FICO Opens Up the Complex World of Optimization to Business Analysts

© 2016 Fair Isaac Corporation. All rights reserved. 1

EXECUTIVE BRIEF

With the Right Methodology, Training and Support, More Organizations Are Getting Business Analysts to Run Their Optimization Projects

The Benefits of Putting Optimization into Business Analysts’ HandsFICO clients often experience profit improvements of 5% to 30% from applying optimization. By following FICO’s proven methodology, organizations can increase the number of optimization projects they execute successfully, resulting in:

• Greater profitability through sharper, individualized customer decisions

• Sound, effective, repeatable optimization practices from business analysts

• Faster development and deployment of more effective decision strategies

• An ongoing proactive program of decision strategy improvements

Many organizations consider optimization only for their largest or most challenging business problems, often utilizing a small number of Operations Research professionals. But in our age of Big Data, market globalization and increased competition, many organizations are successfully making the case that optimization can be applied to a wider variety of business and operational decisions, and be developed by a new group of users — the organization’s business analysts.

With a proven track record of results demonstrating that organizations can increase profitability with business analysts applying optimization to many types of business problems, FICO’s proven development methodology is giving organizations the confidence to extend optimization practices across their enterprises.

Believing in Business Analysts’ Potential to Develop Optimization SkillsEvery organization wants its employees to learn new skills to improve output. And from the employee’s perspective, learning a new, valuable skill ups their value to the organization. So, as organizations develop their use of analytic technology, business analysts — who currently typically have experience in developing predictive models and rules-based decision strategies — have started to move towards developing optimization solutions.

The most common impediments to adoption are the complexity of optimization, and the potentially disastrous downside of inexperienced business analysts applying inadequate development approaches.

EXECUTIVE BRIEFFICO Opens Up the Complex World of Optimization to Business Analysts


Optimization is one of the most powerful analytic technologies, and like most powerful things, just as it possesses tremendous potential to add value to an organization, used improperly it can also cause damage. Success depends entirely on how well the user understands the business problem, and how to properly apply optimization to solve the problem. That level of understanding is not always straightforward.

This can often be a significant barrier, one that organizations must consider if they want to use their business analysts for optimization projects. However, to address that challenge, for over 15 years FICO has provided organizations with configurable optimization frameworks and Decision Impact Models that are designed to be developed by business analysts.

Initially, these were developed to be used by FICO’s own business analysts to deliver optimization engagements with its clients. These approaches evolved over the years, and increasingly FICO found that getting the client more closely involved in the development enhanced projects, yielding fewer errors and improved results. In turn, this increased exposure led to clients wanting to adopt the development methodology through partnership projects, methodology transfer training and software adoption, empowering them to create their own future decision optimization projects.

In FICO’s engagements with its clients, using optimization can yield profit increases of 5% to 30% or more compared to the business-as-usual approach. Opening up the use of optimization practices to business analysts, using a proven methodology, has allowed some clients to significantly

broaden their application of optimization, and in turn increase profitability while managing potential risks.

A Sound Approach for Training Business AnalystsFICO advocates that organizations not only follow a proven development methodology to learn the key fundamentals of optimization — such as those FICO has designed, detailed later in this paper — but also that they receive their optimization training within the scope of a real business project.

This ensures the training is undertaken as part of a project that:

• Works within the context of and addresses a real business problem

• Has the potential to generate business value

• Can easily provide business analysts with exposure to all key project elements: design, development, software, analysis and decision strategy output.

This also provides the platform for creating template design documents, reports and software projects that serve as a guide for success in independently executing their own future optimization projects.

Specifically, FICO’s business analyst approach focuses on methodologies and software that support the point-and-click design and development of Decision Impact Models. These combine analytic models and profit calculation components that are already familiar to business analysts, and are used to drive the decision simulation and optimization process. They calculate outcomes for each of the different decisions that are being considered, and are used within a standard optimization model framework. The use of standard frameworks helps manage complexity, making it easier for the business analyst to focus more on solving the business problem.

Moving to Optimization Escalates Analytic Value

From across the spectrum of analytics, applying optimization to more projects yields greater value to organizations. While the complexity of optimization can make it more difficult to execute, FICO’s proven optimization development methodology enables an organization’s business analysts to learn and safely apply optimization to projects.

Information

Optimization

Hindsight

Insight

Foresight

DIFFICULTY

VALU

E

Analytic Value Escalator How can we make it happen?

Prescriptive Analytics

What happened?

Descriptive Analytics

Why did it happen?

Diagnostic Analytics

What will happen?

Predictive Analytics



Where the FICO Approach Takes Business AnalystsBusiness analysts who follow the FICO® Decision Optimization development methodology often learn that it differs from their current practice of developing decision strategies in three main ways:

1. Focus First on the Potential Decisions for Each Customer – Many current approaches focus first on segmenting customers and then assigning decisions to each segment. Unfortunately, performance bias in the development data, caused by previously applied decisions, often results in a less than optimal segmentation, while also making it difficult to assess the impact of undertaking alternative decisions. FICO’s methodology focuses first on identifying the potential decisions that can be made. Then we model the impact of each of those decisions on each customer, across all key profit drivers, and use this to both simulate historical decisions and support the

optimization of decisions against objectives, goals and constraints.

2. Assess the Impact of Different Decisions – FICO focuses on accurately measuring the “Action-Effect” — how each customer’s performance will change if different decisions are made. FICO has developed a range of data-guided and data-driven predictive and prescriptive modeling techniques to support this. This focus helps identify and overcome any performance bias in the data, and helps provide a more accurate assessment of how changes in decisions will impact outcomes. Action-Effect modeling is essential to understanding the impact of changing decisions.

3. Undertake Rapid Scenario Analysis – FICO’s Decision Optimization methodology and accompanying software allows you to quickly assess many different scenarios and solutions, in a range of market and economic conditions,

so you can identify the one that best meets your goals and constraints. This provides the analyst great insight about the impact of different decisions. It doesn’t dispense with the need for ongoing champion/challenger or A/B testing, essential for accurate, comparative performance monitoring, as well as providing broad data for future model developments. But, it can help speed up the roll-out of challenger sets of decisions, as you can measure progress against expected results.

FICO’s Decision Optimization methodology uses proven decision analysis techniques and provides a lot more accuracy over typical approaches, as it focuses in on the element that has the biggest effect—the decision itself and how it impacts each customer. It provides a method for measuring the impact of different decisions, both to simulate historical decisions and support the optimization of future decisions against business objectives, goals and constraints.

Action-Effect Models Evaluate a Customer’s Reactions to Different Potential Actions

In this example, the different potential actions impact the customer’s probability to take up the loan offered, and the estimated loss that may result. These, plus other drivers, impact the overall estimated profit of each offer.

680720$5,250$50,000132 months

CUSTOMER REACTION

P (Take Up)

E (Loss)

E (Profit)

75%

$440$1,350

ACTIONOFFER 1

P (Take Up)

E (Loss)

E (Profit)

65%

$450$1,250

P (Take Up)

E (Loss)

E (Profit)

67%

$550$1,150

Risk ScoreRevenue Score CB BalancesIncomeTime on FileSegment B

Loan amountPrice

$15,000

5.9%

Loan amountPrice

$15,000

6.9%

Loan amountPrice

$20,000

6.9%

OFFER 2

OFFER 3



The FICO® Decision Optimization Methodology: The Key to Successful Decision OptimizationFICO has seen many cases where organizations have underestimated the requisite knowledge involved in working with optimization. Approached properly and learned correctly, optimization can provide ongoing improvements in business performance, and equip organizations with an unprecedented level of insight and control. That’s the objective of FICO’s methodology.

When undertaking client projects, FICO’s standard partnership development approach means that, at a minimum, FICO works closely with every client to design and develop a Decision Impact Model that both fits the client’s business problem and will robustly support the optimization process.

Additional methodology transfer and software training options provide the client team with a more comprehensive insight into every step of FICO’s methodology, as well as providing the documentation and project templates to support their own internal developments. Having evolved over the last 15 years, the core steps and components of FICO’s methodology (shown in the graphic above) have been proven to address the challenges of applying decision optimization to a wide variety of business problems.

The FICO methodology is broken down into four main phases:

Phase 1 – Project Design

Define Inputs

Any decision optimization project must begin with defining the current decision situation, including a statement of the project goals as well

as any non-negotiable requirements. In this initial stage, FICO helps clients explore potential conflicts and trade-offs. This involves listing current policies and constraints, generating creative decision alternatives, and identifying uncertainties.

The integrity, strength and value of data are vital in any analytic model development, and particularly in optimization. That’s why the methodology involves much more than just data acquisition, but also many procedures in data searching, testing and evaluation. The steps in this stage of the methodology include identifying existing data and data sources, as well as identifying gaps in existing data and

evaluating new data inputs. This step may involve the design of experiments to ensure collection of the best data.

Once data is acquired, the FICO methodology takes steps to clean and filter all data, correct errors and make a final determination of what data is reliable, useful and correct. Other inputs such as assumptions, which are constant values that are input into the Decision Impact Model, are also identified.

Design Decision Impact Model

A Decision Impact Model is a framework of analytic models and calculations used to understand the interactions between criteria used in a decision —

A Complete Business Cycle Enables Optimized Decisions

FICO ’s four-phase development methodology supports the entire lifecycle of designing, developing, executing and deploying a decision optimization solution.

Configure FICO Optimization Software

Design DecisionImpact Model

Feedback Loop & Accelerated Learning

Comparative Scenario

Analysis & Drill Down Reporting

Define InputsCustomer & Bureau Data Segmentations & Scores Pricing/Profit ModelsProduct Metrics

Develop Decision Impact Model(and Action Effect Models)Establish mathematical relationships between Actions, Reactions & Profitability

Simulation & OptimizationIdentify best strategy scenarios subject to multiple business goals, constraints & forecasts

Refinement & DeploymentEngineer final strategy & deploy challengers as Decision Trees or Business Rules in Production Systems

PHASE 1 PHASE 2

PHASE 3PHASE 4



defining the potential decision options, inputs, assumptions and outcomes, as well as the objective(s) in making that decision. If a predictive model measures the probability of a single outcome, then a Decision Impact Model can be considered to measure the probable outcomes of multiple potential decisions, so you can choose the best decision to meet your goals.

Designing a Decision Impact Model is essentially where FICO identifies all of the elements influencing a decision. Clients often gain a great deal of clarity about what drivers are the key to success. In addition, it often brings different business areas together to focus on a common goal.

The design process helps to break down and explain complexities, assisting analysts in defining and understanding the key criteria of decisions — identifying key inputs, outputs and relationships,

usually with a primary focus on profit — which in turn guides the model development. Influence diagrams are often used to visualize the Decision Impact Model design.

Phase 2 - Project Development

Develop the Decision Impact Model

Once the data generation has been finalized, it is then visualized to attain a better understanding of it, using statistical and graphical data summaries. FICO can help businesses aggregate the data to smooth out erratic variations, but not to the point where important distinctions are lost. Then the data is modeled by important relationships.

Predictive models are developed to yield scores and probabilities. Some of these will be “Action-Effect” models, which are required for assessing the effects of different potential decisions on key value-drivers. The FICO team will review

the developed models with the client team and discuss how analysts can use best practice methods to create unique custom-fitted models for each project.

All the different parts of the Decision Impact Model design — the data inputs, assumptions, potential decisions, predictive models, Action-Effect models, outcomes, objectives and constraints — are then built out, specified, validated and reviewed.

Configure FICO Optimization Software

Once the Decision Impact Model design has been finalized, the business analysts pull together all necessary components and set them up in FICO® Decision Optimizer software. FICO shows teams how to combine all the models and calculations together, and how to allocate the roles they will play in the decision optimization process, including potential objectives, constraints, decision keys, stressors and uncertainty.

Influence Diagrams Are Used to Support the Design and Configuration of Decision Impact Models

Influence diagrams are visual metaphors that help users to understand how the inputs, decisions, predictions, outcomes, objectives and constraints interact within the Decision Impact Model.

INPUTSKnown information

used to make decisions

DECISIONSPossible actions

taken

PREDICTIONSUnknown customer reactions,

which drive objective

OUTCOMESKey metrics

OBJECTIVE & CONSTRAINTS

Primary & secondary goals

Data• Credit bureau scores• Predictive scores• Demographic data• Customer segments• Application data• Competitor Info

Assumptions• Costs of funds• Fees & charges• Market conditions

• Revenue• Loss• Costs• Capital

Action Effect ModelsResponseActivationEarly repaymentLoss/charge-off

Time to repaymentTime to charge-offCapital required

Example Decision Impact Model Influence Diagram - Consumer Loan Origination Decisions

Who to accept

Loan price

Loan amount/termProfit

Constraints



An important part of this stage is validating the Decision Impact Model to ensure that it accurately reflects the dynamics of the client portfolio, and how customers’ reactions to actions should impact profitability and other key metrics. The FICO team runs test scenarios through the Decision Impact Model to provide a common-sense check of the predictions.

Phase 3 – Simulation & Optimization Execution

Simulation & Optimization

Next is the critical step of creating and evaluating multiple simulation and optimization scenarios to find the “best” one. The FICO team creates multiple scenarios that explore different combinations of potential decisions, constraint thresholds, assumption values and uncertain parameters.

Simulation scenarios are run on the client’s current strategy (business-as-usual), so that performance benchmarks can be set across a range of metrics.

Then a range of new optimization scenarios are run to challenge and improve on these metrics to find the best decision strategy that adheres to the required constraints. These may include exploratory scenarios that look along a single constraint dimension to help analysts understand how profit is impacted by different constraint levels, or stress tests, which show how key metrics are impacted by changes in market conditions.

Comparative Scenario Analysis & Drill Down Reporting

The scenario output provides great insight into more profitable decisions and the impact of different business constraints. FICO shows client teams

how Efficient Frontier graphs are used to compare scenarios, identifying profit improvements where key business constraints are also met.

An extensive range of reports and analysis are often undertaken to help the analyst understand key scenario influences and differences. Swap-set reports are used to profile sub-populations with differing actions between the current strategy and the new optimized strategy, and to view differences between performances. Penetration reports help identify which segments of accounts are being targeted for different actions, and drill-down reports allow the analyst to profile key sub-populations and gain visibility into the targeting logic.

These comparative reports then provide the business case for deploying the identified optimized scenario as a challenger decision strategy.

Phase 4 – Deployment & Management

Refinement and Deployment

This step involves taking the chosen optimization scenario and converting it into a form ready for use in production. This may mean just passing account, customer or segment level data through the chosen scenario. Or, more often than not, it involves converting it into decision logic, in a decision tree format, ready for deployment into a decision engine, such as FICO® Blaze Advisor® decision rules management system, FICO® Origination Manager, or FICO® TRIAD® Customer Manager, so that it can be applied consistently upon production data on a regular basis.

FICO optimization technology provides a range of functionality to help the analyst build out a decision tree that represents the optimization scenario, including

being able to set tree constraints for use in the optimization process. This allows the analyst to quickly understand the performance impact of different sizes and shapes of trees so they can ensure the resulting tree adheres to cross-record consistency and eligibility constraints, and that it doesn’t jeopardize the effectiveness of the strategy.

Tree editing functionality is used to undertake final refinements to the decision tree to ensure that it can be seamlessly deployed into the production environment, using PMML or FICO’s own FSML formats.

The FICO team then provides instruction in deploying the optimal decision strategy into the decision management solution as a challenger strategy alongside the current champion. The team also shows how to measure and compare the results. Assuming the challenger outperforms the champion, after a period to confirm the performance is directionally in line with expectations, it can become the new champion.

The FICO team will show how to properly document the development project and track the ongoing performance of the solution. They will also instruct and assist in deploying the Decision Impact Model software project files into FICO® Decision Optimizer to create a pre-configured Optimization Solution that can be licensed and delivered to the client to support the ongoing management of the decision area.

Feedback Loop & Accelerated Learning

Clients have the option to make ongoing use of the FICO-developed pre-configured Optimization Solution. This may include running additional scenarios on new data, or updating the Decision



Impact Model based on the new performance data available from new or different decisions being made.

This completes the FICO methodology cycle. All learning and performance gained from the first development should then be used to inform and improve the second iteration. This leads directly to ongoing improvements in Decision Impact Model accuracy, resulting in better, more relevant decision strategies to meet future business needs. The use of more up-to-date input data also ensures that decision strategies can be updated to reflect the latest business goals and customer performance. Some clients also start to develop strategies based on future expected market

or business conditions, so that they can assemble a suite of strategies to proactively manage their decisions to fit future needs.

Clients can also obtain wider software licenses that allow them to develop and deploy their own decision optimization projects across a range of different decision areas. FICO has many clients who have gone down this road with great success.

Business Analyst Optimization Software: FICO® Decision OptimizerFICO® Decision Optimizer is part of FICO’s industry-leading suite of optimization software and solutions.

It provides support across the whole FICO Decision Optimization methodology, from design to deployment. Companies worldwide are successfully using FICO Decision Optimizer to improve their decision strategies using its advanced decision impact modeling, simulation and optimization functionality.

Built for the business analyst, it gives business experts the control to simulate and optimize a wide range of decision areas, and to inject their knowledge into the mathematical optimization process, without having to refer to expert operations research resources.

Graph CompleteDIM TransAuthsDIM

SAVE CANCEL

FICO® Decision Optimizer - Transaction AuthorizationHOME APP JOBS

Project Scenario 1

PROJECT - CORE Inputs Decisions Decision Impact Model Data Model Components Data Roles

LISA M HELP

DMN 1.0

Elements

Decision

Input Data

Knowledge Source

Knowledge Model

Name

TransAuthsDIM

Description

Delete this DRD

DRDAccounts DataPot Rev 1

Pot Rev 2

Pot Rev 3

Pot Rev

Assumptions Data

Score Expert

Score New

Score BEH

Metrics

Actions Data

ConstraintsBad RateInterest IncomeCost of FundsFees

Revenue

Loss

Profit

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Success Story: Canadian Tire Bank Challenge: Improve business performance in areas such as Credit Line Increase, and Collections and Recoveries

Solution: FICO® Decision Optimizer, FICO® Decision Optimization methodology

Canadian Tire Bank wanted to improve business performance across a range of decision areas. The first optimization solution for the bank was a set of iterative credit line increase projects. Within the first year, this led to $8 per account incremental profit improvements.

With that success, the bank adopted FICO’s Decision Optimization methodology and software and, working in partnership with FICO, turned their attention to early-stage collections. Within the first six months of implementation, Canadian Tire improved the receivables cure rate by 2% and collected $31 more for every $1 spent on collections activity.

The team has taken on progressively more ownership of developing the optimization solutions in-house. With this self-sufficiency, they have moved into new decision areas such as Initial Credit Line, Credit Transactions Authorizations, Late Stage Collections and Credit Pricing.

The FICO® Decision Optimizer graphical component – based development environment allows the business analyst to quickly and easily configure the Decision Impact Models used to drive the optimization process. Its extensive reporting and output capabilities then allow them to gain great insight into the impact of alternative simulation and optimization scenarios, utilizing different goals and constraints, while applying stress tests and allowing for uncertain events. It supports a range of options to allow new decision strategies to be easily deployed in production decision management systems.

Clients can license FICO Decision Optimizer both pre-configured to a specific decision area with a FICO-built Decision Impact Model, or as an un-configured software application that allows clients to configure their own Decision Impact Models from scratch. A range of basic to advanced hands-on training courses is available, supported by FICO experts.

For the more advanced business analyst, FICO Decision Optimizer can also provide a stepping stone to the FICO® Optimization Modeler software, which is designed for Operations Research Specialists to programmatically create highly customized and powerful Optimization Solutions.

At FICO we’ve been working in partnership with clients, creating

business analyst – focused FICO optimization solutions for over

15 years. If you’re interested in successfully applying

optimization, contact FICO for a free initial consultation.

FICO Opens Up the Complex World of Optimization to Business Analysts

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