FICO

By Fair Isaac Corporation

About this podcast   English    United States

Fair Isaac Tech Talks are short interviews designed to empower consumers, business managers and analytic scientists with breakthrough ideas and technology from Fair Isaac, inventor of the FICO® score and a leader in analytics and Decision Management technology. Get helpful information for managing your personal credit profile, learn about the latest tools and techniques for managing risk, fraud and customer satisfaction, and discover the latest advances in credit scoring, business rules management, predictive analytics and optimization.
yesterday
FICO WORLD 2018, MIAMI, Florida FICO today unveiled a host of new retail banking solutions that allow lenders to manage the credit lifecycle in a way that is smarter, faster and simpler. The innovations are designed to help support lenders with their digital transformations as retail banking continues to be shaped by the forces of mobile, cloud, analytics and big data. “We have seen remarkable changes in banking in the last two years as lenders accelerate their digital transformation and reinvent the customer experience,” said Tim VanTassel, vice president of FICO's credit lifecycle business line. “Lenders are engaged in an analytic arms race to find, delight and retain the right customers by determining and deploying differentiated offers and experiences.” Read the full media release here Originate Loans Using Optimized Deal Structures Providing consumers with multiple options for the best-fitting terms in real time has been an industry goal for some time, and with its latest innovation FICO has made it a reality. FICO® Origination Manager now interacts seamlessly with Alternative Deal Structure (ADS) to evaluate thousands of alternative offers and present a set of differentiated options in seconds. Manage Customers with Greater Agility FICO® Strategy Director, which delivers faster, easier decision authoring and management with plug-and-play industry configurations, builds on the proven decision process flow of FICO® TRIAD® Customer Manager and now offers the same business value with configuration for the Telecommunications industry. The Telco Service Management solution uses analytically driven decisions to help make relevant and profitable offers, reduce churn and improve device financing decisions. At the same time, new configurations for lenders bring the capabilities of TRIAD Customer Manager to Strategy Director and provide a simple migration to speed cloud adoption and time to value. Make Better Decisions Collecting Payments FICO® Debt Manager FitAgent can now sift through massive real-time datasets from internal or external sources, such as dialers and other communication systems, using FICO® Decision Management Platform Streaming to rapidly generate powerful insights that assist with the collection and recovery process. FICO has further improved the FitAgent user experience with new controls, views and insights around payments, customers, accounts and communication that put the customer at the center of a lender’s operations. To reduce the cost of deploying industry-leading analytics, Debt Manager also easily consumes optimization analytics from FICO’s suite of decision optimization capabilities. Improve Customer Communications with AI and the Cloud FICO® Customer Communication Services (CCS), provides analytically driven, scalable, two-way, automated voice, text, email and mobile app notifications. This solution helps banks, telcos, government agencies and utilities around the world connect more effectively with their customers and resolve suspected fraud cases and overdue payments automatically. FICO has collaborated with AWS to bring Amazon’s AI-driven text–to-speech service to CCS. [video width="1280" height="720" mp4="http://www.fico.com/en/blogs/wp-content/uploads/2018/04/AWS-FICOCCS-Final-041418-proxy.mp4"][/video] FICO is also using Amazon Web Services to deliver CCS Voice. “We make millions of contacts per day around the world and AWS allows us to scale with the high performance, security and reliability needed to match the growth of our business. In growing regions like Asia-Pacific, where we currently serve six countries, it has been the perfect match for customers who need speed, simplicity and scale,” said VanTassel. FICO® World 2018 runs through April 19 in Miami Beach, Florida. More than 1,000 business leaders from 50+ countries are attending to explore new ideas, technologies and solutions in AI, advanced analytics and decision management.The post Banking Solutions: Reduce Complexity, Increase Sophistication appeared first on FICO.
April 18, 2018
No audio available for this episode
FICO WORLD 2018, MIAMI, Florida Mission Critical AI FICO showcased the latest enhancements this week to its FICO® Decision Management Suite (DMS) which leverages artificial intelligence (AI), machine learning (ML), advanced analytics, optimization and decisioning to deliver better, more predictive business outcomes. New capabilities include: DMS Enterprise Grade Cloud Service: Now available on AWS, this managed service provides 24x7 high availability, disaster recovery, and supports the development, test and production environment. New tools and execution platform: For mission critical AI, decisions, analytics and optimization, the new FICO® Analytics Workbench supports a wide range of commonly used AI and ML model executions and FICO developed analytic models for use cases such as fraud and anomaly detection. FICO® Decision Central™ and DMS Hub in the Cloud: Enables true centralized decisioning with performance tracking, governance, source code control and collaboration for analytics and AI models. Next generation decision optimization: Latest version of FICO® Decision Optimizer is now available in the Cloud. “We are excited to unveil new capabilities in FICO DMS,” said Jari Koister, vice president of product management at FICO. “DMS supports the full life cycle of decision, analytics and AI driven applications, this includes data ingest and management, collaborative development, scalable elastic execution, and management and performance tracking of models. “Enterprises are eager to transform their business to be analytic and AI driven,” said Koister. “The effort to develop, deploy and improve such solutions for mission critical applications is complicated. With a broad range of new products and capabilities DMS provides a path to help businesses transform and take advantage of AI, ML and optimization efficiently, while maintaining focus on their business problems and value add.” Read the full media release here FICO® World 2018 runs through April 19 in Miami Beach, Florida. More than 1,000 business leaders from 50+ countries are attending to explore new ideas, technologies and solutions in AI, advanced analytics and decision management. The post Mission Critical Artificial Intelligence in the Cloud appeared first on FICO.
April 18, 2018
No audio available for this episode
FICO today unveiled several solution upgrades that will help banks, lenders, fintechs and other institutions fight fraud and financial crime. These solutions bring unparalleled efficiency and machine learning capabilities to fraud, risk and compliance professionals. “We’re giving our customers new tools across the spectrum of our fraud and financial crime portfolio,” said TJ Horan, vice president of fraud solutions at FICO. “These releases, along with our continued leadership in machine learning R&D, keep our solutions at the cutting edge of AI-based financial crime protection. In addition, our solutions are supported by a rapidly growing team of advisors with deep industry experience. This is why financial institutions around the world overwhelmingly choose FICO to fight fraud and financial crime.” The new solutions and features include: FICO® Falcon® Platform, designed to adapt fraud defenses across all channels, with each transaction, will provide third-party model support that allows users to deploy analytic models created by their own data science teams. Anti-Money Laundering (AML) Advanced Analytics, designed to work with the FICO®TONBELLER® Siron® platform, leverages supervised and unsupervised machine learning to combat money laundering. FICO® Card Compromise Manager 2.0 leverages advanced analytics and data from the billions of payment cards protected by Falcon Platform customers worldwide to detect data breaches and points of card compromise. FICO® Application Fraud Manager, which helps institutions detect and prevent fraudsters from opening accounts, includes new rule simulation capabilities that allow organizations to evaluate new rules and policies against “what if?” scenarios. FICO® Identity Resolution Engine 5.0, which combines entity resolution and graph/network analytics that enable the proactive detection and investigation of organized crime, now provides continuously updated entity analytics and data visualization tools. “One of the biggest trends in the financial crime industry is the convergence of fraud and regulatory compliance operations, which includes AML and know-your-customer, or KYC, regulations,” Horan said. “At FICO World, we are also previewing the FICO Financial Crimes Studio and FICO Falcon X, a new financial crime platform that will give institutions a whole new, integrated way to enforce protection. We’re excited about this game-changing platform — stay tuned for more.” For more detail on these solutions, visit fico.com/enterprisefraud. FICO® World 2018 runs through April 19 in Miami Beach, Florida. More than 1,000 business leaders from 50+ countries are attending to explore new ideas, technologies and solutions in AI, advanced analytics and decision management. The post New Ways to Fight Fraud and Financial Crime appeared first on FICO.
April 13, 2018
No audio available for this episode
“33% of enterprises will take their data lakes off life support (in 2018). Without a clear connection to change-the-business outcomes, many early adopters will pull the funding plug on their data lakes to see if they pay for themselves or die.”  - Forbes.com There's untapped potential in your data lake — if you can tap into it, it doesn’t need to die! FICO has the experience and the AI tools to wade through your unstructured and structured data, emerge with actionable insights, and then implement them to improve your business. How exactly do we do that?  We’ve created a universal how-to guide on this topic, which will be presented at FICO World 2018, April 16-19 in Miami Beach. Beyond Big Data to Big Insights and Big Business Value On Tuesday, April 17, my colleague Peter Ould and I will divulge the details of FICO’s three-step process for getting business value from big data quickly. In short, the steps are: Exploit the Data (Hint: This step is critical in guiding the subsequent steps and maximizing value) Listen to the Data to Find the Complex Patterns (Hint: Most people skip this step but they shouldn’t) Execute Learnings Effectively and Efficiently (Hint: Machine Learning really helps here) Our presentation highlights each of the three steps, discussing the key techniques and methodologies involved as well as the resulting business value achieved by some of FICO’s most innovative clients. As the pace of data generation and data diversity continue to increase, making better, faster data driven decisions will differentiate you from your competitors. Join us in Miami Beach to learn about FICO’s proven process for tapping into the potential of your Big Data.The post Three Steps to Make Your Data Lake Pay Off appeared first on FICO.
April 12, 2018
No audio available for this episode
AI in Collections an Inevitability Artificial intelligence (AI) is becoming more integral in improving collections, according to banks in Asia Pacific (APAC). In a survey conducted at the FutureCollect event in March, seven out of ten senior collections managers revealed they plan to implement and integrate AI into their collections systems within the next two years, and 24 percent said they will do it next year. These new findings are consistent with FICO’s insights on AI earlier this year, predicting companies will focus on operationalizing AI in 2018. Almost half (48 percent) of banks believe that the use of AI will help them optimize their collection decisions, while 41 percent feel it will enable them to accurately predict consumer behavior. AI-powered analytics can improve automation in collections in many areas, from optimizing contact strategy settings to ensuring human agents make sophisticated decisions when restructuring debts or even calculating provision rates at an account level for IFRS 9 compliance. “AI is in the spotlight within the boardroom of most banks,” said Dan McConaghy, president for FICO Asia Pacific. “Lenders understand that they need the tools that allow them to stop relying on gut-feel decisions or out-of-date models, and collections is a key area where AI has the potential to improve business decisions as well as the customer experience.” The survey was conducted at the recent FICO® FutureCollect 2018 event in Tokyo, Japan, which was attended by 53 representatives from banks and financial institutions across Asia Pacific & Japan. Read the full release here AI in Collections - CCS enhancements AI enhancements for the FICO® Customer Communication Services (CCS) solution are being rolled out this year, and will further lift the significant impact that automation continues to deliver. “We believe that Customer Communication Services has a lot to offer late-stage collections,” said McConaghy. “Automated collections helps to reduce the number of customers that end up in these late stages through early intervention with early contact strategies that work. Now with the addition of AI, we are also seeing significant improvements in minimizing roll rates across credit card portfolios. “When customers move past the 90 days bucket, our AI is able to arm highly skilled agents with options to make more sophisticated decisions when restructuring payments for this group. This means customers are more likely to repay and remain customers, while still giving the organization the benefit of making a profit on the offer made.” Our head of analytic consulting for Asia Pacific, Phillip Norman, explains how AI will affect collection strategies. The probability to pay, the likelihood of cure rates and the cost to collect, are just some of the areas that will be optimized and automated. [embed]https://youtu.be/OW2hT6r5T7k[/embed] Further AI modules, to be added to CCS in the second half of 2018, will see even more benefits delivered for contact strategies, next best action, treatment optimization and more.  The post 70% of APAC Banks To Use AI in Collections by 2019 appeared first on FICO.
April 12, 2018
No audio available for this episode
Today we have released the findings from our first ever global consumer survey on automotive finance perceptions. FICO’s independent research surveyed 2,200 adult consumers across nine countries including the US, Canada, Mexico, Chile, Australia, New Zealand, Germany, Spain, and the UK. The respondents were between the ages of 18-64 who acquired a loan on a new/used vehicle within the last 3 years. The findings cover the financing aspect of both new and used vehicles from the beginning of the journey where customers start to research, the middle where negotiation, ‘shopping around’ and the loan origination begins, and the end where the deal is formalized and the consumer walks away with their vehicle. 5 Surprising Findings in Automotive Finance (1) Americans love speed, right? The country that invented McDonalds should have the shortest wait times for auto finance. Wrong. It turns that the US is ahead of only Mexico in terms of wait time length to complete an auto finance transaction! (2) Americans and Canadians prefer going online, right? Not so much. These two countries reported the lowest desire to complete their next transaction online out of the nine countries where we collected data. That said, there is a 23-point gap in terms of current digital use vs desired future use in the US, so clearly there is a consumer desire to make the shift to digital. (3) You might think that Millennials would pick digital first, but it turns out not to be the case. Their first choice of channel for their next purchase is to go to the bank! This makes a little more sense though if you remember that Millennials often don’t have a lengthy credit history so may feel that going to someone they know will give them a better deal. (4) Are women less likely to negotiate? We did not find a significant difference in terms of being likely to negotiate for an auto loan across men and women. Interestingly we found men are somewhat more likely to go online for their next loan and women somewhat more likely to go to a dealership. (5) Want a great deal on your auto loan? Go to Germany. Germans were mostly likely to report they got a good or excellent deal on their transaction. They also reported short wait times and led the way in terms of current adoption of digital. There were also a few findings that weren’t surprising. Customers want more transparency and speed during the process. They dislike lengthy paperwork. They want to be treated as individuals and they want to complete the transaction on the channel that works best for them. Some folks prefer the convenience of going online, some appreciate the one-stop shopping they can get at a dealership, and others like and trust their bank and prefer to go there. The one thing all consumers have in common? Financing a car isn’t just a one-time transaction but a moment of truth where financing companies can start or seamlessly continue a longer term, mutually beneficial relationship. Want more insights? I’ll be presenting these and other findings alongside observations from GM Financial and Ally at our FICO World session next week in Miami entitled,"Consumer and Dealer Perceptions in Automotive Finance." For more info about the session, please check out the FICO World website. You can download the US report and the other eight country reports here.The post Automotive Finance: 5 Surprising Findings About The Consumer Experience appeared first on FICO.
April 12, 2018
No audio available for this episode
It used to be that KPIs for the fraud department focused only on loss prevention, aligned to the amount of fraud stopped and money saved – this is no longer the case. Fraud communications and other interactions are increasingly seen as a vital part of the customer experience. In a recent survey, we asked heads of fraud where they thought the most revenue was lost. Almost half reported that the amount lost to poor customer experience, as a result of false positives, was higher than the amount lost to genuine fraud. Fraud departments that step up to play their part in customer retention and satisfaction are transforming themselves on the balance sheet to a revenue-generating center. To this end, today’s fraud department is likely to have additional targets that include: Customer satisfaction Reduced false positive ratios Reduction in cost of operations Target levels of automated fraud communications (to remove friction from the customer journey, improving customer experience) Customers expect to interact on a number of new channels and there is little tolerance for friction or disruption. And when a process goes wrong, customers don’t see the process at all, they see the brand making their life difficult. Take having a payment declined, when trying to rent a car abroad, for example. Those businesses that don’t respond to consumer demand for convenience will ultimately fail. We’ve already experienced this; once-ubiquitous brands such as Blockbuster and Woolworths have disappeared. Conversely, those that offer a friction-free customer experience prosper; Netflix, Amazon and Monzo are some examples. What Interactions Can You Automate? The fraud team can inadvertently block a smooth customer journey, but automation helps by: Making alerts to suspected fraud fast and appropriate. This is done by using automated channels to contact customers with fraud communications on their preferred channel. Because there is no need to wait for a human operative to take action, disrupted processes can be put back on track quickly. Giving customers more control. Automated methods allow them to make decisions that make their lives easier — for example, to freeze a card, or prove a transaction is legitimate and allows it to proceed. Letting customers use the channels they love to access other areas of the bank quickly. For example, customers can use touchID to authenticate when trying to start a conversation with an agent in telephone banking. We have found that customer satisfaction has increased in those banks that deploy higher levels of automation in fraud management. Customers appreciate the visibility of such fraud control and insights into their account activity, particularly when they can see that their bank is reacting immediately to threats. Rather than view such controls negatively, customers are likely to view them as proof that their bank is taking necessary and timely action to protect them, whilst giving them technology that they love to respond quickly and easily. Despite the focus on customer experience, the fraud department must still meet objectives related to identification of customers and resolution of fraud cases. Fortunately, we found that the role of automation is equally important in delivering this. We have seen a direct correlation between the amount of automation and the overall resolution of all fraud cases. The more channels and processes that were automated for fraud management, the more likely it was that a case would be fully resolved, even outside of the automated channels. How Many Interactions Are Fraud Departments Automating? Despite the clear benefits of automating fraud interactions, there is a wide range in the amount of automation deployed, as shown below. Since automation improves both customer satisfaction and case resolution, those at the lower end of the adoption scale are taking a big risk. The reputation of their brand, the value of their organization and ultimately their own jobs are at risk – a fraud department that is not performing is a candidate for outsourcing, and we have seen this happen. There are legitimate reasons why some organizations have not yet embarked on fuller automation programs. They may have concerns about the security of automated channels or had negative customer feedback about a previous attempt at automation. In my next blog post I will write about these challenges and how they can and should be overcome.The post Why Should Banks Automate More Fraud Communications? appeared first on FICO.
April 9, 2018
No audio available for this episode
Jari Koister, Vice President of Product Management at FICO, discusses the advantages and challenges organizations face when using AI and machine learning. He also unveils the Explainable Machine Learning Challenge, check out the video below.   https://youtu.be/csqQt-D610s   To participate in the xML Challenge, or just keep up on the progress, go to community.fico.com.  The post VIDEO: Explainable Machine Learning appeared first on FICO.
April 9, 2018
No audio available for this episode
A look at the UK Classic card trends based on data from December 2002 to December 2017 in the blog revealed the highest levels in that time period for spend and average lines. It also highlighted some potential signs of debt stress, most prominently among accounts 1-5 years on book. We reviewed February’s data from the FICO Benchmarking Service to see the impact of the Christmas spend on this subpopulation. The normal seasonal trend of a sharp increase in delinquency in January with a drop in February was repeated this year. Although results are still noticeably below those seen during the last economic downturn, more recent activity indicates possible areas of concern and debt stress: The percentage of 2 cycle accounts was 26% higher than in February 2016, and was the highest for February since 2014. The percentage of 2 cycle balances was also up by 24% and was the highest for February since 2013. Average 2 cycle balances reached their highest since at least 2002 and are 15% higher than in February 2016. Average card lines hit their highest point since at least 2002, growing 7% since February 2016. This means that average delinquent balances are growing at over double the rate of lines. Despite this rise in lines, the percentage of overlimit accounts reached the highest level since January 2011. The average amount overlimit reached its highest February value since at least 2002, and was last at this level in March 2016 and higher in July 2012. During the last 3 months average 1 to 3 cycle balances again reached over two-year highs for accounts <5 years on book. Due to these continuing trends, we recommend that Issuers review their results to determine if they are seeing the same behaviour and to understand why this is happening, in case strategic changes are required in originations or account management. There is scope for issuers to review accounts earlier in the collections life cycle when they have not missed any payments but are spending above the agreed limit, and may be suffering from debt stress. A proportion of these will be higher risk than some accounts which have just made one payment late — so-called ‘lazy payers’. This review could also be expanded to include other high-risk accounts that are still within their limit accounts. This type of early identification and intervention could also provide benefit in relation to IFRS 9 provisioning.  Issuers could establish whether a collections focus needs to be placed on the highest-risk, high-balance accounts in this particular segment as well as implementing or increasing the pre-delinquency actions. I will be writing soon in more detail on the subject of pre-delinquency. To learn more about our cards benchmarking service, or FICO’s new Risk Benchmarking Service which forms part of the Fair Isaac Advisors P&L Insight Suite, please contact me at [email protected] post UK Cards Show Signs of Post-Christmas Debt Stress appeared first on FICO.
April 6, 2018
No audio available for this episode
How are advances in artificial intelligence and machine learning changing credit risk assessment? That’s a topic I’ll be exploring in three presentations at FICO World 2018, April 16-19 in Miami Beach. These three presentations have a common thread: How FICO applies artificial intelligence and machine learning not as a “silver bullet” but carefully balanced with human domain expertise in the formulation of problems and models. Applying Machine Learning to Challenge the FICO Score: What Have We Learned? FICO® Scores are among the most scrutinized models in the world, so would you expect modern machine learning — with its challenges around explainability — to bring great benefits to FICO® Score R&D and production? On Tuesday, April 17, 1:30-2:30, my colleague Ethan Dornhelm and I will show that machine learning offers tremendous efficiencies for research “in the lab”. But in order to bring these efficiencies to the field in the form of a new international FICO® Score, we benefitted from blending the latest machine learning algorithms with FICO’s own explainable and palatable Scorecard development technology. Join us to see how we did it and how the FICO® Score compares against “purist” ML models! Using AI to Address Affordability in Credit Decisions Regulators in the UK require that account management decisions need to be forward-looking, by factoring in customers’ abilities to absorb additional debt. In situations where detailed information on incomes and spending isn’t available, how else can we judge affordability? We reformulated this problem as a what-if question: For whom would increasing balances cause financial distress? We conducted an observational study into cause-and-effect for which we leveraged credit bureau data and AI algorithms to identify customers who would have a significant change in their default likelihood if they had a sizeable increase in their total credit card balances. This led to a new scorecard and index that rank-orders affordability risk and complements traditional credit risk scores. Join me at this session on Thursday, April 19, 10:15-11:15. FICO® Scores Through the Economic Cycle: Understanding Consumer Sensitivities to Economic Fluctuations The FICO® Scores is a robust rank-ordering analytic, and that rank-ordering remains strong across economic downturns and upswings. But what can we learn from shifts in the odds-to-score relationships through the economic cycle? To unlock insights into individuals’ sensitivities to economic downturns, we applied machine learing to multi-year credit bureau data, comparing and contrasting payment behaviors from a normal economic period versus a recessionary period. We constructed a new Economic Sensitivity Index which could be valuable both for credit decisions and for provisioning. See how we constructed the problem and our empirical findings in my session with my colleague George Shand on Thursday, April 19, 9:00-10:00. I hope to see you at FICO World 2018, where artificial intelligence and machine learning will be part of many presentations, not just mine!The post FICO Scores, Artificial Intelligence and Machine Learning appeared first on FICO.

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