Resources

IDC MarketScape: Worldwide Anti–Money Laundering Solutions in Financial Services 2018 Vendor Assessment

This IDC Financial Insights study presents a 2018 vendor assessment of worldwide anti–money laundering (AML) solution providers in financial services using the IDC MarketScape model. This research quantitatively and qualitatively assesses ...

IDC MarketScape: Worldwide Know-Your-Customer Solutions in Financial Services 2018 Vendor Assessment

This IDC study presents a 2018 vendor assessment of worldwide know-your-customer (KYC) technology providers using the IDC MarketScape model. This research quantitatively and qualitatively assesses multiple characteristics that help explain...

Optimizing Collections and Recovery: Finding Balance With Your Debt Recovery Strategies

This FICO-led session will discuss Trends and Challenges in Collections Management and solutions to address these challenges from Early Stage Collection to Late Stage Recoveries. We’ll discuss adaptation of analytics across the industry – ...

Introducing the FICO® Debt Manager™ FitAgent™ User Interface

Offering task-oriented workflows for contacting customers and collecting payments, FitAgent™ is the intuitive web interface added to the FICO® Debt Manager™ collection and recovery platform in mid-year 2017.

FitAgent was designed with one purpose in mind: increasing collector efficiency. How did we do this? By putting ourselves in the collectors’ seats as we visited clients and conducted extensive user research activities. We learned what information the collectors need and when, the steps they’re taking in the collection process and the actions they perform.

State of Maryland streamlines statewide collections with a human touch

The state is increasing revenue from collections, citizens have a better experience with the collections department, and staff members have more interesting and rewarding jobs.

SunTrust transforms origination process and improves customer experience

SunTrust customers have a user-friendly, efficient process throughout the loan application; the bank responds quickly due to improved workflow and automation; and new account bookings have increased 50%.

Trustmark improves the customer experience and employee morale

Collections agents are more efficient and productive because they have up-to-date customer information, as well as effective collection strategies and customers’ preferred contact methods. Employee training is now easier, and customer delinquencies are reduced.

National Australia Bank uses FICO solution to put customers first and improve collections results

Client: National Australia Bank (NAB) has 35,000 employees and ranks among the world’s top 25 banks in terms of market capitalization. Challenge: NAB wanted to change its approach to collections and identify the best communication metho...

Thames Water reduces bad debt by understanding customers better and tailoring communications

Client: Thames Water Utilities Limited is the largest water company in the UK. Challenge: Thames Water needed to improve collections processes and reduce bad debts by better understanding its customers. Solution: FICO® Debt Manager™ ...

Vanquis Bank gains agility, opening new credit possibilities with FICO® Origination Manager

Client: Vanquis Bank specializes in offering loans and credit cards to people with limited credit history who may have been turned down elsewhere. Challenge: The bank needed to modernize its customer acquisitions system from an aging an...

FICO® Predictive Models for Origination Frequently Asked Questions

With analytics, you can consider a wide range of risk and revenue factors to consistently make smarter origination decisions, reach high application processing speeds and improve operational efficiencies. FICO helps you attain the best predictive scores/models for your business needs — whether you are new to scoring or have an experienced in-house analytics team. We offer empirically derived custom models tailored to your portfolio, expert models that require no historical data and reduce time to market, and pooled models developed on data from several financial institutions. But what exactly are custom models, expert models and pooled models? How do they differ and what is the effort needed to put them into action?

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