1. Internal Build vs. Buy Services? Calculating the Economic Decisions of Outsourcing Maris Rolmanis CGI - Global Business Engineering maris.rolmanis@cgi.com April, 2006

2. 2 Agenda  Process Considerations  Information is Key  Segmentation  Outsourcing – Maximizing the Value  Why: Motivations  What: Candidates for Outsourcing  How: Economic Framework

3. 3 The Dream…….  Turning revenue into profit  Reality is….. Not all customers pay on time or are even willing to pay Sounds simple: ensure the customers pay for the services and products used on time complete without additional effort/stress Saturation Revenue Profit

4. 4 Today’s Focus - Revenue into Profit Product Development Usage Management Collections Acquisition/ Provision Loss Recognition Marketing Recoveries Integrated Risk Management Managing credit risk allows companies to maximize their customer profitability Propensity Scoring Churn Management Retention Winback Cross-sell/Up-sell Customer Segmentation Customer Valuation Pricing Strategies Prescreen Credit Scoring Product Selection Approvals/Declines Risk-based Pricing Offer Analysis Workflow Routing Up-sell/Cross-sell Portfolio Scoring Care Differentiation Fee Waivers Product Upgrades Pay/No Pay Authorizations Up-sell/Cross-Sell Usage Monitoring Customer Satisfaction Limit Adjustments Risk-based Collections Behavior Scoring Collection Actions Fraud Management Agency Placement Repossession Assessment Credit Risk Management Life-cycle Risk-based Collections

5. 5 Collections Management – Information is Key Prudent Best Practices 1. Gather all customer contacts & history 3.Score customer using risk behavior model(s) 4.Introduction of champion/challenger strategies 5.Extension of scoring models to Value Management Score customer against risk behavior model(s) using customer input data Combine different enterprise scoring models and systems to generate common view on the customer – allowing maximizing on his value Add additional – behavioral & predictive customer data describing his motivation and his psychometrics Segment customers into logical grouping (subjective/best practice) and according treatment 5.Introduction of Psychometric Profiles 2.Segment & assign customer to risk groups Frequent (automated) assessment & continuous improvement cycle - Ensure all customer contacts are tracked - Ensure all required history data can be obtained in (data model) and by the system (operations) - Ensure the availability of the analysis and reporting data - Ensure all customer contacts are tracked - Ensure all required history data can be obtained in (data model) and by the system (operations) - Ensure the availability of the analysis and reporting data

6. 6 Managing the Debt Collection Customer Segmentation Customer group 1: Willing to pay – pay in time Customer group 3: Could pay – but does Not want to (at least immediately ) Customer group 2: Willing to pay – but temporarily out of money Customer group 4: Does not want to or cannot pay Educate NegotiateStop Leverage Embed into other selection criteria Length of relation Length of relation Average used amount Average used amount Average payment behaviour Average payment behaviour Personal criteria Personal criteria Contract value Contract value Open promises Open promises Former actions Former actions

7. 7  Why move on to scoring?  What are the key benefits?  More formalized approach allowing more ‚objectivity‘ in decisioning (~ improved quality/reduction of credit risk)  Enables almost individual treatment („mass customization“)  Introduces easy extendable, changeable & maintainable frame for adding new criteria  Leverages ‚collections view‘ to enterprise-wide credit risk  Allows integration of „predictive“ models  Dynamic customer evaluation – each situation encounters the most recent events (not as static as within a treatment strategy) Information is Key… Scoring

8. 8 Customer Scoring Volume Demands automation Past Customer Data Analysis & Modelling - Understand your customers - create scoring model and scorecard - develop decision trees indiv. SCORECARDS Evaluation model Recalculate based on events Adjust if required Analyse the past Predict the future Decision trees using Decision Analytics Analysing model e.g. - Discriminent analysis (uni/multivar.) - Regression analysis (Logit/Probit) - Neuronal Networks Embed into Apply - Data availibiltity & Data history - Capacities & Resources - Know-how - Tools (e.g. Data Mining)

9. 9  Which customers are likely to stay, to go?  How can I reduce attrition / increase loyalty among the right customers?  Is there a best “next product” to offer my customer?  What should be the timing and channel for that offer?  How can I interest customers in new types of services, such as integrated production planning or a new product customization service?  How aggressively should I be approaching customers? Customer Issues  What is the future value that I can expect from my customer portfolio, and what are the sources of this value?  How am I doing compared to my competitors?  Am I winning/losing the right kinds of customers?  Am I getting sufficient value from the customers I seek?  How specifically can I increase the value and reduce the risk of my customer portfolio?  How can I learn and adapt quickly as conditions change? Tactical Strategical

10. 10 Integrated Customer Value Management Environment Profitability Attrition Vulnerability Customer Decision Strategy Processes Customer Management Decision Strategies Customer-Level Decision Engine Data Warehouse z Proactive Marketing Responsive Marketing Originations/ Provisioning Servicing Retention Management Collections Actions/ Tactics Feedback and Learning Customer Contact Internet Direct Marketing Call Center ATM Shop Operations Customer Knowledge Through Models and Data Segment Objectives Risk Profile Channel Preferences which customers what products what product(s) what fee what rate what credit limit pay/no pay limit adjustment what action, when outsource? waive fee(s) upgrade

11. 11 General Outsourcing Characteristics  An outsourcing contract is an agreement for services associated with service levels (measure of performance against agreed criteria).  For credit & collections, services that can be outsourced extend from whole business process, call center operations, to portfolio analytics, to IT systems and maintenance.  An outsourcing contract is generally a long-term agreement (3+ years) so understand the future strategy, and ability to adapt.  An outsourcing contract may require servicing from different locations, internal and external, possibly other countries (both near-shore and offshore).  “Buyers” expect significant cost savings, continuous improvement and/or business value. A “Seller’s” ability to do so is based on its concentration of infrastructure and expertise, its standardization, its efficiency and its creativity and innovation to adapt with changing markets.

12. 12 WHY: The Driving Motivators for Outsourcing Financial Pressure   Reduce costs   Reduce headcounts   Drive revenue Competitive Advantage   Speed to market   Innovation   Efficiency   Effectiveness   Drive revenue   Flexibility

13. 13 A Matter of Perspective Outsourcing Considerations in the Credit & Collections Space Buyers Outsourcers Staffing capabilities?   Difficulty in attracting and retaining quality trained staff in highly competitive market   Multiple opportunities for staff; knowledge retention; access to broad breadth of analytical, technological & process skills Supply/demand alignment?   Slow to grow and/or downsize; staff allocated to low value initiatives   Ability to re-allocate staff to other clients; completely scaleable both ways; same capability, but with different billing model Core competency?   Compete for attention and funding with higher-value alternatives   Heavy investment in leverageable infrastructure: efficiency, effectiveness, reliability

14. 14 WHAT: Candidates for Outsourcing in Credit & Collections Management Credit Life Cycle Credit Recovery Collections Usage Value Continuum Higher Lower Credit Data Storage Credit Scoring Credit Model DevelopmentBehavior Model Development Application Processing Account Retention CRM and Marketing Cross-Sell Delinquency Model Development Outbound calling Bankruptcy Processing Recoveries Post Write-Off Litigation Debt Sale Skip Tracing Fraud ID Detection Fraud Monitoring Letter processing System Maintenance & Support Analysis Champion/Challenger Strategy Design Execution System Development In-bound calls

15. 15 HOW: The Economic Framework 1.Identify the Impact Points = Key performance measures (KPM’s) 2.Quantify each Impact Point = Value of Improvement 3.Determine the Baseline 4.Define & Test Alternatives Approaches

16. 16 Identifying the Impact Points for Collections P&L Measures  Bad Debt  Gross Bad Debt, Gross Recoveries, Net Bad Debt  Fraud  Expenses  OpEx: Salaries (collectors, analysts, IT staff), Credit Reports, Skip Tracing  CapEx: Processing systems/infrastructure, upgrades  Revenue Non-P&L Measures  Churn/Attrition  Collection strategy attitude = follow-on business value  Cash Flow (DSO)

17. 17 General Outsourcing Claims 4 Distinct Impact Points Bad Debt DOWN Ops Expense DOWN Churn/Attrition Revenue UP

18. 18 Quantifying each Impact Point Credit Life Cycle UsageUsage CollectionsCollections CreditCredit Marketing Write-Off Recoveries Product Development Bad Debt   # of accounts   account balances Work more high-risk/high-balance accounts more aggressively, resulting in more payments Can’t control creditworthiness of through-the- door sales Can’t control pre- delinquency balance build-up

19. 19 Quantifying each Impact Point Pay lower rates FTE Expense   hourly rate   productivity   automation Collector Workforce Salaries Manual tasks Productivity Automate tasks Work higher % of paid hours Work faster

20. 20 ??? Additional Economic ModelingRevenue   # of accounts   usage/ARPU More efficient/effective collection efforts = Fewer accounts rolling through delinquency = Delinquent accounts cured sooner = Accounts back in buying cycle more often = MORE INCREMENTAL REVENUE?

21. 21 ??? Additional Economic Modeling Churn   voluntary   involuntary Better account segmentation = Risk-differentiated calling campaigns = Lower-risk customers don’t get heavy-handed treatment = LOWER VOLUNTARY CHURN? More efficient/effective collection efforts = Fewer accounts rolling through delinquency = Delinquent accounts cured sooner = Fewer accounts reach disconnect point = LOWER INVOLUNTARY CHURN?

22. 22 Points to Consider  Make sure the BAU forecast is realistic  Remember what’s in scope of control…and what’s outside of control  Focus on the business drivers  Test different scenarios  Define HOW the improvements are going to be madeSegmentation More dials/RPCs Better training More payments Faster payments Fewer forward rolls

23. 23 Pricing Models  Input-based models  Units sent for processing  FTEs  Cost Plus  Time & Materials  Build-Operate-Transfer (BOT)  Output-based models  Units processed  Fixed or Milestone Priced  Shared risk-reward  Contingency  Revenue Change  Savings Win-Win: How do the Buyer and Seller make money? Win-Win: How do the Buyer and Seller make money?

24. 24 Summary: A Top 10 List 1. 1. It’s about the ECONOMICS: Just about everything can be quantified (even “qualitative” factors). 2. 2. Define your reasons for outsourcing. 3. 3. Know your P&L. 4. 4. Verify (and challenge) all assumptions. 5. 5. Know what’s controllable vs. what’s not. 6. 6. Focus on the actual business drivers. 7. 7. Compare against out-year forecasts, not today’s BAU. 8. 8. Test different scenarios. 9. 9. Understand the linkages between process components. 10. 10. Know how both sides make money.

25. Internal vs. External? Calculating the Economic Decisions of Outsourcing Take decisions based on facts & Own the full process