What s the payback on Connected Decisions?

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1 What s the payback on Connected Decisions? Sharing data, analytics and intelligence across the customer lifecycle produces better decisions, enhanced profitability and a sustainable competitive advantage. Number 9 November 2008 FICO has built a library of use cases in which sharing data, decisions and analytics across the credit lifecycle produces a significant and measurable bottom-line impact. It makes business sense that sharing intelligence to connect decisions across the customer lifecycle will produce smarter decisions. And decisions that are better informed have been proven to enhance performance. But exactly how can decisions be connected, and what is the value that can be expected? Historically, lenders have acquired separate decisioning systems to support individual functions in the credit customer lifecycle. These stand-alone systems have served them well. Lenders have also sought out insights from additional sources to help improve the choices they make in managing their operations. For example, lenders have relied on data from credit bureaus to help them assess customer risk and opportunity. While upgrades and enhancements to existing systems will improve their performance, taking a silo approach has its limits. There are efficiency gains and competitive advantage that can only be obtained by paying attention to what happens between decisions for example, between an originations decision and a collections decision, or an authorization decision and a fraud decision. This opportunity is not lost on the industry. According to a recent Tower Group survey of consumer lenders, 80% of respondents believe an integrated view of customer data will become increasingly important in their decision processes in the next two years. Yet very few institutions take a holistic approach to decision making. The problem is not lack of interest it s execution. To date, there has not been a viable solution that makes connected decisions possible across the entire lifecycle. That s about to change. Under FICO s initiative, Decision Management technology is evolving rapidly from stand-alone products to a Connected Decisions approach that will create greater value. This paper describes this integrated approach and presents three examples that are representative of the potential ROI from Connected Decisions. FICO believes that delivering a Decision Management suite that connects decisions is the critical next frontier where productivity and profits are to be found. Institutions that make the strategic move to a unified approach to decision management will find a new and distinctive source of competitive advantage. Make every decision count TM

2 »»What Are Connected Decisions? The concept of Connected Decisions is all about taking a wide-angle view of the business, to see problems and spot opportunities early while there is still time to take decisive actions that improve results. It s not just about better vision it s about making better decisions. Connected Decisions means taking a customer lifecycle view rather than a functional view. It recognizes that access to historical information, previous actions, and current policies at one decision point in the lifecycle can influence decisions at another point. This influence can be negative, when lack of awareness fails to account for all risk, or positive, when the additional information uncovers hidden revenue opportunity. The real challenge is to figure out what is required to support a Connected Decision environment. That is precisely the problem FICO has invested in solving. Today s decisioning systems are typically segregated by lifecycle function: marketing, origination, account management, collections and recovery, and fraud management. As a result, decisions made in any one function do not take into account the total customer relationship. This includes not only the customer s holdings inside and outside the firm, but also the historical information and activity related to that customer in other lifecycle areas. For example, a high-value customer that by oversight misses a payment might receive a harsh collection notice, when only a collections perspective is considered. But when the history of the customer s good standing from account management is connected, a more courteous treatment is applied. Of course, a lender would always extend favorable policies to high-value customers. But these are not manual events. Scenarios like this one are buried in the millions of transaction and policy decisions made each year. So any real solution that delivers Connected Decisions must be woven into the operations of the Decision Management systems. This means the lifecycle products need to be designed to work as a suite. Figure 1: A New Approach to Decision Management Decision Management Application Suite Origination Customer Management Collections & Recovery Fraud Decision Management Architecture Common Components Data Model Rules Management Model and Rules Case Management Reporting Repository FICO is bringing this approach to market through our Decision Management suite. Taking a unified view of decisioning across the credit lifecycle, the Decision Management suite provides linkages between leading solutions for origination, customer management, collections and recovery, and fraud management. page 2

3 Enabling Connected Decisions In order to make Connected Decisions possible and realize tangible value from them, Decision Management solutions need to be built on a common technology architecture. A service-oriented architecture ensures flexibility and reuse in order to lower the cost of deployment. It is not, however, the primary source of added value. The core driver of incremental business benefit is insights from the entire lifecycle and access to FICO s market-leading analytics. The unified architecture will enable higher analytic performance and better decisions by leveraging a set of shared components, including: These vital components add value within each functional area while also making it possible to extract the value that lies between different functions. Data Model A common data model ensures that data is consistent from one application to the next, and that data updated anywhere within the suite is available across the suite of applications. We have designed this data model to improve analytic development by: 1) providing clean, normalized data; and 2) linking data and decisions from various parts of the lifecycle. An analyst building an originations model, for example, can better recognize the factors that identify fraud risk or predict default. Knowing what to include in the model is critical, which is where FICO s 50 years of experience with Decision Management solutions makes a difference. Rules Management All applications in the Decision Management suite share a common system of creating and changing business rules. The result is that consistent decisions and policies can be deployed across the lifecycle and even across offices from a single, centralized system. Our Decision Management architecture uses the industry-leading FICO Blaze Advisor business rules management system, which is ranked #1 by Yphise, an independent technology research and analyst firm, and other third parties. Model and Rules Repository All rules and predictive models are stored in a central repository, where they can be accessed via any application for any decision across the lifecycle. This feature of our Decision Management architecture is also based on the FICO Blaze Advisor system. Case Management A unified case management system will make it easier to review and resolve cases across functions of the customer lifecycle, and to move cases from one area to another. FICO brings deep expertise to the specific requirements for case management throughout the customer lifecycle, based on our Decision Management applications. Reporting Shared reporting functionality and formats allows for consistent reporting across all applications and easier transfer of knowledge from one functional area to another. The critical factor in reporting is the linking of performance data back to individual decisions. That enables business managers to track, for example, the impact of originations strategies on collections, and to follow individual accounts through the lifecycle. page 3

4 Figure 2: The FICO Decision Management Architecture DESIGN TIME EXECUTION TIME CLIENT ENVIRONMENT Common Browser-Based GUI Portal Services Layer Strategy Design Service Invocation Calling Application Model Management Decision Orchestration Business Process Mgmt & Monitoring Rule Management Simulation & Optimization Configuration & Deployment Rules & Models Rules Learning Models Performance Management Adaptive Engines Event Management Case Management Business Services Security Enterprise Services Enterprise Service Bus... System Mgmt Identity Mgmt Decision Services Software Services Data Integration Layer Client Data Store Analytics Development OLAP/Reporting Common Data Model OLTP Provider Access 3rd Party Data FICO s Decision Management architecture includes the strategy design functions, powered by our tools for building models and managing rules, and the decision services layer, which orchestrates execution of the right rules and models to deliver the right decisions and actions to each operational transaction. Besides enabling Connected Decisions and the resulting business benefits, the Decision Management suite will also bring a number of operational benefits. By having a single analytic development, testing and deployment process across the entire lifecycle, operational complexity is reduced substantially. The common architecture allows rapid deployment and makes implementation less costly. Upgrading will also be easier, faster and less costly than it has been with standalone solutions. In a service-oriented architecture with shared components, businesses can install upgrades and add new modules without a rip-and-replace approach common in today s systems. page 4

5 How Connected Decisions create value Connected Decisions can deliver a wide range of business and operational benefits. Before covering the specific examples, it is helpful to point out some of the areas where Connected Decisions create value. Vision: Improved business visibility and reporting across the entire customer lifecycle. Segmentation: Finer categorization of customers leads to better matches between actions and outcomes. Lifecycle coordination: Individual and incremental value-add through connections that span different types of decisions: Treatments based on the customer s total relationship and lifetime value Identification of cross-sell and up-sell opportunities, in-stream with customer touchpoints Early detection and prevention of customer dissatisfaction mistakes (collections calls, blocked authorizations from fraud risk) that can damage relationships Improved marketing effectiveness from both an operational perspective and acquisition success Fraud detection; early and often across the enterprise Policy and compliance management: Consistent management and shared best practices of policies at all levels: account, customer, location/branch, geography and parent/subsidiary. Time to market and cycle-times: Risk avoidance and actions on opportunities in real-time or batched, as needed; flexible architecture allows for quicker spin-up of new product offerings.»»the Value of Connected Decisions: Case Studies FICO has created numerous scenarios in which interoperability between different Decision Management applications enables Connected Decisions that produce measurable value. Our objectives were to: Quantify the potential return on investment when decision points are connected. Illustrate the types of opportunities that are possible by sharing data and analytics between functions to produce more effective decisions. Invite a dialogue with our clients to explore Connected Decisions that have future potential. The following three examples demonstrate the value of Connected Decisions in a Decision Management suite environment. page 5

6 Scenario 1. Cutting First-Party Fraud at the Source In this example, we examined how integrating originations data with fraud management analytics improves detection of first-party fraud, in which the fraudster obtains credit under false pretenses with no intention of repayment. Conventional fraud analytics focus on third-party fraud, looking for changes in transactional behavior patterns, such as unusual purchase types, amounts or locations indicative of activity by someone other than the legitimate cardholder. With first-party fraud, however, the fraudster is the customer, and the behavior may remain typical until the moment of bust out, when the fraudster maximizes spending before disappearing. Most lenders classify first-party fraud losses within bad debt losses rather than measuring them separately. Based on case studies with participating banks, FICO found that first-party fraud losses can be as high as 100 basis points ($0.01 loss/$1.00 revenue) compared to third-party fraud at basis points ($0.001 loss/$1.00 revenue). By factoring originations data and risk score into transactional fraud scoring once the account is established, banks will be able to identify and treat first-party fraud. First a model should be deployed to detect potential first-party fraud at the origination stage. Second, the identification and investigation of first-party fraud should continue after the account is active by monitoring the monetary and non-monetary transactions. Our clients experience up to 50% in the reduction of first-party fraud losses with a first-party fraud detection capability, combined with supporting services. An analytic model combining origination data with fraud detection analytics can produce from 15% to 20% reduction in fraud losses. Adding rules strategies and professional consulting can create further reductions of 25% to 30%. page 6

7 Figure 3: Pass Originations Data and Risk Scores into FICO TM Falcon Fraud Manager ORIGINATIONS FRAUD Is Application Approved and Accepted by customer? Send application data (with application ID & acct #) and Risk Scores Is profile initiated? NO Initiate and update profile with data and score Update profile with data and score Book Loan to Client Host System and Assign Account # Client Host System Provides Acct #s to Application IDs New account s monetary & non-monetary transactions scored leveraging application data/score Does score indicate high probability of suspect fraud? Do rule conditions of transaction & other data fulfill case creation logic? Case Generates Fraud Analyst Investigates for first-party fraud Analyst dispositions case and takes appropriate action Originations Process First-Party Fraud Identify Data is updated into Originations Fraud Check lookup tables First-Party Fraud Identify Data collected for file update Dispositions and Actions stored for future risk segmentation and fraud modeling This diagram illustrates how originations data and risk scores are fed into FICO Falcon Fraud Manager. The fraud management system leverages application data and risk score in its analytics. The model utilizes the customer behavior with the monetary transactions to produce a transactional score indicating fraud. Rules on case generation based on fraud score and/or fulfilled decision criteria will generate a case for investigation. Identified first-party fraudster demographic data is fed back into the origination system and factored into future origination decisions. page 7

8 Financial Benefits The chart below shows a sample ROI calculation for a bank with 2 million accounts. Based on an estimated first-party fraud loss reduction of 20%, the savings from integrating origination data and fraud analytics are projected at $6 million. Institution Profile Portfolio Size in Accounts 2,000,000 Average Balance Active Accounts $2,000 Portfolio Size Active Accounts 1,600,000 Portfolio Value Active Accounts $3,200,000,000 Third-Party Fraud Loss $4,000,000 First-Party Fraud Loss $30,000,000 Revenue per Active Account $50 Value Reduced First-Party Fraud Losses by 20% Reduced Implementation Costs First Year Total Savings Estimated Benefits from Interoperable Origination and Fraud $6 million $50,000 savings by utilizing our Decision Management suite $6.05 million Scenario 2. Identifying Fraud Among Collection Cases First-party fraud cases usually wind up in collections as unpaid debts, and may not be recognized initially as fraud. In this example, we looked at the benefits of sharing data between fraud and collections and recovery applications, specifically automating fraud case creation from collections and recovery and common case management from fraud to collections and recovery. In the current environment, creating potential fraud cases for review from collection data requires either manual intervention or custom integration. Similarly, cases or customers identified as fraud require manual updating in the collections system or custom integration. In a Connected Decisions approach, collections and fraud share common data that is critical for both areas. This data can be used both to improve fraud analytic models and to drive collection strategies, making the entire operation more efficient while reducing losses. Common case management will allow collections departments to systematically create potential fraud cases for immediate evaluation and action by fraud analysts, which will in turn drive the appropriate collection workflows. page 8

9 Advanced analytics, rules and robust case handling capabilities combined with cooperation between fraud and collections departments are the keys to early detection of threats that may otherwise be invisible until it s too late to prevent large losses. In addition, the ability to identify fraudulent accounts before they are written off as bad debt provides operational efficiencies in the collections and recovery process. Institutions that integrate data between fraud and collections and recovery functions stand to realize: Reduced losses on cards and lines of credit through early detection and suspension of spending. Reduced losses on secured loans through early detection and recovery of collateral. Reduced collection costs through avoidance of unproductive collection activity. Figure 4: Automated Fraud Case Creation in Falcon from FICO Debt Manager TM Collections System COLLECTIONS AND RECOVERY FRAUD Is account First Payment Default (FPD)? Is profile initiated? NO Initiate and update profile with data and score NO # Call Attempts >X Update profile with data and score Has contact been made via phone? NO Store data into database Queue Collection Case for Call Has Mail been Returned? Collections rule (based on score or hotlist) fires. Generates case. Model scores high based on collections score and/or data. Generates case. Fraud score or other rule generates case. Collections data supplements investigation. Route Collection Case to Skip Trace Confirmed Fraud? Updating Collections with Fraud Analysis Results Case Generates Fraud Analyst Investigates and takes appropriate actions/disposition Confirmed first-party fraud abuse. End Case. Confirmed Non Fraud. End Case Suspect Fraud Case still open Confirmed first-party fraud abuse. Move to Collections Fraud Process Confirmed Non Fraud. Continue Skip Trace Suspect Fraud Continue Skip Trace Dispositions and Actions stored for future risk segmentation and fraud modeling This diagram illustrates how the collections and recovery and fraud functions can exchange data to identify fraud cases in the collections and recovery system and initiate appropriate actions. The issuer will be better able to determine which uncollected debts are most likely first-party fraud cases, and can contain losses by freezing card usage or cutting off access to credit. As a result, collection and recovery efforts shift more quickly to the fraud protocol. page 9

10 Financial Benefits The chart below shows a sample ROI calculation for a bank with 2 million accounts. Based on an estimated first-party fraud loss reduction of 10%, the savings from integrating originations data and fraud analytics are projected at more than $3 million. Institution Profile Portfolio Size in Accounts 2,000,000 Average Balance Active Accounts $2,000 Portfolio Size Active Accounts 1,600,000 Portfolio Value Active Accounts $3,200,000, Month Recovery Rate 12% Baseline Annual Loss $145,000,000 First-Party Fraud Loss $30,000,000 Cost of Collections /Account Cycle 2 4 $33 Value Reduced First-Party Fraud Losses (Identification & Treatment) Reduced Cost of Collections Reduced Implementation Costs First Year Total Savings Estimated Benefits from Interoperable Collections and Fraud 10% reduction $3 million $40,000 Reduced Cost of Collections 1,200 Fewer Charge-Off $33/Account $50,000 savings by utilizing our Decision Management suite $3.1 million Scenario 3. Coordinating Treatment from Customer Management to Collections Customer management and collections systems work best when they work together. In order to do this, integration work is required, which is often time-consuming and costly to perform. Frequently, clients decide to cut corners by including only the most obvious data elements. The net result is an implementation that misses out on key elements that drive value. Passing detailed data between customer management and collections systems greatly enhances the segmentation and decision capabilities. Integration will include those pieces of data that will help lead to reduced charge-off losses and reduced attrition. FICO is in the process of updating the bi-directional interface between our FICO TRIAD adaptive control system and FICO Debt Manager solution for collections and recovery, so that the two systems will act in concert. For example, using Debt Manager, a collector will accept a promise to pay from a customer. With the integrated system, TRIAD will be aware of this promise and therefore page 10

11 will not recommend inappropriate actions, either on the downside (such as sending additional collections letters) or on the upside (such as authorizing overlimit transactions). In the integrated solution, TRIAD adaptive control system will perform the segmentation that drives appropriate accounts into collections while Debt Manager will manage the day-to-day operations on those accounts. Debt Manager will keep TRIAD informed of operational activities that may lead to changes in recommended actions, and the two systems together will feed data into the reporting subsystem that will keep both portfolio and collections managers informed about the interaction between the two systems. Main Customer Management benefits: Allows identification of operational negation by ensuring consistency between the intended strategy and operational actions. Permits assessment of the cost of collection relative to amounts collected, allowing strategy improvements to be made. Allows identification of productive actions being taken in the collections system which are not part of strategies, so that strategies can be improved. Leverages recent customer contact insights for more precise strategy determination Increases precision of treatment determination, by using analytic insights and results of champion/challenger test outcomes. Main Collections and Recovery benefits: Increases collector efficiency by queuing only those accounts that need to be worked. Reduces losses through more targeted actions, improved segmentation and decisions. Helps ensure consistency between strategy as defined and operational execution. Allows simplification of how operational process is defined within the collections system. page 11

12 Figure 5: Connecting FICO TRIAD Adaptive Control System and FICO Debt Manager TM Solutions Client Bill/ Post Process ACCOUNT MANAGEMENT Client Billing System Client Masterfile COLLECTIONS AND RECOVERY TRIAD processes the data sent to it from the client s system and creates a file known as the TRIAD instruction file. That file is processed by Debt Manager updating a number of Debt Manager fields which are used by core Debt Manager processes such as Routers and Multiple Account Rerouting (MARR) to progress accounts through strategies and workflows. TRIAD Driver To Debt Manager (Actions from TRIAD) TRANSFER Load TRIAD Data Debt Manager database TRIAD Linkage TRIAD 200C (nightly bill/post called module) TRIAD Report Record TRIAD reporting process (several separate items including tally, file transfer and extract/transform/load DB) TRIAD Reporting Database (part of common data model) Debt Manager stored data for TRIAD Debt Manager creates output in a file that is then sent to TRIAD for nightly processing. The file contains manual handling status which is used in TRIAD triggering and segmentation to keep TRIAD from processing accounts in the middle of important collections actions (such as promise to pay in effect). Separate batch jobs run outside the nightly billing and posting routine TRANSFER Reports (seen through reporting tool in UI) TRIAD and Debt Manager actions and costs will be contained in reporting database so managers can see the interaction of the two systems Reports (seen through reporting tool in UI) Debt Manager Feedback process Write TRIAD data to file To TRIAD (indicator of Debt Manager status) Same database as above. Shown here for reporting purposes. Action/Result Tracking Cost of Collection Interaction with collectors Debt Manager Strategy Execution Case Management Debt Manager database (part of common data model) This diagram illustrates how the collections and recovery and customer management functions can exchange data. FICO TRIAD recognizes an account is delinquent and determines the appropriate treatment; those accounts identified with higher risk are sent to FICO Debt Manager for customer contact. Activity about the contact is captured in Debt Manager and passed back to TRIAD in order to determine the next steps. These next steps could include continuing on with the previously determined treatment or a new treatment based on the activity. TRIAD and Debt Manager actions and costs will be captured in a common reporting database, giving collections and risk managers insight into decisions made on accounts by the two systems. page 12

13 Financial Benefits The charts below estimate the benefits of integrating the TRIAD system and the Debt Manager solution, for a client with 2 million accounts. Based on this profile, the first year benefits would be an additional $1.6 million on top of the $7.1 million in reduced charge-offs. Institution Profile Portfolio Size in Accounts 2,000,000 Average Balance Active Accounts $2,000 Portfolio Size Active Accounts 1,600,000 Portfolio Value Active Accounts $3,200,000, Month Recovery Rate 12% Baseline Annual Loss $145,000,000 Attrition Rate 8% Revenue per Active Account $50 Value FICO Debt Manager TM Only FICO TRIAD Adaptive Control System Only Interoperable Debt Manager and TRIAD Potential Benefit of Total Debt Manager & TRIAD Solution* Reduced 5% reduction in 2% reduction in.5% additional reduction Charge-off Charge-offs $7.1 million Charge-offs $2.9 million for both Debt Manager $8.7 million Losses and TRIAD $1.56 million Reduced Implementation costs Implementation costs $45k savings by Implementation between and Collections between Account utilizing our Decision $45k Costs and Account Management Management and any Management suite Solution $90k Collections Solution $90k Reduced NA 5% reduction in 1% additional reduction $384k Attrition attrition $320k in attrition $64k First Year Total $7.1 million $3.1 million $1.6 million $9.1 million* Savings * Potential Benefit of Total Debt Manager and TRIAD Solution represents the minimum amount of total benefit gained by implementing an interoperable Debt Manager and TRIAD system. The $8.7 million total for reduced charge-off losses is based on the $7.1 million gained via Debt Manager installation plus the $1.56 million gained in additional reduction in charge-offs as a result of the interoperable system. Benefits may be even greater in this aspect, as suggested by the $2.9 million in savings from the TRIAD-only solution. However, since there is some overlap in benefits gained as a result of each individual system, it is incorrect to assume that total benefits are the sum of the Debt Manager-only, TRIAD-only, and Interoperable Debt Manager and TRIAD amounts. As shown, the client would receive value from each individual product, but the integration of the two products yields even greater value. For example, clients implementing Debt Manager frequently reduce their charge-offs by 5%, driven mainly by more efficient and timely collections activity and management of their collections queues. By the same token, clients implementing TRIAD frequently reduce their charge-offs by 2%, primarily by improved segmentation targeting high-risk customers for early collections treatment. By integrating the two products, clients could gain an additional half a percent reduction in charge-offs, since segmentation achieved within TRIAD will be improved through the knowledge of Debt Manager s operational actions that are captured and passed into TRIAD. page 13

14 Reduced implementation costs of the integrated solution come as the result of the Decision Management Suite s common infrastructure. Similar to the improvement in charge-off losses, reduced attrition via the integrated solution is achieved by additional information passed by Debt Manager into TRIAD enabling better identification of low-risk customers. Realizing the Vision FICO s Decision Management suite strategy leverages decades of intellectual property and has been validated with many of our clients. These capabilities are already being recognized in the marketplace as the next frontier to improving business results. The concept of Connected Decisions has been rigorously examined and found to deliver measurable ROI in a number of areas. Because the architecture is flexible, both FICO and its clients can add new Connected Decisions at any time. And, since the Decision Management suite can be deployed one application at a time, benefits compound with each additional product. Development of the Decision Management suite has been carefully designed and the entire blueprint has been defined. The products are road-mapped for sequential release, with many components already in place. As each product is deployed for a client, it will plug into the Decision Management suite, adding value provided by Connected Decisions and efficiencies of operation. The applications that support the examples are targeted for release beginning in the spring of 2009 and running through the summer of To learn more about FICO s Decision Management suite and opportunities for Connected Decisions, contact us at or info@fico.com. The Insights white paper series provides briefings on research findings and product development directions from FICO. To subscribe, go to Product roadmaps and similar marketing materials should be considered forward looking and subject to future change at FICO s discretion. Future functionality, features or enhancements as shown are FICO s current projections of the product direction, but are not specific commitments or obligations. For more information US toll-free International web (0) info@fico.com Fair Isaac, FICO, Connected Decisions, Blaze Advisor, Falcon, TRIAD, Debt Manager and Make every decision count are trademarks or registered trademarks of Fair Isaac Corporation in the United States and in other countries. Other product and company names herein may be trademarks of their respective owners Fair Isaac Corporation. All rights reserved. 2504WP 05/09 PDF