Category Archives: FICO

FICO Score Planner: Helping People Meet Their FICO Score Goals

Functioning in the U.S. economy using cash only can be a challenge.  Simple daily transactions, such as making an online purchase, going out to eat, or even paying a bridge toll is a lot easier if you have a credit or debit card.

Most people know that having a higher credit score is a positive thing as it can help increase access to credit at more attractive rates.  Additionally, most people also understand that not paying your bills on time, carrying a high amount of credit debt, and opening up a lot of credit in a short period of time are behaviors that will likely have a negative impact on their credit scores.

What’s less intuitive is knowing what potential actions they could take to reach a target credit score goal by a target date. For example, if someone currently has a 695 FICO® Score 8 based on Experian data and want to increase that score to 725 in 6 months so they can apply for a new credit card, how would they know if that target score was even possible or what actions could be taken to potentially achieve it?

FICO® Score Planner is a new feature built by FICO scientists that enables an individual to set a target FICO® Score 8 goal and desired time duration to reach their goal.  These inputs along with an individual’s current FICO® Score 8 and credit report are analyzed by the FICO® Score Planner algorithm, which produces a set of potential actions consumers could take to help reach their target goal.  Consumers can then track their progress to their goal or modify their goals along their way.

Screen Shot 2018 07 17 at 1.42.01 PM FICO Score Planner: Helping People Meet Their FICO Score Goals

Ideal for people with an active credit profile, FICO® Score Planner helps take away some of the guess work many people face when trying to figure out potential actions they can take that may help to achieve their FICO Score goals.

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Credit Knowledge is Power

Screen Shot 2018 07 10 at 3.08.33 PM Credit Knowledge is Power

This is a guest post from Rourke O’Brien, Assistant Professor of Public Affairs at the University of Wisconsin-Madison

Does regular consumer access to their FICO® Score influence financial knowledge and behavior?

Professors Abigail Sussman, Tatiana Homonoff and I recently completed a multi-year research study with 400,000 Sallie Mae customers.  Using a randomized control trial research design, we studied whether student loan borrowers who check their credit scores regularly make better financial decisions and manage finances more responsibly. The answer? An emphatic YES.

Kelly Christiano, SVP at Sallie Mae and I had the opportunity to present the findings at this year’s FICO World. Sallie Mae was the first national private education lender to offer free access to quarterly FICO Scores through the FICO®Score Open Access program.

Our research found that after one year, student loan borrowers who logged on to view their FICO Score had fewer past due accounts and took steps to establish a credit history. These positive behaviors ultimately translated into higher FICO Scores for borrowers.

For students who want to improve financial health, it is important to be aware of the terms of opening new accounts (only open new lines of credit when needed) and to make sure that payments are on time. Moreover this research suggests that all consumers, not only student loan borrowers, should regularly check their FICO Score to be thoughtful and empowered about how their credit behavior impacts their long-term financial health.

You can also review the full research details here “Does Knowing Your FICO Score Change Financial Behavior? Evidence from a Field Experiment with Student Loan Borrowers

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Fraud Detection: Applying Behavioral Analytics

This is the second in my series on five keys to using AI and machine learning in fraud detection. Key 2 is behavioral analytics.

Behavioral analytics use machine learning to understand and anticipate behaviors at a granular level across each aspect of a transaction. The information is tracked in profiles that represent the behaviors of each individual, merchant, account and device. These profiles are updated with each transaction, in real time, in order to compute analytic characteristics that provide informed predictions of future behavior.

Profiles contain details of monetary and non-monetary transactions. Non-monetary may include a change of address, a request for a duplicate card or a recent password reset. Monetary transaction details support the development of patterns that may represent an individual’s typical spend velocity, the hours and days when someone tends to transact, and the time period between geographically disperse payment locations, to name a few examples. Profiles are very powerful as they supply an up- to-date view of activity used to avoid transaction abandonment caused by frustrating false positives.

A robust enterprise fraud solution combines a range of analytic models and profiles, which contain the details necessary to understand evolving transaction patterns in real time. A good example of this occurs in our FICO Falcon Fraud Manager, with its Cognitive Fraud Analytics.

Given the sophistication and speed of organized fraud rings, behavioral profiles must be updated with each transaction. This is a key component of helping financial institutions anticipate individual behaviors and execute fraud detection strategies, at scale, which distinguish both legitimate and illicit behavior changes. A sample of specific profile categories that are critical for effective fraud detection includes:

Behavioral analytics for fraud detection chart Fraud Detection: Applying Behavioral Analytics

Key 3 is distinguishing specialized from generic behavior analytics. Watch for that post, and follow me on Twitter @FraudBird.

For more information:

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Stay Safe Online with These 5 Tips (Video)

Stay Safe Online Tips Stay Safe Online with These 5 Tips (Video)

For many years, bank fraud teams have had to worry not only about tackling fraud but also about the impact that security and fraud prevention measures have on their customers. We just completed a survey to ask thousands of consumers in the UK and US exactly what they think about those security measures and fraud processes that are designed to help them stay safe online.

The short answer? They’re frustrated.

You probably knew that already, but the extent of the frustration is interesting:

  • 77% think that security measures are unnecessarily complicated
  • When opening a bank account, only 23% are prepared to wait for access for more than an hour
  • When opening an account online, if asked to take a phone call, post a document or visit a branch, 22% would give up altogether or take their business to another bank

You can read more of the results in this story in the Mirror.

Part of the answer to frustration is education. With that in mind, we made this short video, with quick tips on how to stay safe online.

Today I’m back to my day job, working with our banking customers. I’ll be using the statistics from our research to highlight the areas where we can partner to enhance the fine balance between good fraud protection and poor customer experience.

We’ll be publishing more detailed data in the coming days and weeks, to help businesses understand and address potential pain points within their mobile and online experiences. If you’re interested in digging into the results, give us a call.

There’s more about the solutions businesses use to manage fraud successfully and keep their customers happy on our website.

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How To Issue More Credit Cards With Predictive Analytics

Shanghai Pudong Development Bank Issued More Than 9 Million New Credit Cards Last Year Using FICO Originations

Shanghai Pudong Development Bank (SPDB) Credit Card Center, a credit card lending pioneer in China, has increased its customer base using originations powered by technology from analytics software firm FICO.

SPDB Credit Card Center’s total number of credit card applications using originations driven by a big data AI analytics strategy has exceeded 9 million, since January 2017. During this incredible growth, SPDB has maintained a controllable risk level while increasing its origination rate more than two-fold to 88 percent of applications. FICO’s big data AI analytics has reduced risk by 50% with an approval rate that is four times higher.

For its achievements, SPDB has won the 2017 FICO Decisions Award for Customer Onboarding and Management. The winners of the FICO Decisions Awards were spotlighted at FICO World 2018, the Decisions Conference, April 16-19 in Miami Beach, Florida.

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SPDB receive their FICO Decision Award

FICO’s origination and big data AI analytics solution was introduced with the aim of overcoming the challenges brought by the rapid development of SPDB’s credit card business. One of the key limitations holding back speedy originations was the limited credit data available on customers.

“Using custom scorecards and models from FICO built using Big Data AI analytics, SPDB Credit Card Centre has managed to significantly improve its risk assessment of consumers with either thin files or no files at the People’s Bank of China credit bureau,” said Sandy Wang, managing director in China for FICO. “The coverage rate or scorable population of the FICO models built using big data AI analytics, covers more than 75 percent of applicants.”

Joy Macknight, deputy editor of The Banker, one of this year’s judges for the FICO Decisions Awards, said, “I gave SPDB top marks because of their customer-centric success. They are achieving great results by taking a holistic approach to risk management across originations and collections.”

“SPDB has harnessed analytic technologies to reduce their overall risk, greatly increase the proportion of automatic originations, increase approval rates and scale their collections,” said Sandy Wang. “They have skillfully created a data-driven and comprehensive origination optimization strategy, using advanced decision science technologies and cutting-edge modelling experience from FICO. It has been a fruitful partnership and a project that has yielded significant results.”

Read the full release

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Check Your Organization’s Cybersecurity Score — For Free

There’s a lot of buzz about cybersecurity ratings — measures of a firm’s cybersecurity risk — but most businesses don’t understand how they work or know how they rank. We think it’s absolutely critical that they do. That’s why we announced today that we are making our own cybersecurity score free of charge to companies worldwide.

Now any company can vet the accuracy of their cybersecurity score before they’re unknowingly assessed by other organizations in their supply chain. As insurers begin using these scores in pricing cybersecurity insurance and as organizations start using ratings to vet supply chain and partner risk, businesses will need to vet the details used to assess their security posture — just as consumers check their FICO Score before applying for loans.

Getting your score is easy. You can sign up for a free subscription to the Portrait portal of the FICO® Enterprise Risk Suite, which gives you access to your firm’s FICO® Enterprise Security Score.

In fact, you can do more than just benchmark your cybersecurity score and see how business partners and insurers would view your cybersecurity posture. You can also curate the assets upon which your firm’s score is based. Again, just as consumers can review their credit bureau file to make sure the information that goes into their FICO Score is accurate, you can make sure that your FICO Enterprise Security Score is based on the right assets.

We are the first ratings provider to bring total transparency and self-service asset curation to the process of cybersecurity risk assessment. It’s part of our commitment to doing this right. We are also part of a consortium of industry leaders that worked with the U.S. Chamber of Commerce to develop new guiding principles for cybersecurity ratings.

For a simple view of what goes into your cybersecurity score, see this infographic:

FICO Security Ranking Infographic Check Your Organization’s Cybersecurity Score — For Free

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A Guide to Making AI Explainable – Yes, It’s Possible!

Screen Shot 2018 06 18 at 4.33.19 PM A Guide to Making AI Explainable – Yes, It’s Possible!

The possibilities of artificial intelligence are endless. AI helps businesses create tremendous efficiencies through automation, while enhancing an organizations ability to make more effective business decisions. However, it’s no surprise that companies are beginning to be held accountable for the outcomes of their AI-based decisions. From the proliferation of fake news to most recently, the deliberate creation of the AI psychopath Norman, we’re beginning to understand and experience the potential negative outcomes of AI.

While AI, machine learning, and deep learning have been deemed to be ‘black box’ technologies, unable to provide any information or explanation of its actions, this inability to explain AI will no longer be acceptable to consumers, regulators, and other stakeholders. For example, with the General Data Protection Regulation in effect, companies will now be required to provide consumers with an explanation for AI-based decisions.

FICO has been pioneering explainable AI (xAI) for more than 25 years and is at the cutting edge of helping people really understand and open up the AI black box. As you move forward with your AI journey, we’ve curated a list of blogs that uncover the importance of and trends leading to xAI.

According to GDPR, customers need to have clear-cut reasons for how they were adversely impacted by a decision. But what happens when your model was built with AI? This blog post uncovers the requirement of making AI explainable.

AI comes with many challenges, including trying to decipher what these models have learned, and thus their decision criteria. This blog lists ways to explain AI when used in a risk or regulatory context based on FICO’s experience.

Ready to make AI explainable? This post illustrates how you can achieve better performance and explainability by combining machine learning and scorecard approaches.

In 1996 we filed a patent for Reason Reporter—indicative of how long, in fact, FICO has been working with Explainable AI. Simply enough, Reason Reporter provide reasons associated with the neural network scores Falcon produces. The not so simple part? This post demonstrates how we utilize the reason reporter algorithm during model training.

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Authorised Push Payment Fraud – The Liability Challenge

Push Payment Fraud Authorised Push Payment Fraud – The Liability Challenge

Last week, the National Board for Customer Disputes in Sweden, after reviewing cases referred to them, have ruled that banks should be liable for so-called “push payment” fraud losses over a certain amount.

Authorised push payment fraud, or APP fraud, is gaining in popularity in the criminal community. Customers are being tricked into authorising payments by persuasive social engineering schemes run by criminals. These criminals have been so successful that this kind of fraud even has a nickname: hypnofraud.

Fraudsters have always targeted the weakest link in the process. As systems become more and more secure, the weakest link has become the customers themselves.

The push payment fraud trend has sparked debate at Payment Services Providers (banks and other financial institutions), regulators and consumer bodies about who should foot the bill when these kinds of schemes are successful. In 2016, a super complaint by the UK consumer organization, Which, was filed which called for the PSPs to do more to stop this kind of fraud, and to take greater responsibility for the losses when customers fall for these scams.

The question of liability isn’t straightforward, as my colleague Sarah Rutherford noted in a recent post. On one hand, customers are being tricked by highly convincing, almost hypnotic fraudsters, often posing as representatives from a bank. Whilst the industry can educate consumers about this, we can’t expect all customers to be experts in identifying whether calls, emails or SMS are genuine or fraudulent. On the other hand, if a customer withdrew cash from an ATM and was persuaded to hand over that cash by a fraudster, no one would expect the bank to foot the bill.

Whilst regulators and consumer bodies around the world make their own judgements, there is something the banks can do to reduce the scale of this problem and make social engineering scams less successful. By analysing the way each customer normally uses their account — whether transactions are authenticated by them or not — they can detect transactions that are out of character and stop them before funds disappear from accounts.

Customer behaviour profiling is a key way to detect and stop fraud from taking place, whilst allowing a frictionless experience for customers going about their daily business. For more on this, see our posts on the FICO Blog:

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Russian Credit Health Keeps Rising

Russian Credit Health April 2018 Russian Credit Health Keeps Rising

The two-year trend of improving Russian credit health continued in Q1 2018. Following a slide that lasted four and a half years, the FICO® Credit Health Index for Russia began climbing in April 2016 and climbed another 2 points last quarter, from 92 to 94.

What does this mean? Just as millions of Americans check their FICO Scores to see how their credit is doing, FICO and the National Bureau of Credit Histories (NBKI), Russia’s leading credit bureau, keep tabs on the health of Russian consumers. The FICO Credit Health Index measures Russian credit health, based on the percentage of consumer loans and credit cards reported to NBKI that are delinquent by more than 60 days.

The base was set at 100 in July 2009, and it climbed until the end of October 2011. Then came the long fall, which was arrested in early 2016.

What happened? “The biggest impact to the index came as Russian lenders and their customers embraced a new kind of credit product: the credit card,” said my colleague Eugene Shtemanetyan, who manages FICO’s operations in Russia. “Unfortunately, late payments here didn’t carry the stigma or penalties of late payments on secured credit, such as a mortgage or car loan. It took awhile for the Russian market to understand the importance of timely card payments, and for Russian lenders to adjust their customer risk management practices. The market stabilized, and loans issued in the last three years are higher-quality than the ones from the years prior.”

Risk management is still very much a priority for Russian credit grantors. “The main risks for delinquency remain the same — a decrease in real incomes,” said Alexander Vikulin, CEO of NBKI. “Therefore, lenders need to continue to closely monitor market indicators such as the PTI (payment to income), as well as to monitor the financial behavior of borrowers for all types of loans.”

FICO and NBKI provide Russian creditors with data to help them better understand how the credit market is developing and to build quality loan portfolios. FICO Scores, available through NBKI, are used by more than half of the leading Russian banks.

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Analytics Reveal What New Credit UK Consumers Can Afford

Affordability Risk Analytics Reveal What New Credit UK Consumers Can Afford

In the UK, affordability risk has been the subject of increased scrutiny by the Financial Conduct Authority, which, in consultation with lenders, has begun a process of stricter control in terms of treatment of consumers and assessment of their financial vulnerabilities. The goal has been to stop the rising numbers of British borrowers in a state of persistent debt.

At Money2020 today in Amsterdam, we took an important step toward helping UK lenders crack this puzzle. Along with our partners Equifax, we launched a product to address the combined issue of credit and affordability risk, initially in the UK market.

This product stems from extensive research into affordability risk, summarized in a recent white paper written by my colleague, Dr. Andrew Jennings. It’s a hot issue because consumers have a huge appetite for credit, and more “credit-hungry” consumers will normally present a greater risk to lenders. Still, it has been very difficult for a lender to understand the pressures on any consumer in terms of their ability to absorb more credit and pay off the required instalments, without placing unbearable stress on their finances.

During origination, a lender can ask for evidence of income and expenditure if required, and also use data available from sources such as credit bureaux to try to understand the financial circumstances of the applicant. But what happens after a loan is approved, when, say, a lender wants to increase a customer’s credit line, or cross-sell them a new credit product?

It is infeasible to continually request paperwork from a consumer to continue to assess affordability risk. In many respects, understanding the pressure consumer has in meeting their financial obligations cannot be measured.

The FICO® Risk and Affordability Decision Suite, powered by Equifax, is a result of significant research and development by FICO and Equifax and combines a suite of over 46 curated decision keys, including 5 analytics from both FICO and Equifax.

These include:

  • A new consumer-level FICO® Customer Management Score for risk assessment, developed using a combination of traditional methodologies and machine learning techniques
  • A Balance Change Sensitivity Index that identifies which customers would have a significant change in Probability of Default (PD) if they had a sizeable change in their credit card balance
  • An Indebtedness Score, developed on a consumer-level outcome definition to identify customers that are more likely to fall into arrears due to unsustainable credit commitments and higher debt-to-income levels
  • An Affordability Index, which uses trended information on the level and consistency of the funding of the customer’s principal current account and overdraft utilisation to provide new insight into a customer’s cash-flow and affordability position.

When considering the affordability stress on a consumer, it’s critical to use the most up-to-date data. This solution streamlines the delivery of data from Equifax and presents it to the decision processing system of a lender or processor, on a daily basis just in time for account cycling and decisioning in a fully end-to-end managed solution.

For more information on the research behind this solution, read our white paper, A New Challenge for Risk Management: Understanding Consumer Affordability Risk.

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