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Consumer credit card debt reached $650 billion in Q3 2015 — the highest level since Q4 2009.

As 2016 approaches, many people have identified their New Year’s resolutions, but the majority fail to stick to these resolutions.  While 45% of people make resolutions, only 8% are successful in achieving their goals. The most common resolution types:* To increase the likelihood of keeping resolutions, experts recommend setting small, attainable goals and regularly tracking progress. *Total is higher than 100% because of multiple resolutions >> New Year's Resolution Statistics

According to PlayNetwork.com, for the first time in two decades Mariah Carey’s “All I Want For Christmas Is You” is no longer the most-played holiday song in retail stores. The list of top songs includes: Rank Artist Title 1 The Shins Wonderful Christmastime 2 Mariah Carey All I Want For Christmas Is You 3 Christina Aguilera Christmas Time 4 Waitresses Christmas Wrapping 5 Jack Johnson Someday At Christmas 6 Kelly Clarkson Underneath the Tree 7 Michael Buble A Holly Jolly Christmas 8 Bing Crosby White Chistmas 9 Train What Christmas Means To Me 10 Ella Fitzgerald Have Yourself A Merry Little Christmas >> Top 20 Songs Heard by Holiday Shoppers

Payments and the Internet of things has been colliding for a while now – and it surfaced again recently with Mastercard announcing that it is working with an array of partners including Capital One to launch payments in connected devices. The thinking here seems to be that payments is a function in the Marlow’s pyramid of needs for any new consumer device. I am conflicted on this point – not that I don’t believe the Internet of Things isn’t important, but that we may be overthinking in how payments is important to be shoved inside everything that has a radio baked in. And not everything will have a radio in the future, and the role of a smartphone as the center of the connected device commerce universe isn’t going away. It is important to keep perspective here – as this announcement is less about coat sleeves hiding NFC chips with tokenized credit cards – rather it’s the commerce enablement of devices that we may carry on our person so that they can be armed for payment. Though I may disagree on whether a coat sleeve or jewelry are essential end-points in commerce, a platform of capabilities to challenge, authenticate and verify, and ultimately trust and provision a tokenized representation of something, whether its a card or a fragment of a consumer's identity, to a device that itself represents a collection of radios and sensors is very exciting. It is exciting because as device counts and assortments grow, they each have their own residual identity as a combination of things and behaviors that are either deterministic or probabilistic. The biggest shift we will see is that the collective device identities can be a far better and complete representation of customer identity that the latter will be replaced by the former. Name-centric identities will give away to algorithmically arrived ones. As Dan Geer puts it, no longer will I need to announce that I am Cherian, but my collection of devices will indeed do so on my behalf, perhaps in consultation with each other. More over, none of these devices need to replicate my identity in order to be trusted and tethered, either. Coming back to Payments, today my Fitbit’s claim to make a successful payment is validated way before the transaction, when I authorized provisioning by authenticating through a bank app or wallet. What would be interesting is when the reverse becomes true – when these class of devices that I own can together or separately vouch for my identity. We may forget usernames and passwords, fingerprints may prove to be irrevocable and rigid, but we will always be surrounded by a fog of devices that each carry a cryptographically unique and verifiable signature. And it will be up to the smartphone, its ecosystem and the devices that operate in its periphery to individually negotiate and establish trust among each of them. So this is why I believe the MasterCard effort in tokenizing devices is important when you view it in conjunction with the recent launch of SwiftID from CapitalOne. Payments getting shoved in to everyday things like wearables, disguises the more important effort of becoming a beachhead in establishing trust between devices, by using tokenization as the method of delivery. As you may have gathered by now, I am less excited of pushing cards in to devices (least of all – cars!) and more about how a trusted framework to carve out a tamper proof and secure cache within an untrusted device, along with the process to securely provision a token or a signed hash representing something of value, can serve as the foundation for future device – and by extension – user identity. On a side note, here’s a bit about pushing cards in to cars, and mistaking them for connected cars. To me there are only two connected car classes today. One is Tesla where each car on the road is part of the whole, each learning separately and together as they examine, encounter and learn the world around them to maneuver safely. The other is a button in an app that I hit to have a car magically appear in front of me. Other than Tesla and Uber, there are no other commercial instances of a connected car that appeals (Google has no cars you can buy, yet).

Millennials, now the largest generation in the United States, are taking longer to establish credit than earlier generations of young people.

Leveraging customer intelligence in the age of mass data compromise Hardly a week goes by without the media reporting a large-scale hack of sensitive personal or account information. Increasingly, the public seems resigned to believe that such compromises are the new normal, producing a kind of breach fatigue that may be lowering the expectations consumers have for identity and online security. Still, businesses must be vigilant and continue to apply comprehensive, data-driven intelligence that helps to thwart both breaches and the malicious use of breached information and to protect all parties’ interests. We recently released a new white paper, Data confidence realized: Leveraging customer intelligence in the age of mass data compromise, to help businesses understand how data and technology are needed to strengthen fraud risk strategies through comprehensive customer intelligence. At its core, reliable customer intelligence is based on high-quality contextual identity and device attributes and other authentication performance data. Customer intelligence provides a holistic, bound-together view of devices and identities that equips companies and agencies with the tools to balance cost and risk without increasing transactional friction and affecting the customer experience. In the age of mass data compromise, however, obtaining dependable information continues to challenge many companies, usually because consumer-provided identities aren’t always unique enough to produce fully confident decisioning. For more information, and to get a better sense of what steps you need to take now, download the full white paper.

Experian data shows consumers are more confident managing their credit since the recession. The Q3 2015 Experian Market Intelligence Brief was released today featuring data that highlights consumer credit card debt has now reached its highest level since Q4 2009. Credit card debt levels reached $650 billion in Q3 2015, the highest it has been since Q4 2009 when it was $667 billion. Credit card delinquency rates on outstanding balances 60 or more days past due have decreased 71 percent during the same time period. Combining those indicators with the national unemployment rate dropping 50 percent during the same span illustrates a positive economic outlook on credit card trends among lenders and consumers. “Overall credit card limits have increased 102 percent since Q4 2009 with $82 billion originated in Q3 2015,” said Kelly Kent, vice president of Experian Decision Analytics. “The increase in limits from lenders and the steady climb in credit card debt combined with exceptional delinquency rates signals greater confidence among consumers as they are showing more assurance in managing their credit since the recession. We expect to see credit card debt increase in Q4 based on historical seasonal trends driven by the holiday shopping season especially with the early positive holiday sales as a sign.” The Q3 2015 Experian Market Intelligence Brief report is now available.

According to the latest Experian State of the Automotive Finance Market report, leases accounted for nearly 27% of all new vehicle transactions in Q3 2015, up from 24.7% the previous year and the highest percentage on record.

Customer Experience during the holiday shopping season During the holidays, consumers transact at a much greater rate than any other time of the year. Many risk-management departments respond by loosening the reins on their decision engines to improve the customer experience — and to ensure that this spike does not trigger a response that would impede a holiday shopper’s desire to grab one more stocking stuffer or a gift for a last-minute guest. As a result, it also is the busy season for fraudsters, and they use this act of goodwill toward your customers to improve their criminal enterprise. Ultimately, you are tasked with providing a great customer experience to your real customers while eliminating any synthetic ones. Recent data breaches resulted in large quantities of personally identifiable information that thieves can use to create synthetic identities being published on the Dark Web. As this data is related to real consumers, it can be difficult for your identity-authentication solution to determine that these identities have been compromised or fabricated, enabling fraudsters to open accounts with your organization. Experian’s Identity Element Network™ can help you determine when synthetic identities are at work within your business. It evaluates nearly 300 data-element combinations to determine if certain elements appear in cyberspace frequently or are being used in combination with data not consistent with your customer’s identity. This proven resource helps you manage fraud across the Customer Life Cycle and hinder the damage that identity thieves cause. Identity Element Network examines a vast attribute repository that grows by more than 2 million transactions each day, revealing up-to-date fraud threats associated with inconsistent or high-risk use of personal identity elements. Our goal is to provide the comfort of knowing that you are transacting with your real customers. Don’t get left in the cold this holiday season — fraudsters are looking for opportunities to take advantage of you and your customers. Contact your Experian account executive to learn how Identity Element Network can help make sure you are not letting fraudsters exploit the customer experience intended for your real customers. Learn more about the delicate balance between customer and criminal by viewing our fraud e-book.

Electronic signatures and their emerging presence in our Internet-connected world I had the opportunity to represent Experian at the eSignRecords 2015 conference in New York City last week. The concept of electronic signature, while not new, certainly has an emerging presence in the Internet-connected world — as evidenced by the various attendee companies that were represented, everything from home mortgages to automobiles. Much of the discussion focused on the legal aspects of accepting an electronic signature in lieu of an in-person physical signature. The implications of accepting this virtual stamp of approval were discussed, as well as the various cases that already have been tried in court. Of course, the outcome of those cases shapes the future of how to properly integrate this new form of authorization into existing business processes. Attendees discussed the basic concept of simply accepting a signature on an electronic pad as opposed to one written on a piece of paper. That act alone has many legal challenges even though it provides the luxury of in-person authentication through a face-to-face meeting. The complexities and risk increase exponentially when these services are extended over the Internet. The ability to sign documents virtually opens up a whole new world of business opportunities, and the concept certainly caters to the consumer’s need for convenience. However, the anonymity of the Internet presents the everyday challenge of balancing consumer expectations of greater ease of use with necessary fraud prevention measures. Ultimately, it always comes back to understanding who is actually signing that document. All of this highlights the need for robust authentication and security measures. As more and more legal documents and contracts are passed around virtually, the opportunity to properly screen and verify who has access to the documents gets more critical. Many organizations still rely on the tried-and-true method of knowledge-based authentication (KBA), while many others have called for its end. KBA continues to soldier on as an effective way to ensure that people on the other end of the wire are who they say they are by asking questions that — presumably — only they know the answers to. In most cases, KBA is viewed as a “check the box” step in the process to satisfy the lawyers. In certain cases, that’s all you need to do to ensure compliance with legal policy or regulatory requirements. It starts to get tricky is when there’s more on the line than just “check the box” actions. When the liability of first- or third-party fraud, becomes greater than simple compliance, it’s time to implement tighter security, while at the same time limiting the amount of friction caused by the process. Many in attendance discussed the need for layers of authentication based on the type of documents that are being processed and handled. This speaks directly to the point that one size does not fit all. As the industry matures and acceptance of e-signatures increases, so too does the need for more robust, flexible options in authentication. Another topic — that was quite frankly foreign to everyone we talked to — was the need for security around the concept of account takeover. When discussing this type of fraud, most attendees did not even consider this to be a hole in their strategy. Consider this fictional scenario. I’m responsible for mergers and acquisitions for my publicly traded company. I often share confidential information via electronic means, leveraging one of the many electronic signature solutions on the market. I become a victim of a phishing attack and unknowingly provide my login credentials to the fraudster. The fraudster now has access to every electronic document that I have shared with various organizations — most of which have been targets for mergers and acquisitions. Fraudsters are creative. They exploit new technologies — not because they’re trendsetters, but because oftentimes these new technologies fail to consider how fraudsters can benefit from the system. If you are considering adopting e-signature as a formal process, please consider implementing: Flexible levels of authentication based on the risk and liability of the documents that are being presented and what they are protecting FraudNet for Account Takeover, which enhances security around access to these critical documents to protect against data breaches Not only the needs and experiences of your own business, but customer needs as well to enable to the best possible customer interactions If you haven’t considered implementing e-signature technology into your business process, you should — but be sure to have your fraud team present when considering the implementation.

Experian® recently released the 2015 State of Credit report, which analyzes key credit metrics across the nation.

We all know that first party fraud is a problem. No one can seem to agree on the definitions of first party fraud and who is on the hook to find it, absorb the losses and mitigate the risk going forward. More often than not, first-party fraud cases and associated losses are simply combined with the relatively big “bucket” of credit losses. More importantly, the means of quickly detecting potential first-party fraud, properly segmenting it (as either true credit risk or malicious behavior) and mitigating losses associated with it usually lies within more general credit policies instead of with unique, targeted strategies designed to combat this type of fraud. In order to create a frame of reference, it’s helpful to have some quick — and yes, arguable — definitions: Synthetic identity: the fabrication of an identity with the intention of perpetrating fraudulent applications for, and access to, credit or other financial services Bust-out: the substantive building of positive credit history, followed by the intentional, high-velocity opening of several new accounts with subsequent line utilization and “never payment” Default payment: intentionally allowing credit lines to default to avoid payments Straight-roller: an account opened with immediate utilization followed by default without any attempt to make a payment Never pay: a form of straight-roller that becomes delinquent within the first few months of opening the account So what’s a risk manager to do? In my opinion, the best methods to consider in the fight against first-party fraud include analytical solutions that take multiple data points into consideration and focus on a risk-based approach. For my money, the four most important are: Models and scores developed with the proper set of identity and credit risk attributes derived from current and historic identity and account usage patterns (in other words, ANALYTICS) — Used at both the account opening and account management phases of the Customer Life Cycle, such analytics can be customized for each addressable market and specific first-party fraud threat The monitoring of individual identity elements at a portfolio level and beyond — This type of monitoring and LINK ANALYSIS allows organizations to detect the creation of synthetic identities Reasonable (e.g., one-to-one) identity and device associations over time versus a cluster of devices or coordinated attacks stemming from a single device — Knowing a customer’s device profile and behavioral usage with DEVICE INTELLIGENCE provides assurance that applications and account access are conducted legitimately Leveraging industry experts who have worked with other institutions to design and implement effective first-party fraud detection and loss-mitigation strategies — This kind of OPERATIONAL CONSULTING can save time and money in the long run and afford an opportunity to avoid mistakes By active use of these methods, you are applying a risk-based approach that will allow you to realize substantial savings in the forms of loss reduction and operational efficiencies associated with non-acquisition of high-risk first-party fraud applications, more effective credit line management of potentially high-risk accounts, better segmentation of treatment strategies and associated spend against high-risk identities, and removal of first-party fraud accounts from traditional collections processes that will prove futile. Download our recent White Paper, Data confidence realized: Leveraging customer intelligence in the age of mass data compromise, to understand how data and technology are needed to strengthen fraud risk strategies through comprehensive customer intelligence.

With Black Friday quickly approaching, a recent Experian study shows online Black Friday searches are already tracking ahead of last year. This October, the weekly search share for Black Friday averaged 12% higher than October 2014 and is expected to increase dramatically between now and Thanksgiving week. Top product searches for the week ending October 31, 2015 include: Marketers can design more successful campaigns and maximize rewards for both consumers and brands by staying on top of the latest search trends. >> Holiday Hot Sheet

Profile of an online fraudster I recently read a study about the profile of a cybercriminal. While I appreciate the study itself, one thing it lacks perspective on is an understanding of how identity data is being used to perpetrate fraud in the online channel. One may jump to conclusions about what is a good indicator for catching fraudsters. These very broad-brush observations may result in an overwhelming number of false positives without digging in deeper. Purchase value A single approach for understanding the correlation between purchase value and fraud does not work to best protect all businesses. Back in 2005, we saw that orders under $5 were great indicators of subsequent large-ticket fraud. For merchants that sell large-ticket items, such as electronics, those same rules may not be effective. To simply believe that the low dollar amount is the extent of the crime and not just a precursor to the real, bigger crime indicates a lack of understanding of how fraudsters work to manipulate a system. For some merchants, where fraudsters know they can go to do card testing against their business, low-dollar-amount rules may apply. However, for other businesses a different set of rules must be put into place. Time of day We have been tracking fraud time of day as a rule since 2004, but the critical point is a clear definition of which time of day. For the merchant, 3 a.m. is very different than 3 a.m. for a fraudster who is in Asia or Eastern Europe, where 3 a.m. merchant time is actually the middle of the online fraudster’s day. FraudNet is designed to identify the time from the user’s device and runs its rules from the user’s time. We find that every individual business will have a very specific threat profile. Businesses need to build their individual fraud strategy around their overall attack rate taking into account the strength of the defense and the ability to be flexible to accommodate the nuances for individual consumers. A general approach to fraud mitigation inevitably results in a system that begins to chase broad averages, which leads to excessive false positives and mediocre detection. That’s what drives us to do the job better. The proof of every fraud solution should lie in its ability to catch the most fraud without negatively impacting good customers.  

According to a recent survey commissioned by VantageScore® Solutions, millennials cite being unscoreable as the main obstacle to credit access. Among the findings: One-third of millennials cannot obtain the credit they need Of those unable to obtain credit, 34% attribute it to lack of a credit score 49% of millennials agree that competition in the credit-scoring marketplace is beneficial Lenders can help this segment and open the gateway of credit by using advanced risk models that can accurately score consumers considered unscoreable by conventional risk models. >> Infographic: The Giant Credit Gap VantageScore® is a registered trademark of VantageScore Solutions, LLC.