Tag Archives: Analytics / Scoring Technology

Analytics & Optimization Using Alternative Data in Credit Risk Modelling

Aug292017

“Whenever I bring up the topic of alternative data, the first question our board asks is, ‘Are we using Facebook data?’ “ This comment from a participant in our recent EMEA Risk Leadership Forum caused a lot of chuckles and nodding heads. When it comes to evaluating credit risk, everyone wants to know if, when and how lenders will start probing their Facebook account. For reasons that will be obvious to lenders, that tantalizing possibility doesn’t actually top the list of data sources to mine. In fact, at the forum we explored a few sources of data that can add to the picture of a consumer’s creditworthiness. Multiple Types of Alternative Data What is alternative data? In credit granting, it generally refers to any data that is not directly related to a consumer’s credit behavior. Traditional data usually means data from a credit bureau, a credit application or a lender’s... [Read More]

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Fraud & Security Cybersecurity: To Be (Empirical), or Not to Be?

Hamet with data background
Aug022017

That is the question for cybersecurity risk assessment. FICO has been in the analytics business since our inception back in 1956.  Our founders, Bill Fair and Earl Isaac, had the novel idea that businesses could make better decisions through data. Before anyone thought to call the resulting algorithms “analytics,” they set off to create game-changing approaches to correlating signals with outcomes to help companies manage risk, reduce expense, and maximize opportunities. Bill and Earl began looking for problems they could solve through an empirical analysis of data, and credit underwriting was a use case that was well-suited to the technique. Most credit-granting organizations had credit applications tucked away in filing cabinets (a source of consistent signal data), and most also had a reasonable handle on outcomes – i.e., who was managing credit to terms and who was in arrears or in default. The ability to relate data known at the time of the... [Read More]

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Analytics & Optimization The Future of Analytics: The Revolution Will Be Unstructured

Picture of Osvaldo Driollet
Jun052017

Although there has been much speculation over this statistic’s origin, most industry experts agree that 80% to 90% of the world’s data is unstructured data, and about 90% of it has been produced over the last two years alone. Of these unthinkably vast stores, only 0.5% is effectively analyzed and used today. In the business world, most unstructured data lies in customer-related text, which is abundant and available. However, most organizations don’t know how to efficiently extract predictive elements from unstructured customer data. They’re not sure how to reap the value of these insights by using them to boost the performance of predictive analytics, and make better operational customer decisions. But, done right, extracting valuable predictive insights from huge quantities of text takes just seconds. The Future Is Unstructured The tech industry is full of predictions, but in this one, I have high confidence: The future is unstructured –– because... [Read More]

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Risk & Compliance How to Build Credit Risk Models Using AI and Machine Learning

boxing poster with machine learning vs scorecard modeling
Apr062017

Which works better for modeling credit risk: traditional scorecards or artificial intelligence and machine learning? Given the excitement around AI today, this question is inevitable. It’s also a bit silly. While some new market entrants may have a vested interest in pushing AI solutions, the fact is that traditional scorecard methods and AI bring different advantages to credit risk modeling — if you know how to use them together. Take, for example, our new credit decisioning solution, FICO Origination Manager Essentials – Small Business. It’s designed to help lenders make faster origination decisions without increasing risk. This new FICO product combines our well-established scorecard technology with AI to build better credit risk models. How FICO Uses AI to Build Better Credit Risk Models As with our other origination products, Origination Manager Essentials includes credit risk models, and these models are segmented — different types of small business customers and different... [Read More]

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Analytics & Optimization Top 10 of 2016: Our Blog Posts You Liked Best

Jan032017

With 2016 recently coming to a close, we took a look back to uncover which topics you – our blog readers – gravitated toward last year. Chief among your interests were analytic innovation, credit risk, regulatory compliance, customer experience and mobile payments. Here’s a recap of our top 10 most popular posts published in 2016: US Credit Quality Rising … The Beat Goes On – Ethan Dornhelm shares FICO research showing how US consumer credit quality continues to climb. Why Is Customer Experience So Hard to Explain? – For an organization to improve customer experience, here’s why everyone needs to start on the same page. 4 Analytic Predictions for 2017 – From Killer Devices to AI Hype – FICO Chief Analytics Officer Scott Zoldi shares his predictions for analytics trends and burning issues in 2017. Your Customer Experience Management Is SO Immature! – Roughly 80% of companies are customer experience... [Read More]

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Risk & Compliance Can the Internet Revolutionize the Finance Industry in China?

Dec232016

This was the question FICO’s Dr. Andrew Jennings was challenged to answer as a guest speaker on a PBOC sponsored panel at The Third World Internet Conference in China. While one would assume the answer is ‘yes’, the world of FinTechs, P2P lending and online financial services have suffered quite a few stops and starts in China. Investment bubbles driven by consumers seeking higher returns, embryonic regulation and a patchwork of lackluster risk management practices persist in a nation undergoing a massive program of urbanization. Jennings spoke about the dual problems of reckless lending and the challenge of improving financial inclusion in China. He proposed that both can be solved with clever, analytically driven credit assessments that use new sources of data. “When we look at the data in China, there is not a single data source that can provide us with a predictable credit score for everyone. So the... [Read More]

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Risk & Compliance 2017 Predictions: 4 Trends that Will Shake Up Banking Next Year

Dec202016

If you follow the financial press, blogs and newsletters, you may have noticed a sea change in the topics du jour over the last 12 months. As we close out 2016, receding into the background are the never-ending stories of Big Data technology, as well as the hype of how P2P lending is taking over. Instead, the focus is on blockchain, open banking, AI, fintech beyond P2P lenders, cybersecurity, digitisation and customer experience. This shift is exciting because, as these topics all collide, it will shake up the very face of banking as we know it … although probably not quite as quickly as the technology talking heads would have us believe. I have one more to add to that list: financial inclusion must be central to the story of 2017 because it will be the beneficiary of many mainstream industry innovations. Here are some thoughts on just four of... [Read More]

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Analytics & Optimization Four Analytic Breakthroughs That Are Driving Smarter Decisions

Hand holding analytics
May262016

Patents are the currency of innovation, in software or any other industry. At FICO World 2016 in April, I explored how four patents we have recently been granted will enrich FICO’s product portfolio and, in turn, your business. Collaborative Profiling From cybersecurity, to payment card fraud, to marketing, companies want answers to the question, “How do we know when someone’s behavior has changed in a significant way?” And subsequently, “How do we rank those changes to focus on the most important cases?” FICO’s recent patent on Collaborative Profiling and change-point detection provides an efficient new way to answer these questions. By distilling behaviors from a large group down to a few basic “archetypes” of behavior, we can effectively determine which persons have the biggest changes in archetype mixtures. That’s a powerful capability that can also help marketers to better understand changing customer preferences. Structuring IoT Messages For the past few years... [Read More]

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