How Five Financial Services Organizations Transform Decisions with FICO Optimization

© 2016 Fair Isaac Corporation. All rights reserved. 1

OPTIMIZATIONBeyond the Software

The big challenge for companies today is to make the right decisions at the right time — to stay competitive and profitable. Historically, organizations have made decisions by looking into the past to understand what happened and why. In turn, companies started to create predictions, which helped measure future outcomes. In the past few years, as the amount of available data has increased, companies have moved toward prescriptive analytics that assess the different outcomes of potential decisions and identify the best one for handling a future scenario. As companies progress their use of analytics, they derive exponentially more value.

Consumer Loan Optimization: Česká Spořitelna, the largest

bank in the Czech Republic, increased portfolio profit by 26% and increased new sales by 29% by optimizing the origination of consumer loans.

Credit Line Optimization: A large North America bank optimally

balanced profit and risk with credit line increases, which resulted in growing balances by 9% and reducing the loss rate by 9%.

Collections and Recoveries Optimization: Canadian Tire Bank

applied optimization to collections and recoveries, which resulted in collecting $31 more for every $1 spent on collections activity.

Credit Authorization Optimization: A large Australian

bank implemented transaction-level optimization for authorizations, which resulted in an increase of $111 million in approved transactions and an increase of $6 million in annual revenue.

Customer-Level Originations Optimization: A large South

America bank developed a customer-level optimization solution across a package of lending products, generating a 6:1 ROI in the first six months.

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

Evolution of Decision-Making Using Analytics

For over 15 years, FICO has been helping clients successfully apply prescriptive analytics to improve decisions. This case study compilation shows how five financial services companies have worked with FICO to apply optimization to improve their business.

How Five Financial Services Companies Are Using Optimization to Change the Way Decisions Are Made



Maximizing Profitability with

Optimized Credit Decisions

Client: Česká Spořitelna Bank

Type of Optimization: Consumer Loan Origination

Challenge: Maximize profitability by increasing uptake on consumer loans, without increasing risk.

Solution: FICO® Decision Optimizer, FICO® Custom Decision Optimization, FICO® Xpress Optimization Suite, FICO® Optimization Modeler

Results: Česká has seen across-the-board improvements in consumer loan amounts, interest rates and application approvals. In addition, significant revenue increases have been achieved:• 26% increase in portfolio profit amounting to $16 million per year • 29% increase in new sales amounting to $41 million the first year

Česká Spořitelna, the largest bank in the Czech Republic, wanted to combat aggressive pricing by competitors without sacrificing profitability. By applying FICO Optimization Solutions across the portfolio, the bank is able to analyze a massive amount of data to arrive at the best price and credit limit for each individual borrower, based on their risk profile, loan appetite, price sensitivity and personal wealth.

After surpassing expectations with the first optimization solution, Česká applied similar solutions to other parts of the portfolio. And as the Česká team became more proficient with the optimization software, they gradually took on more ownership of designing the solutions.

With three successful optimization projects up and running, Česká has achieved an increase of over $50 million in revenue. Along with increasing new sales and the profitability of the existing portfolios, Česká has increased loan amounts, approval rates and acceptance rates.

Thanks to these extremely successful results, Česká Spořitelna has now begun using even more advanced analytical procedures involving real-time optimization in order to react to increasing demand for debt consolidation loans.

Powerful Tools Come with Great Responsibility Prescriptive analytics can lead to extremely powerful and accurate predictions, helping to understand the impact of future decisions and adjust

actual decisions based on that outcome. It can drastically improve the accuracy of decision-making, particularly when married with powerful optimization tools.

Working with a trusted partner such as FICO can help manage and mitigate the

risks that come with using powerful and complex software. Having developed hundreds of optimizations solutions across many industries, FICO is adept at identifying issues and helping to ensure clients create robust solutions.



Balancing Profit and Risk with

Credit Line Increases

Client: Large North America Bank

Type of Optimization: Credit Line Increase and Cross-Sell Offers

Challenge: Optimize the credit line management platform in order to drive more profit organically and limit the need for management intervention.

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

Results: Increased credit line utilization and reduced losses via optimization:• Response Rate +2%• Balances +9%• Loss Rate -9%

This large North America bank initiated its use of optimization with a credit line project. The bank manages credit lines for several million clients and wanted to find a better balance between increasing profits and minimizing risk.

The team partnered closely with FICO experts to develop a suite of action-effect models, leveraging performance data from its current strategy. By fitting these models into an optimization framework in FICO Decision Optimizer, the bank was able to simulate various optimal scenarios in order to explore new segments and ultimately deploy a stronger strategy that both increased credit line utilization and reduced losses.

After seeing significant value from the credit line optimization project, the bank asked FICO to develop optimal cross-sell offers for pre-approved loans and credit cards.

The bank had been using a rule-driven approach, but wanted to use optimization so it could effectively manage competing objectives between Marketing and Risk.

FICO created a close collaboration between the teams to fully understand the profit goals and the risk constraints. The team developed an optimization solution using FICO Decision Optimizer that relies on a suite of predictive models for response, revenue and risk.

Key Requirement: Quality and Breadth of Data At the core of every prescriptive analytics solution is data. The old adage of “garbage in, garbage out” has never been more relevant. To create robust prescriptive analytic models, the data

should be clean and should reflect the outcomes from the different actions and populations being considered. In addition, the data should account for any bias that might be present from previous actions.

FICO has developed a range of modeling techniques for developing predictive

and prescriptive analytics, such as action-effect models, that are often key to the success of optimization solutions. Whether the dataset is sparse or complete, FICO can extract the most value from it, using open and collaborative development steps.



Key Requirement: Proven Development Methodology To succeed with mathematical optimization, you definitely need powerful software. But prescriptive analytics is about much more than the technology. Powerful tools in the wrong

hands can do more harm than good. It is vital to understand how to construct the problem and to validate the results very carefully.

FICO’s methodologies, software and best practices have been developed and refined through years of research and

across hundreds of client engagements, across many industries. This breadth of experience means FICO offers organizations the highest confidence in achieving success when applying optimization and prescriptive analytics to improve business-critical decisions.

Maximizing Returns Across

the Customer Lifecycle

Client: Canadian Tire Bank

Type of Optimization: Credit Line Increase, Collections and Recoveries

Challenge: Improve business performance across a range of credit decision areas — from limit increase to collections and recoveries

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

Results: Canadian Tire has achieved significant results with each optimization solution implementation:

Credit Line Increase: • $8 per account increase in profit

Collections: • 2% improvement in receivables cure rate• $31 more collected per dollar spent on collections activity

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.

After achieving such significant results, 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.

It then undertook projects in late stage collections, including complex areas such as optimizing settlement offers, in order to reduce the time and effort spent on future collections and to reduce agency recovery fees.

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



Transaction-Level Optimization

in Authorizations

Client: Large Australia Bank

Type of Optimization: Credit Transaction Authorization

Challenge: The bank wanted to increase revenue by finding a better strategy for referred credit card transaction authorizations.

Solution: FICO® Custom Decision Optimization

Results: After developing a transaction-level decision strategy for overlimit and one-cycle delinquent accounts, the bank has experienced significant financial benefits without increasing risk rates:• $111 million increase in the incremental value of approved transactions • $6 million increase in annual revenue • Reduction in bad debt expenses

After a successful credit line optimization implementation, this large Australia bank turned its attention to optimizing credit authorizations. The bank felt there was a good chance its existing authorization strategy could be improved. It just needed to figure out how. That’s where FICO came in. With a focus on collaboration and transparency, the bank provided as much data and business knowledge as possible and then FICO applied the analytic and optimization knowledge. It was determined that revenue could be increased without a significant increase in risk by better targeting transaction approvals on overlimit and one-cycle delinquent accounts.

The bank was making authorization decisions for those accounts based on a monthly behavior score generated internally. FICO removed that month-long delay to provide real-time scores that enabled more predictive decisions. The solution takes data from all available sources and brings them into one action-effect model. A business analyst can then use simulation and scenario planning to adjust constraints in order to reach its end-goals of revenue gains versus risk.

This transaction-level optimization solution led to an increase of $111 million in the incremental value of approved transactions and an increase of $6 million in annualized revenue, all without a significant uptick in delinquency.

Key Requirement: Ongoing Expert SupportWhether a company wants to solve a single business problem or broadly apply optimization technology and methodology across the whole business, it is essential to have access

to an experienced and knowledgeable support team that can provide guidance about the business problem and clarify complex technical issues.

FICO prides itself in providing ongoing expert support to its clients, whether by providing a managed service, occasional

training or detailed solution design guidance. FICO consultants use the same tools and techniques as our clients, and our product development teams boast some of the best mathematical modeling experts available.



Optimizing Customer-Level

Originations

Client: Large South America Bank

Type of Optimization: Customer-Level Originations

Challenge: Optimally set customer-level exposure at originations across a portfolio of lending products.

Solution: FICO® Decision Optimizer, FICO® Custom Decision Optimization, FICO® Optimization Modeler

Results: In the first year, the bank achieved significant improvements:• $8.60 decrease in losses per customer on the current account• $44.20 increase in profits per customer on standard card/loan products• $120.79 increase in profits per customer on the elite card products

This large retail bank in South America wanted to improve the overall performance of its business by optimizing the acquisition of new customers through a set of packaged products, including standard and elite credit card offers as well as pre-approved consumer loans.

The bank had been managing originations by using predictive models to assess risk and by setting account limits based on a consumer’s monthly income. With a goal of evolving to profit-focused decisions, the bank partnered with FICO to optimize an originations strategy.

The problem proved to be challenging, with each account having varying exposure profiles, profit calculations, goals and constraints. On top of that, there were over 10,000 potential decision options for each customer.

FICO developed a separate optimization solution for each product, which feeds into one master solution that provides customer-level optimized decisions across all products.

The customer-level optimization solution has led to significant increases in income and reductions in losses. Six months post-implementation, the bank achieved a 6:1 return on investment. Because of the success of this optimization, the bank is extending its use of optimization solutions and is implementing additional projects in other regions.

Key Requirement: Collaboration From our vast experience with implementing optimization solutions, we have learned the importance of collaborating with our clients and giving

our clients a completely open and accessible view of the logic and methodology built into the solutions.

FICO understands that developing such a solution cannot be a one-way conversation. Educating our clients about how we’re building the predictive

and prescriptive models goes a long way in achieving the best results. Our philosophy is that if we show you what we’re doing, then you understand the models better and can provide better information for validating and enhancing the solution.

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The combination of FICO’s powerful software, domain expertise, extensive implementation experience and transparent methodology has established us as a leader in developing optimization solutions. We offer a complete range of services and software for all users, making optimization accessible to everyone, everywhere.

To learn more about how FICO Optimization can

help you improve your business decisions,

go to www.fico.com/optimization.

Initial FICO-Led Development Project

• First Decision Optimization project• Introduction to FICO development methodologies• Project deliverables: ° Optimized Decision Strategy

° Training

FICO Optimization Solution Adoption

• FICO developed decision impact model – embedded in software solution• Project deliverables: ° Optimized Decision Strategy

° FICO Optimization solution software

° Methodology & Software Training

Collaborative Development

• Joint development between FICO and Client on a new decision area• Knowledge transfer on decision impact modeling methodology• Project deliverables: ° Optimized Decision Strategy

° FICO Optimization Solution software

° Methodology & Software Training

FullAdoption

• Full FICO Methodology adoption• FICO Software used across multiple decision areas• Client-led development of multiple decision impact model and decision strategies• Ongoing FICO training & support

Within project used to: ° Review model design

° Review scenario analysis

Ongoing use to: ° Run new scenarios on new data

° Develop new decision strategies

° Manage and update decision impact model

Ongoing use to: ° Design, develop and manage decision impact models

° Run many new scenarios

° Iteratively develop many new decision strategies

Full software adoption: ° Design, develop and manage many different decision impact models

° Advanced scenario analysis & stress testing

° Integration with other systems

Client software usage Increasing knowledge transfer & software adoption

Typical Roadmap of How Companies Leverage Optimization Over Time

Most companies begin using optimization by relying on FICO’s expertise in developing solutions. Over time, as the client team becomes more familiar with the process, it jointly develops solutions with FICO, with some companies then establishing in-house teams to develop their own solutions. Some more advanced clients jump straight to full adoption, although we still recommend taking time to learn the FICO methodologies.

http://www.fico.com/optimization

How Five Financial Services Organizations Transform Decisions with FICO Optimization

Data & Analytics

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