Analytics & Optimization An IT Perspective: Why We Embraced OpenStack


One of the most exciting innovations at FICO in recent years was the launch of the FICO® Analytic Cloud. We developed our cloud to democratize access to analytics, and we built our cloud on OpenStack — an open-source, infrastructure-as-a-service platform. Our director of engineering and cloud services, Nicholas Gerasimatos, recently talked about our experience with OpenStack at the OpenStack Summit 2015 in Vancouver. During an interview with SiliconANGLE, Nicholas discussed the strategic benefits of building on OpenStack as well as the challenges of developing on an open source platform. As you’ll see, we’re big believers in open source for present and future of development. We couldn’t imagine taking on a project like the FICO Analytic Cloud with a proprietary platform. We hope you enjoy the interview, and we’d love to hear your take on OpenStack.

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Risk & Compliance Murky FCC Ruling May Provoke More TCPA Lawsuits

1991 telephone 2

Needless to say, we’ve come a long way since 1991. It was a year when the mullet was still sexy, when rap was just becoming mainstream, and when the World Wide Web first became publicly available on the internet. It was also the year when the Telephone Consumer Protection Act (TCPA) passed.

The advent of new communications technology has created gaps in this law and accompanying regulations. For nearly 25 years, the TCPA has remained unchanged, yet modern communications has evolved rapidly, with mobile phones largely replacing landlines as the communication method of choice. The Federal Communications Commission (FCC) has issued several interpretative regulations and orders during this time, but has been relatively quiet since 2008.

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Analytics & Optimization How Banks Can Fight Attrition and Improve Risk Predictions


How can banks leverage their transactional and non-traditional data sources to fight attrition and risk prediction? At this week’s Credit Scoring and Credit Control XIV conference, I will be discussing this subject in detail, but I thought I’d give you an overview of my talk. Transactional and non-traditional data sources show a lot of promise for banks. Using transactional analytics, for example, we can build more predictive behavior risk models using combination of Masterfile and transaction data. Such models are also better at predicting risk of default earlier than the traditional models. So banks can achieve the twin benefits of identifying more instances of future bad cases much earlier. Similar benefits accrue in case of attrition detection. Working with transaction data can also eliminate the need for expensive Masterfile data while keeping the performance gains intact. With the advent of Big Data technologies, it has become far easier for banks... [Read More]

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Analytics & Optimization Engaging Fickle Customers and Tackling Silent Attrition


At the Credit Scoring and Credit Control XIV conference August 26-28, I will be discussing innovative analytic techniques and applications revolving around engaging fickle customers and tackling silent attrition.  Here is a preview of my talk: Everyone knows the ideal customer: frequent shopper, highly profitable, engaged, loyal. But in today’s competitive markets the most profitable customers are a fickle species and can turn away (or more likely are lured away) on a dime, possibly without giving prior warnings. “Silent attrition” happens when customers stop transacting without saying “I’m no longer your customer”. It occurs in non-contractual relationships such as in retail and it happens with credit cards when customers stop using a card without canceling it. When silent attrition emerges, businesses have a brief window of opportunity to try to re-engage the customer before the parting becomes cemented. Rapid detection of silent attrition and fast contact through mobile channels provides... [Read More]

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Customer Engagement Millennial Bank Loyalty … Not So Much


FICO has been looking at millennial banking habits for a number of years now, and banking loyalty is one area of particular interest to us and our clients. Our research and studies by others have consistently shown that millennials are much more likely to switch banks than other generational groups, and that their loyalty to banks is much lower than to other categories of products/services. Below is some data from a recent study that shows financial services at the bottom of the heap. Source: Adroit Digital, Millennials: The New Age of Brand Loyalty, 2014 When we spoke directly with millennials, we found similar results – bank loyalty is quite low. This short video of millennials discussing bank loyalty highlights some of those areas. Here are several interesting takeaways: One reason cited for not changing banks was the “hassle factor” of moving online banking. Many large banking institutions are viewed as... [Read More]

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Collections & Recovery CFPB on Debt Collection: What Consumers are Complaining About

CFPB logo

Last month, the CFPB issued the first in a new monthly report focusing on consumer complaints. The report covers complaints by product, state and company, and each issue includes a specific product spotlight and geographic focus. This first report showcases debt collection. Debt collection represents 32% of complaints submitted in June 2015, and this is the 22nd consecutive month the CFPB handled more complaints about debt collection than anything else. The debt collection complaints for June 2015 fall into six categories:   You might be surprised to learn the greatest month-over-month percentage decrease (-4%) came from student loan complaints. What does this mean for members of the accounts receivable management industry? You’re expected to mitigate risk areas. You’re expected to respond to complaints within 15 days and if the complaint can’t be closed within this time period, document work in progress and final resolution within 60 days. Anything done outside... [Read More]

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Analytics & Optimization Optimize My Life, Please!

Optimize Me

Working in an analytics company often gets me thinking about how I could use some of our advanced techniques in everyday life. Specifically, I often daydream about the mathematical process called optimization. Really I do, don’t you? In the most basic terms, optimization is the selection of one or more “best alternatives” from a larger set of possibilities. From a business perspective, optimization could involve determining the best three car loan offer options to give to a prospective buyer, considering (among other things) the buyer’s ability to repay the loan (based on credit history) and the lender’s risk appetite (as well as indirect factors such as dealer incentives).Non-banking examples include optimizing sport schedules (think TV deals and travel challenges), as well as determining the best way to provision everything from fuel to beer and peanuts on an airline, per this video. But that’s all business, right? What if we had... [Read More]

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Risk & Compliance US Credit Quality Continues To Climb – But Will It Level Off?


According to the latest national distribution of FICO® Scores, US consumer credit quality has continued the slow-and-steady climb we’ve seen over the last few years. As we’ve observed for several years now, more consumers are scoring 800 or above—19.9% vs. 19.6% just six months earlier. And fewer consumers are scoring below 550. In fact, there’s been a clear pattern of decline in this segment since the low point of the economy in late 2009/early 2010. Some of this trend may be a result of the lowest-scoring consumers “dropping out” from traditional credit usage, and by extension no longer having valid FICO® Scores. Still, this decline is encouraging. It indicates that overall more consumers using credit are managing it responsibly enough to not be among the lowest scorers. In addition, the national average FICO® Score is currently at an all-time high since we’ve been tracking this metric, dating back to pre-recessionary... [Read More]

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Risk & Compliance Model Risk 101: A Checklist for Risk Managers

Model Risk 101 Chalkboard #3

In my previous Model Risk 101 blog post, I discussed how the first line of defense – model developers and users – are tasked primarily with implementing a consistent, formalized model development approach. That’s a challenge in and of itself – but model risk management and governance doesn’t end there. Once in production, predictive models are subject to performance erosion driven by changes in portfolio risk characteristics or availability of economic data. Across the model lifespan, it is therefore critical to answer questions such as: “Are these models still fit for purpose?” or “What corrective actions are needed in case of model performance breaches?” That’s where your second line of defense comes in. For an integrated model risk management system to work, the second line – primarily risk managers – must go beyond periodic validation to ensure that model use and performance remain in alignment with the portfolio risk profile,... [Read More]

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Analytics & Optimization Why Businesses Need Decision Trees

Decision Tree

A lot of people may not know what decision trees are. Do they bear fruit? Are they hardy enough to survive inclement weather? Actually, decisions trees are an essential part of daily life. Everyone uses decision trees to plan their lives, whether or not they know it. Only we probably don’t think of them as decision trees. Should you change out of your pajamas? Will you ever find the thing you lost? Should you get a dog? Several daily life decision tree examples are posted on this site – these are intentionally funny, perhaps, but I think we can admit this stuff isn’t that far from the truth. Well, if decision trees power our daily decisions, how are businesses using decision trees to power their customer interactions? This was the key topic that my colleague Lamar Shahbazian and I recently co-presented in a short webinar, Unleashing the Power of Business Rules Development. While decision trees in business take... [Read More]

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