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Analytics in financial services - practical methods that convert data to dollars


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Jaime Fitzgerald's keynote presentation at the Financial Services Symposium on August 18, 2011

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Analytics in financial services - practical methods that convert data to dollars

  1. 1. Analytics in Financial Services:Practical Methods that Convert Data to Dollars™Jaime Fitzgerald -- Founder and Managing Partner,Fitzgerald Analytics, Inc. Architects of Fact-Based Decisions™August 18th, 2011
  2. 2. “If You Like to Tweet…” Event Hashtag: #FSIUG Symposium Collaborators #FSIUG @AdelphiU @Oracle My Team @JaimeFitzgerald @fitzanalytics @Data2DollarsFinancial Services Symposium 2
  3. 3. Presentation Outline 1. Quick Intro 2. The Challenge  Business Challenges  Challenges in Addressing via Analytics 3. A Methodology That Helps: Causal Clarity™ 4. Application to Your Business Models 5. From Opportunities to Results 6. Key TakeawaysFinancial Services Symposium 3
  4. 4. Introduction Jaime Fitzgerald, Founder @ Fitzgerald Analytics • Find & unlock opportunities Professional Focus: via data, technology, people, and processes. Key Success Easier Ways to and Better Ways to Factors: Find Opportunities Unlock That Potential Principles “Begin with the End in Mind” (Covey) -> Goal Definition is Key I Work By: “Quality is Free” (McGregor) -> Process MattersFinancial Services Symposium 4
  5. 5. Presentation Outline 1. Quick Intro 2. The Challenge ("The Gap")  Business Challenges  Challenges in Addressing via Analytics 3. A Methodology That Helps: Causal Clarity™ 4. Application to Your Business Models 5. From Opportunities to Results 6. Key TakeawaysFinancial Services Symposium 5
  6. 6. A Challenging Time in Financial ServicesFinancial Services Symposium 6
  7. 7. “Rough Seas” in Financial Services 1 The Tide is No Longer Rising 2 3 Regulatory Currents Customer Behavior Shifting 4 Risk Management has Become Über-Strategic 5 New Competitive ThreatsFinancial Services Symposium 7
  8. 8. Trends and Challenges: “Rough Seas” Five Trends Creating “Rough Seas” in the Financial Services Market 1. The Tide is No Longer Rising: with a few exceptions—most notably parts of wealth management—growth no longer “just happens”….you have to make it happen The Waters are Choppy -- with today’s trends, the captain can’t leave the helm! 2. Regulatory Currents: existing models and assumptions have been upended. Lots of “re-routing” underway to protect profits and “work around” new constraints. 3. Customer Behavior Shifting: information-empowered customers are revisiting their options, choosing in different ways, and taking advantage of more transparency 4. Risk Management has become Über-Strategic: always essential, it has become do-or-die, and harder than ever as the spectrum of risks and threats grows 5. New Competitive Threats. Non-traditional players are increasingly seeking to “poach” business from incumbent players. These sharks show up suddenly, whether from Greenwich or from the other side of the world.Financial Services Symposium 8
  9. 9. Overcoming the Challenges While these challenges threaten, those who adapt to them best will profit. Challenge A Path to Overcoming It... Key Performance Indicators 1. Tide not  Optimize profit from existing customers  Retention Rate rising  Avoid attrition / protect customer equity  Share of Wallet  New rules change drivers of revenue and  Product Profitability (driven by “revenue replacement” during product 2. Regulatory cost for our products and operations redesign) Changes  “Explosion of redesigns” (Products,  Risk Mgt / Controls Performance Processes, Policies, Reporting, etc.)  Cost Control / Efficiency  Retention rate 3. Customer  Adjust to new customer buying criteria  Share of wallet Behavior  Customer lifetime value  Risk Mgt / Controls Performance 4. Risk Mgt  Manage high stakes risks more robustly (varies by business model)  Leverage sources of differentiation 5. Competitive  Share of target segments Threats  Foster customer loyalty to reduce  Customer experience + loyalty defectionFinancial Services Symposium 9
  10. 10. Five Profit Engines These Five Analytically-Driven Profit Engines are Powerful Weapons as you Compete in Today’s Environment… Method Keys to Profit Impact 1 Customer Lifetime  Allocate resources to your most profitable customers  Use WITH predictive analytics to INFER WHO WILL be most Value + Segmentation profitable in the future, not just the present.  You won’t be right all the time, and you don’t have to be 2  Identify the drivers of customer loyalty vs. defection Customer Retention  Target high-ROI tactics to retain most valuable customers 3 Cross-Sales /  Offer customers products they are most likely to buy Up-Sales  Choose the optimal time, method, and terms of the offer 4  Allocate marketing spend to the highest impact efforts Marketing ROI  Use predictive models to choose best target customers, timing, message, and channel mix 5  Adapt to new regulations, customer preferences, and costs New Product Design  Predict in advance the costs and benefits of product changes  Systematically test product features to find the most profitable designsFinancial Services Symposium 10
  11. 11. Key to Success: Integration! Don’t Build These Engines as Silos! Connect the Dots to Magnify Impact. 1 Customer Lifetime Value + Segmentation 2 3 Cross-Sales / Customer Retention Up-Sales 4 Marketing ROI 5 New Product DesignFinancial Services Symposium 11
  12. 12. Customer Profitability & Segmentation Analysis Analysis of customer-level profitability reveals valuable insights regarding the differences between customers Example: Use of customer profitability analysis to determine strategies for each unique group of customers… Illustrative 1. Retain Best Customers 3. Rationalize Benefits vs. Profit per Customer 2. Increase Share of Wallet Among Costs Among Least Mid-Value Customers Profitable Customers Customer Profitability ($/year) Loss per Customer Top 2nd 3rd 4th 5th 6th 7th 8th 9th Bottom Average (Most (Least Profitable Profitable 10%) 10%) Profitability Deciles (each bar represents 10% of existing customers, ranked by profitability)Financial Services Symposium 12
  13. 13. Profitability Management Becomes More Refined Over Time through an Iterative Process Driven by Customer Knowledge Build Customer Profitability Models  Identify costs & revenues Drive Action Into Frontline Systems Face-to- • Create consistent message Face  Build profiles  • Create consistent individuals Target action to message  Feed data from Data  • Target action to individuals Optimize product / service internal and external Warehouse portfolio Mail sources  Optimize product/service portfolio  Maintain data warehouses Phone External New Customer Knowledge Internet Data  Feed campaign results into data Sources warehouses  Test predictive accuracy of model  Break down segment into individual customer analysesFinancial Services Symposium 13
  14. 14. Putting it Together: Growth and Profitability Let’s look at four segments with different profiles, starting with their growth rates, their size, and their profitability per customer… 80% 60% Growth Rate in # of Customers Profitable segment: grow faster? 40% 1 Fast-Growing, (X-sell / Up-sell) No Profit (Product 20% Redesign) 2 3 Acquire More via 0% Targeted Marketing -20 -10 0 10 20 30 40 50 60 70 80 90 100 110 120 Direct Customer Profit -20% -40% Our Biggest Problem: Retention 4 Size of Bubble = -60% Number of CustomersFinancial Services Symposium 14
  15. 15. Integration: Connecting The Dots A few examples of how inter-related these processes are… 1 Customer Lifetime Value + Segmentation New Information and Insights 2 3 Cross-Sales / Customer Retention Up-Sales 4 Marketing ROI 5 New Product DesignFinancial Services Symposium 15
  16. 16. Why are Analytics Projects Risky?Financial Services Symposium 16
  17. 17. Achieving the Potential of Analytics – Closing the Gap To profit from analytics, you need results not buzz… 1. So Much “Buzz” about the Potential of Analytics  Best-selling books on Analytics (Competing on Analytics, Supercrunchers, etc.)  New efforts (business units, teams, roles, initiatives) 2. When Analytics Works, the Impact is Buzz-Worthy!  Selected firms have made analytics a source of competitive advantage  It happens every day… just not as broadly as would be ideal 1 2 3 4 Right Focus Right Method Execution Results! Let’s discuss the keys to increasing your odds of success…Financial Services Symposium 17
  18. 18. Simplify Your Analytic Process via “Causal Clarity” Clearly defining “Cause and Effect” is the most crucial enabler of analysis that is Find Unlock More  Simpler Opportunity Easily Faster  More Efficient Fewer Wasted Steps  Higher Impact Benefit /CostFinancial Services Symposium 18
  19. 19. Three Simplifying Concepts To “begin with the business goal in mind,” I recommend three concepts Term Definition 1. Point of Opportunity  An opportunity for improvement within YOUR business model  Defined because it impacts key drivers of your results 2. Causal Clarity  Clear Definition of key drivers, cause + effect in Cause Effect your business model, business unit, etc.  Easy to Explain to others, preferably visually 3. Causal Model  A visual representation of “what drives results” in Price Revenue your business model Transactions  Create this, and you have achieved “Causal Clarity”Financial Services Symposium 19
  20. 20. Causal Models: A Simple “Base Case” Each business model has an inherent “causal model,” but the “core branches” are similar Example: Drivers of Net Profit Revenue less Your Has Cost of Revenue Gross Profit Business Operating Costs Model less Net Profit Marketing Other Costs Overhead OtherFinancial Services Symposium 20
  21. 21. What Happens If We Skip the Causal Clarity? Why not just get to work? …We are stuck “trying” rather than causing. We If we don’t establish a may “try hard but cause less” than if we find the “causal model”… “points of leverage” in the causal model …It’s pretty easy. It takes careful thought, but The Good News Is… we are not building a spaceship… Let’s take a look at how painless — and valuable — this can beFinancial Services Symposium 21
  22. 22. The Good News: Establishing “Causal Clarity” is Not Rocket Science Easy and Quick: There are 3 Main Steps 1 2 3 3 Things To Goal Business Model Causal Model Define: Inputs  Usually net profit  Products / services  Aka “drivers tree” To  Can be anything!:  Distribution  Makes the causal Use: – Marketing ROI  Target customers model visual – Non-profit impact  At what price – Customer  Cost structure satisfaction  Known KPIs and – Etc. rationale for themFinancial Services Symposium 22
  23. 23. The “Point of Opportunity” Concept Illustrated Has “Causal Creating Your Business Model” A Point of Model (aka Drivers) Opportunity Returning to the causal model above on the previous slide, let’s find a concrete point of opportunityFinancial Services Symposium 23
  24. 24. A Point of Opportunity Here is an opportunity to enhance ROI on Marketing + Sales efforts: Point of Opportunity: “Efficiency of New Client Acquisition” Key Driver / KPI: Acquisition Cost per New Client Formula: [spending on new client marketing]/[# New Clients) Transactions Price per per Client Transaction X # of Clients Volume Sales and MarketingFinancial Services Symposium 24
  25. 25. What We Need to Get Practical To get practical about analytics, we need three things… What We Need Definition 1. Causal Clarity re: Your  How You Make Money Business Model  Key Drivers of Results 2. Definition of Your Points  Gaps vs. Potential of Opportunity  Room for Improvement 3. A Plan to Capture the  Insight You Need Opportunity  Method to Get ItFinancial Services Symposium 25
  26. 26. Planning Your Analysis Planning starts with the goal, the “point of opportunity” Your Point of Opportunity (Decision or Process) Translates to Insights or Information Required Which drives Analysis Methods Required to Create this Information Allowing definition of Required Data And selection of the right Tools, Platforms, Technology, People, and ProcessesFinancial Services Symposium 26
  27. 27. Summary of Key Takeaways We hope you will benefit from the concepts shared today For All 1. Begin Your 2. Define + 3. Identify 4. Define the 5. Keep Attendees Business Agree on Points of info needed analysis as Model the Causal Opportunity to unlock simple as Model the oppor- possible… tunity Tips By Executives Leadership Role:  Establish “causal clarity” visually so that everyone understands  Encourage teams to use this context to prioritize and target effort  Expect recommendations to be justified by their impact on key drivers Business Professionals Technology Professionals  Identify points of opportunity  Insist upon understanding the before investing time in analytic business context and causal logic details of requests for analytic systems and effortFinancial Services Symposium 27
  28. 28. Invitation to Two Free Communities The Practical Analytics Portal Our Mission This is a great place to To "democratize analytics" by sharing knowledge and tools. learn and network with other professionals in Our Vision analytics, both specific to The potential of analytics "within Financial Services, and reach" to an exponentially larger Beyond community of professionals. To Join: To Join: email me -and-Data-in-Financial-Services/ for an invitationFinancial Services Symposium 28
  29. 29. Analytics Democratized™ To Join: Text “Analytics” to 41242 ….or find us on Facebook & TwitterFinancial Services Symposium 29
  30. 30. Q&AFinancial Services Symposium 30
  31. 31. “Bonus Slides”Financial Services Symposium 31
  32. 32. Background: Types of Questions Analytics May Answer Past Present Future What happened? What is happening What will happen? Information now? (Reporting) (Alerts) (Extrapolation) What’s the How and why What’s the next best/worst that did it happen? best action? can happen? Insight (Modeling, (Recommendation) (Prediction, experimental optimization, design) simulation) We are about to get practical, let’s keep the following in mind… Source: Tom Davenport in “Analytics at Work”, Harvard Business School PressFinancial Services Symposium 32
  33. 33. One More Framework: Value vs. Volume In some cases, analytics makes a single high stakes decision better. In other cases, we “make it up in volume” High High-Value, Low-Volume Value Decisions Economic Impact of Example: M&A, capital investment, Individual Decision strategic market positioning Medium-Value, Medium-Volume Decisions Example: Product development and pricing, customer segmentation, and targeting Low-Value, High-Volume Decisions Example: Loan approval, customer cross-sell offer, customer upgrade request, prospect marketing offer assignment Low Value Low Volume Decision Volume High Volume Source: Neil Raden and James Taylor in “Smart Enough Systems,” Prentice Hall.Financial Services Symposium 33
  34. 34. Financial Services Business Models To get practical, let’s establish causal clarity for several key business models in Financial Services Core Products / Key Drivers Business Model Services (illustrative)  Customer acquisition,  Deposit Products 1. Retail Financial retention, and profitability  Loan Products Services  Product pricing  Investment Products  Share of wallet 2. Commercial /  Debt Financing  Fee structure / yields  Institutional Financial Services Business Banking /  Volume (e.g. for Money Managers) Financial Services  Cost efficiencies  Cash Management  Proprietary trading  Risk-adjusted returns 3. Trading  Market-making  Transaction spreads  Trade execution  Cost efficiencies  Underwriting  Deal flow 4. Investment  M&A  Deal completion rates Banking  Other advisory services  Fee structureFinancial Services Symposium 34
  35. 35. 1. Retail Financial Services Illustrative Example Products Point of Increase ROI on Marketing Spend 1. Deposits Opportunity: BY Decreasing Acq. Cost / Customer* Key Driver / KPI: Acquisition Cost per New Client 2. Investments Formula: [spend on new client marketing]/ 3. Loans [# New Clients) Products per Profit per Client Product Allocation of X Marketing $ # of Clients Volume *2nd Order Causality + Pt of Opportunity * P = Profit per year per customer, n=number of years the customer staysFinancial Services Symposium 35
  36. 36. 2. Commercial/Business Banking / FS Illustrative Example Point of Grow Fees BY Increasing “Share of Opportunity: Wallet” from Corporate Clients Key Driver / KPI: Share of Wallet (“SOW”) Formula: [Total Fees from Client]/[Total Client Fees on Products YOU offer, via ALL providers] Customer Experience Share of Optimization Marketing Wallet Customer X Better Outreach Loyalty via Predictive Total Size of Analytics Client benefit Wallet of using your • Everything ok? platform more The size of the • You would benefit exclusively pie we are from product X sharing…. * “Total Client Fees” includes spending on ALL companies that offer the same or similar products/servicesFinancial Services Symposium 36
  37. 37. 3. Trading Illustrative Example Point of Maximize Alpha! Opportunity: Key Driver / KPI: Risk-Adjusted Return Formula: Alpha Volume: # Trading Trade-able Quality of Real- Profits Opportunities Time Decision X Less… Models + Tools Quality: “Cost of Profit per Discovery” Opportunity 1. Accuracy of “Triggers” 2. Cost of False Positives How “Big” are Investments in 3. How well do models these Trades Finding these adjust to changed Opportunities world?Financial Services Symposium 37
  38. 38. 4. Investment Banking Illustrative Example Point of Increase Profit per Employee Opportunity: Key Driver / KPI: Return on Human Capital (“HCROI”) Formula: [NET Profit] / [# Employees] Staff & Team Profit per Gross Profit Net Staff + Team Person-Hour Profit Effectiveness X Less… “Other Investments in # Hours Staff Performance” 1. Resource allocation (Who does what. Why?) • Cost of analysis 2. Re-use of IP: How well do we • Cost of training re-purpose? • Cost of new systems 3. Task Value to Cost: (e.g. knowledge mgt + workflow) How much waste?Financial Services Symposium 38