Driving Productivity Gains by Aligning Management and IT

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Agenda:
-A business case for change
-Operating model – design considerations
-Data & MIS considerations
-Technology
-Investment and associated returns

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Driving Productivity Gains by Aligning Management and IT

  1. 1. Driving productivity gains by aligning risk management and ITSohail Farooq, Sr. Director and ME Consulting Practice Leader, Moody‟s Analytics November 2012
  2. 2. Contents1. A business case for change2. Operating model – design considerations3. Data & MIS considerations4. Technology5. Investment and associated returns
  3. 3. A business case for change
  4. 4. Pressure on the credit process to evolve remains relentless Pressure on the credit process to evolve remains relentless The credit process re-alignment is driven by a number of internal and external drivers: – External drivers  Regulatory: Basels II & III  Evolution of market conditions: focus on core business in post write-off period and cost savings – Internal drivers  Market conditions – focus on cost drivers, i.e. loan losses, productivity, etc.  IT consolidation (i.e. target architecture): Consolidation of credit risk MIS and reporting systems  Introduction of new performance metrics (e.g. Economic Profit, RAROC)  Integration of objective risk measurement models and other credit decision tools  Redesign of credit policy (e.g. limit setting)  Workflow automation, e.g. auto accept and auto reject  Strategic and organisational changes (e.g. separation of sales and credit, centralis ation) The credit process re-alignment can potentially unlock significant cost savings
  5. 5. Often credit process upgrades are rendered incomplete due to organizationOften credit process upgrades are rendered incomplete due to organizationOften credit process upgrades are rendered incomplete due to organization or structural complexitiesor structural complexitiesor structural complexities Classic business process upgrade Lack of integration with value-adds Classic business process upgrade Lack of integration with value-add illustration illustration RAROC Skew By Business Unit RAROC Skew By Business Unit Before ratings After ratings RAROC Before ratings After ratings RAROC 15% Value Creating BU 1 15% Client 18% 120% BU 1 Business Units Creating Value BU 2 Business Units Client Servicing Client 18% 120% BU 2 Servicing ServicingClient 27% Servicing Credit 27% 100% 17% 50% Activities Credit 100% 17%Administrative 50% Credit 15% Activities Value Destroying Administrative Credit Activities 15% Administrative 80% Value Destroying Business Units Activities Administrative 80% Business Units 18% BU 3 BU 4 40% 18% Sales and 60% BU 3 BU 4 Sales and 40% BU 5 Sales and Marketing 60% Sales and Marketing BU 5 Marketing Marketing BU 6 40% BU 7 BU 6BU 8 BU 10 40% BU 7 BU 8 BU 1 BU 9 Hurdle 20% Rate 9 BU 20% = 10%  Streamlined Credit Approval Process 0%  Streamlined Credit Approval Process 0% 0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100%  RMs vs. credit officers continue to retain full 0% 10% 20% 30% 40% 50% 60% 70% 80% 90%  RMs vs. credit officers continue to retain full -20% % of Bankwide Economic Capital responsibility for credit assessment -20% % of Bankwide Economic Capital responsibility for credit assessment  The rating tool decisions support not fully recognized  The rating tool decisions support not fully recognized  Economic framework for discussing credit decisions  Primary basis for lending remains unchanged as  Economic framework for discussing credit decisions  Primary basis for lending remains unchanged as based on risk/return, not risk control security value based on risk/return, not risk control security value  Explicit risk/return approach to be aligned with  Written credit application replicates analysis covered by  Explicit risk/return approach to be aligned with  Written credit application replicates analysis covered by shareholders` view of how credit decisions should be rating tool shareholders` view of how credit decisions should be rating tool made made
  6. 6. Perceived lack of clarity is often driven by internal constraintsPerceived lack of clarity is often driven by internal constraints Structural Factor Front-Office Behaviour Outcome Unclear Strategy Focus on Lending Weak Origination Discipline  Strategy not widely understood  $1 of lending revenue equals $1 of  Limits not enf orced, because the  Little/no obvious competitive advantage non-lending revenue rationale f or having them is not shared in some actively pursued businesses  Poor cross-sell due to „patchy‟ non-  Lack of f ocus on identifying  Some businesses with bad strategic f it lending products and limited customer realistically achievable cross-sell f ranchise revenues to pay f or lending subsidy  Lack of consideration of economic cost of credit at origination Revenue Culture ‘Revenue Chasing’ Heavy/Costly ‘Front-End’ Credit Process  Revenue targets (to determine bonus)  Lack of competitive advantage results  Incremental credit requests require a  No capital charge in „revenue chasing‟ / riskier disproportionately heavy credit transactions process  „Revenue chasing‟ results in multiple submissions of the same application Organisational Misalignment ‘Slipping Through the Cracks’ Lack of Focus on Middle/Back End  Multiple legal entities (group  „No‟ does not mean „NO!‟  Excessive f ocus on f ront-end companies)  Lack of clarity allows some process (analysis/approval) at the  Poorly def ined roles & responsibilities transactions to „slip through the cracks‟ expense of monitoring, intensive care  Committee culture: Lack f ocus on risks and workout and recovery but f ocus on adjudication
  7. 7. Develop a common language Develop a common language Wholesale Revenue/RWAs Annual Average 16% Bank X options Strategy A Strategy B Strategy C Bank Y 14% Risk: -80% Risk: -60% Risk: -15% Revenue: +80% Revenue: +130% Revenue: +190% 12% Bank CS Bank J 10% C Bank D Bank SG 8% B Bank AA Bank HC 6% A Bank US Bank S Bank BP 4% Bank BS Bank L Bank B Bank X Bank BB Bank CB 2% 0% 0.0% 0.2% 0.4% 0.6% 0.8% 1.0% 1.2% 1.4% Loan Losses/RWAs Annual AverageSource: Examples
  8. 8. Operating model – designconsiderations
  9. 9. Traditional functional organisation design can undermine value optimisation Traditional model Problems  Adversarial relationship Finance Marketing  No party with holistic value responsibility  Over-emphasis on intermediate (non-value) metrics (e.g. loss rates, Credit Operations response rates)  „Silo mentality‟
  10. 10. Organisational redesign remains the key to improving credit processing Organizational models for credit origination and adjudication Lagging Market Standard LeadingApplication Process Ad hoc Paper-based Standardized Integrated form and Green/yellow/red tool drives Formal separation or application form(s) application form, rating model, simple fast-track/normal/autoreject decisions Origination and typed into electronic rules to screen Portfolio Group, file and spreader applicants transfer price based on NPV modelCredit Analysis “Character Simple analysis Analysis and rating Joint AO/Credit Rating tool Risk vs. return in a Lending” and loan grading by by account officer, analysis, supported assigns risk portolio context Account officer reviewed by credit by a rating tool grade, simple risk vs. returnCredit Approval Account Officer, Multiple Single committee, „Four Eyes‟ (AO + Fast-track Approval and signature from committees, tilted tilted to credit Credit) committee by approval based pricing subject to Branch Manager to commercial exception on hurdle rate portfolio management policiesMonitoring and re- Annual review Smallest, highest Simple, early Robust early warning Portfolio-driven investigations of credit Managed as aaffirmation for all accounts grade borrowers by warning tool in tool replaces annual files trading book exception addition to annual reviews for most review process loans
  11. 11. Many different relationships exist between recoveries and the businessunits which originate the assets Organisational models for recoveries Laggard Market standard Leading practice Specialist Standalone within the Specialist Asset Undifferentiated Asset Owner Business Unit Business Credit Officer Servicer Units  Business Unit  Business Unit  Business Unit  Business Unit  Asset  Business Unit owns assets owns assets owns assets owns assets ownership is retains but transf erred to ownership of  Account responsibility  Specialist  Specialist Recoveries the assets Of f icers is blurred Recovery Unit Recovery Unit manage reports to reports to  Recoveries  Recoveries problem  Standalone Head of Credit as Business acts as accounts recovery Unit Business Unit Department Unit Business (reports to Units  Undif f erentiat  Undif f erentiat  Recovery Unit  Full P&L Board) ed P&L ed P&L acts as cost based on  Full P&L  Constructed centre transf er price based on f ees P&L based on costs and interest income
  12. 12. There is often an intermediate ‘waypoint’ in the migration toward adecision-focused organisational model Traditional Transitional Eventual Finance Front of f iceFinance Front office Finance Front office Strategic Policy and decision analytics support Credit Operations Credit Operations Credit Operations ‘Functional adversaries’ ‘Policy & analysis group’ ‘Strategic decision support’ Classic structure  Integrated analytical approaches  Value-based structural decisions Conflicting goals  Integrated data strategy  Design of value-based operational decision tools  Coordinated use of value measures  Single analysis team  „Membership‟ from all relevant functional disciplines  Profit responsibility
  13. 13. Data & MIS
  14. 14. A few key principles should be followed while designing the data andtechnology architecture Overarching principles  Don‟t let technical constraints, e.g. preference for simplicity, drive business tactic and process decisions  Don‟t hand off data and technology upgrade projects to IT Data-specific principles Systems-specific principles  Data warehouse, modelling data  Processing systems: environment and model implementation – Flexibility to add and change product data should be on separate platforms features at account level is key  Trying to create a global, cross-customer – Ability to capture data from processing data warehouse is too ambitious – design systems is also critical consistency is more important than a single  Decisioning systems: database – Good for managing workflow and  Cost of data storage is much lower than triggering actions based on events, but value of data generally not for running value-based decision models  Err on the side of storing more rather than less data – Ease and flexibility of updates should be important selection criterion
  15. 15. There are broadly two organisational approaches for analytics functionsacross products/businesses Top-Down ‘Networked’  Central analytics group supporting all  Decisioning analytics resources housed businesses within each business  Larger businesses may have „local‟  „Network‟ or analytics steering group analysts, but models and strategies need to consisting of analytics leaders from each be approved by central function business  Trade-off between scale and local  Analytics group sets standards, drives customization innovation and ensures knowledge transfer  However, customisation can be achieved by  Has the benefit of more integration with creating product/business-dedicated teams business, better buy-in of output and more within central unit pertinent decisioning solutions  Easier to drive technical innovation  Maintaining consistency can be a challenge if „network‟ is weak
  16. 16. Technology
  17. 17. We see optimisation as the integration of three key elements Technology Optimising credit Processes processing & MIS Operating Model & Organisational Structure
  18. 18. Workflow optimization exampleTechnology drives productivity gains Collection and recovery technology Lifecycle of a file Origination Cross-sell/ Problem loan ‘Turnaround’ ‘Workout’ Collections Pre-litigation Litigation Recovery or management identification recovery write-off 0 days 90 days Rating tools past due past due (official default) Early warning tools Active file management Key Attributes Process automation  Rating tools: Stable, stratif ied predictor of default  Early warning: Sensitive, behaviourally-based problem loan detector  Active f ile mgmt.: Parameterized f ile classif ication and allocation Data based decision support  Process automation: Powerdialling, automatic letter production  Decision support: Outsourcing, strategy, file allocation, „champion vs. challenger‟ Collection  Collection model: Probability of collection Recovery model model  Recovery model: Probability of recovery  Litigation mgmt.: Automated agenda, tasklist cost management Litigation mgmt.
  19. 19. Focus resources on the analytics and information value chain Business areas Origination Decision Back-office Workout & Recovery & collections litigation Marketing Screening Early Valuation Decision Warning tool management Rating  Information-based decision Pricing Recovery support Scenario testing Predictor  Target setting  Performance monitoring Share of Collection IBDS  Business intelligence Wallet Predictor Process management  Single data entry  Application form  Routing  Documentation  Power-dialling  Electronic agenda  User-f riendly  Solicitation  Electronic sign off  Contracts  Skip tracing interf ace  Letter production  inf ormation Electronic file transf er  Automatic f ile Advanced analytics routing Database  Portf olio management management  Automatic “state” DB credit  Analysis and insight categorisation  Data management  Perf ormance measurement  Automatic data  Data mining update  Reporting  „Silo‟ Management  Tool improvement  Reporting (regular and ad hoc)  Tool development
  20. 20. Investment and associated returns
  21. 21. Recurring cost savings pay off for the investment automatically Comments Cost – Mortgages and P. Loans*  Cost savings in Risk are derived from lower requirements of analyst time, largely due to lower number of 52,000 applications x $24 applications that reach the analysts for sanction$ 000 Unit Savings ~ $1,2 MM – ~ -75% Required analysis hours/year: ~31,500h to4,500 Committees Committees ~7,800h4,000 Analysts3,500 Analysts  Cost savings in the network beyond those achieved via Network3,000 Committees Analysts the integration project are thought to be small and often2,500 hard to analyze, given that the optimization project2,000 contemplates:1,500 Network1,000 Network – The transfer of main administrative tasks from network 500 to central back-office function 0 – The elimination of the duplication of work to collect Pre-TOM Post-TOM data and process applications – Estimated cost savings assume time required for „Risk Audit‟ is the same as today‟s (although this should be tested during pilot)
  22. 22. Direct Banking Innovation Case studyThe concept of direct banking as practiced by ING Direct globallyOriginal Value proposition – Entry approach No. of clients and deposit volume (estimates) Category killer approach Clients Funds entrusted Rank within Offering of only high interest, no fees, simple savings (‘000) (BN) savings market account with great customer service Canada (5/97) 1,491 12.3 7 Spain (5/99) 1,455 13 6New value proposition – Evolving focus Australia (8/99) 1,414 11.2 6 Once ING Direct has successfully built a large enough France (5/00) 626 12.3 9 customer base, it starts to expand into other product areas (cross selling) USA (9/00) 4.629 36 21 In mature markets and where ING Direct is established Italy (4/01) 792 14 7 such as e.g., Canada, it offers a full-fledged product set Germany (8/01) 6,005 60.6 6 comparable to a standard Retail banking offering UK (5/03) 1099 36.3 8 Total 17,511 M 195.9 BNBusiness model Business built on 4 pillars and it competes success-fully Retail deposit market share since inception in large, technologically sophisticated markets Market share 6.0% ING Direct Model UK 5.0% Aus. 1. Cost 2. Brand 3. Focused 4. Effectiveefficiency/ mgmt./ high 4.0% D Product Customer minimum marketing USA mgmt. service 3.0%complexity spending F 2.0% ING Direct does nothing that creates complexity and E therefore inefficiency 1.0% Can Same operating platform in all countries with minimal 0.0% adoptions only (e.g., for regulatory reasons) 0 1 2 3 4 5 6 7 Strong brand building to create traffic Years after launch
  23. 23. Conclusion & Parting thoughts Strongly Neutral Strongly Disagree Stance Agree The market sets the price – we can only respond 1 3 5 If we tamper with customer pricing, attrition will be the result 1 3 5 I do not believe too much money is left on the table in any event 1 3 5 What we „lose‟ in one area we make up in another 1 3 5 We cannot be seen as „sticklers‟ on price in the market 1 3 5 Organizations that command better pricing simply have a better value 1 3 5 proportion We would like to price better but don‟t 1 3 5 have the tools and resources to do so
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