool for different purposes- Deter attrition (churn)- Credit limit adjustments- Improve authorizations- Priorities collections activity

• Behavioral scoring represents an important support system for decisionsregarding the management of the relation (maintenance and closure), themanagement of credit limit for the technical form (e.g. increases ordecreases in agreed overdrafts) and the choice of credit recovery policyadopted (e.g. hard or soft).

Behavioral scoring


A behavioral scoring system allows to estimate the probability ofdefault in a given time frame

• A behavioral scoring model provides an estimation of the probability ofbecoming bad by looking at the behavior of clients during the past(normally from 3 to 12 months) before the observation point.

• It is generally developed on the basis of historical data using multivariateregression.

Behavioral scoring


The performance of the scorecard needs to be assessed

The higher the Gini the stronger thediscrimination of the scorecard

Graphically, it is the area betweenthe two lines on the curve below (A)expressed as a percentage of themaximum possible (B)

A good behavioral scorecard ischaracterized by a Gini of 60-70%

Behavioral scoring

AR=A/ B

Default rates orderedaccording to scorerating bands

The discrimination powercan be measured bythe Gini index

Agenda

Introduction

Use of segmentation

Behavioral scoring


Collection Strategies

Agenda


As the number of days in arrears increases the objectives ofcollection activity change


180+

Recovery rate overexposure at default

Relationship comprised, maximizerecovery

120

90

60

Default in thefollowing 12 months

Keep relationship, get payment ofarrears, pinpoint clients with higher

potential risk of degrading

30

Event to predict(and time horizon)Scoring objective

Days inarrears


Unpaid 1 Collections – Preliminary Segmentation

• First Payment Default:- establishes the nature of the relationship and teaches the customer to

understand that he is expected to pay on time.- can be an early indicator of serious potential problems either with a

customer or with the process (e.g. set-up problems and skips areidentified at this stage).

- Contact must begin as educational dealing with potential CustomerService issues such as:• Has the customer received statement?• Is there a problem with the statement?• Does the customer know the payment options?• Are there any other problems?



Distribution of PopulationBad Loan Ratio According to the Percentile

0,0%

5,0%

10,0%

15,0%

20,0%

25,0%

30,0%

35,0%

40,0%

45,0%

50,0%

5th 10th 15th 20th 25th 30th 35th 40th 45th 50th 55th 60th 65th 70th 75th 80th 85th 90th 95th 100th

Percentile

Ba

dL

oa

n%

Bad Loan Ratio

• Within the lowest score of%5 percentile we have a totalof %38.4 bad rates.

• Within the lowest score of %5percentile we have %14.8 of thetotal bad loans and only %2.6 ofthe good loans.

Low Score

High Score

Percentile% of

Population % Good Loan % Bad LoanBad Loan

Ratio5th 4,5% 2,6% 14,8% 38,4%

10th 4,9% 3,5% 11,6% 33,2%15th 4,8% 4,2% 10,4% 31,6%20th 4,6% 4,8% 9,8% 27,8%25th 5,0% 5,1% 7,4% 22,3%30th 5,1% 4,7% 6,5% 19,6%35th 5,6% 4,9% 5,7% 18,7%40th 5,1% 5,3% 5,4% 14,6%45th 5,4% 5,2% 5,1% 12,5%50th 4,9% 5,4% 4,3% 9,6%55th 4,7% 5,8% 3,8% 9,1%60th 4,3% 4,9% 3,3% 8,4%65th 4,8% 5,5% 2,8% 6,7%70th 5,3% 5,6% 2,6% 5,7%75th 4,6% 5,8% 2,3% 5,0%80th 5,4% 5,2% 1,8% 2,4%85th 5,2% 5,1% 1,2% 2,2%90th 5,3% 5,7% 0,7% 2,1%95th 5,2% 5,1% 0,5% 1,4%100th 5,3% 5,6% 0,0% 0,0%



Segmentation By Risk Level-BARAccounts will be segmented by a combination of Risk Level and Balance. This isknown as the ‘Balance At Risk’ or BAR.

Balance At Risk = Outstanding Balance * Probability Of DefaultPD = 1/(1+(Exp f(Score))

PD



Segmentation By Risk Level using Balance at Risk (BAR)

The following table shows a sample of Unpaid 1 accounts from the developmentsample accounts segmented into three risk groups each representing approximately33% of accounts.The segmentation is based on the BAR calculation. As can be seen the 33% ofaccounts with the highest risk account for 60% of the outstanding balance and 88.6%of the BAR. This segment has an 8.1% risk level – more than 4 times the next worst33% tier of accounts.

% OfAccounts

% OfBalance

BalanceAt Risk

% Of BAR RiskLevel

High Risk 4.414 33.4% 3,858,999 60.3% 311,046 88.6% 8.1%Medium 4,389 33.2% 2,058,856 32.2% 38,098 10.8% 1.9%

Low Risk 4,412 33.4% 477,011 7.5% 2,077 0.6% 0.4%Total 13,215 100% 6,394,866 100% 351,221 100.0% 5.5%

NumberOf

Accounts

TotalStatementBalance



Segmentation By Risk Level-BAR

50 200 500

33.3%140 20.0% 10.0 40,00 100,00160 11.1% 5,60 22,20 55,60180 5.9% 2,90 11,80 29,40200 3.0% 1,50 6,10 15,20

ProbabityOf Default

Account Balance

120 16,7 66,7 166,7

Score

Rank ScoreBalance At

Risk Balance1 120 166,7 5002 140 100 5003 120 66,7 2004 160 55,6 5005 140 40 2006 180 29,4 5007 160 22,2 2008 120 16,7 509 200 15,2 500

10 180 11,8 20011 140 10.0 5012 200 6,1 20013 160 5,6 5014 180 2,9 5015 200 1,5 50

Balance At RiskNo PreviousCollections Previous

Group CollectionLow Soft 1 Soft 2

Soft 2 Medium 1

Medium 1 Medium 2

High Medium 2 Medium 3

• This is quantifying the balance of an account likelyto go bad or in other words, if there were 10accounts with a balance of 100 each and aprobability of default of 50%, then the expectationis that 500 €will go to loss, or on average a 50€Balance at Risk for each account.

• For three different account balances the followingis the Balance At Risk at different scores.

• The portfolio is segmented by whether theaccount was previously in collections or not. Thebusiness has devised five collection strategies forthis level of delinquency.



Formulation of Strategies

• The elements of collection strategies are:

- Method of Contact

- Timing Of Contact

- Content of Message

- Frequency of Contact

- Testing and Measurement

• It is necessary to build up the required strategies for each process phase.

- e.g the templates for the letters, scripts for telephone contacts to ensurethat the correct message is given to customers.

• Formulation of methods, timing and frequency are based on the costs, risksand reward associated with each action.

• Each action needs to be documented fully to ensure compliance.



Formulation of Strategies• The table shows the timing of

payments received from the threedifferent risk groups in number of daysfrom the Unpaid Date.

• The unknown factor in this is the leveland type of collection activity thatoccurred in each of the risk groups.- What can be seen is that the lower

risk segments pay at a quicker ratethan higher risk groups. Forinstance 31.1% of the lowest riskgroup had paid within 3 days of theUnpaid Date, compared to only17.0% of High Risk accounts.

• Given the difference in both theoutstanding balance and BAR of thesegroups this gives the opportunity todelay contact (e.g. automatic reminderletters and SMS) on low risk clients inorder to save unnecessary expense.

Days To Receiptof Payment

High Risk Medium Risk Low Risk1 8.3% 8.6% 13.2%2 10.2% 13.5% 20.0%3 15.3% 19.7% 26.6%4 17.0% 24.3% 31.1%5 19.3% 26.0% 34..2%6 22.4% 27.6% 38.9%7 25.3% 32.1% 40.2%8 28.7% 36.5% 41.1%9 29.0% 38.6% 44.3%

10 32.0% 40.4% 45.3%11 35.2% 42.0% 46.9%12 36.2% 41.3% 47.5%13 37.1% 45.2% 48.7%14 39.5% 46.7% 51.0%15 40.4% 49.8% 52.3%16 42.9% 51.6% 53.5%17 45.2% 52.0% 54.8%18 47.2% 55.1% 56.0%19 51.1% 54.7% 57.4%20 52.9% 57.6% 58.3%21 53.6% 58.9% 61.2%

22-30 Days 64.8% 66.1% 74.2%31-61 Days 91.2% 89.7% 98.1%

No Payment 7.3% 2.8% 2.7%

Percentage of Unpaid 1 Population Paying



Level of sophistication

Risk Rating Tools - Around the world

Customer levelProfitability

Beh

avio

ur S eg ment

Customer levelProfitability

Beh

avio

ur S eg ment

Usescorecardsas standard

KnowledgeBased

Decisions

Profitabilitybased

decisioningMulti-product

customer leveldecisions


Agenda

Introduction

Use of segmentation

Behavioral scoring


Collection systems

Agenda


Issues addressed by collection systems

Addressing the right customers, at the right time, with the right message

• Selecting the optimal collection strategy for a customer at each point intime

• Analytical capabilities – segmentation of delinquent accounts and/orbehavioural scoring (self-correct, won’t pay and etc.)

• End-to-end automate the processes – no need to rely on the humandecisions

• Collection operator screens populated with the required data

• Assessment and planning of collection workforce

• Automated generation of the reminder letters, messages and letters to lawenforcement agencies

• Variety of client interaction channels – integration with call centers, SMS-gateways, e-mail

Collection Management systems


Collection applications overview

ReminderMedium

CollectionHard

CollectionLegal

CollectionSoft

CollectionWrite off of

credits

Analytics (Client segmentation for collection, measure collectors’ performance)

Scoringsystem

Cardsystem

Analytic CRM Collateralmanagement External

agencies

• credit bureaus• collection agencies• law enforcementauthorities• etc

Corebanking

Collection applications

Interactionchannels:- emails- call centres- sms

Bank’s operational systems Externalparties



“Elements” of Collection system – IT perspective

CRM

Workflow

Analytics

Collectionsystem

Collection system = CRM + Workflow + Analytics



Acquire vs. develop in-house

Acquiring

Access to methodologies of thevendor (if available)

Specialist expertise and accessto the best practices

Tried and tested systems

Typically costly solution

Faster implementation (~ 3-5months)

In-house

Could be lower cost

Need strong methodologicalsupport in order to develop a

mature solution

May very long to develop amature solution (> 1 year)

Control/tailoring of solution



Points to consider when selecting collection application

• Functional and analytical capabilities

• Availability of the methodology expertise with the vendor?

• Obligation by the vendor to provide timely access to expert consultancyduring implementation (typically experts are scarce resources)

• Technical architecture (e.g. does the application come with its own datastore? Data import can take days)

• May need a separate data warehouse for Collection due to excessiveamount of analytical calculations and data queries

• On-line integration with the bank's core applications

• Call Center integration and client interaction channels

• Flexibility to customization by the bank

• Localization



How PwC can help - Collection Systems

• Designing “TO-BE” Collection environment- Analytical models and strategies- Processes- Functional and technical requirements

• Selection of the collection application• Managing the system implementation – Project

Management, Quality Assuranceor• Managing in-house development initiative


© 2009 PricewaterhouseCoopers. All rights reserved. “PricewaterhouseCoopers” refers to the networkof member firms of PricewaterhouseCoopers International Limited, each of which is a separate and independentlegal entity. *connectedthinking is a trademark of PricewaterhouseCoopers LLP (US).

Contacts

Sergey Bazoev, PartnerAlexey Yankovsky, Senior ManagerH. Kaan Aksel, Senior Manager8044 490 6777

Documents

Best Practices in the Collection Process 190 - PwC · approach to collection process ... Use of scoring and segmentation is particularly useful for ... • The transfer of accounts