Tag: customer experience
It seems like artificial intelligence (AI) has been scaring the general public for years – think Terminator and SkyNet. It’s been a topic that’s all the more confounding and downright worrisome to financial institutions. But for the 30% of financial institutions that have successfully deployed AI into their operations, according to Deloitte, the results have been anything but intimidating. Not only are they seeing improved performance but also a more enhanced, positive customer experience and ultimately strong financial returns. For the 70% of financial institutions who haven’t started, are just beginning their journey or are in the middle of implementing AI into their operations, the task can be daunting. AI, machine learning, deep learning, neural networks—what do they all mean? How do they apply to you and how can they be useful to your business? It’s important to demystify the technology and explain how it can present opportunities to the financial industry as a whole. While AI seems to have only crept into mainstream culture and business vernacular in the last decade, it was first coined by John McCarthy in 1956. A researcher at Dartmouth, McCarthy thought that any aspect of learning or intelligence could be taught to a machine. Broadly, AI can be defined as a machine’s ability to perform cognitive functions we associate with humans, i.e. interacting with an environment, perceiving, learning and solving problems. Machine learning vs. AI Machine learning is not the same thing as AI. Machine learning is the application of systems or algorithms to AI to complete various tasks or solve problems. Machine learning algorithms can process data inputs and new experiences to detect patterns and learn how to make the best predictions and recommendations based on that learning, without explicit programming or directives. Moreover, the algorithms can take that learning and adapt and evolve responses and recommendations based on new inputs to improve performance over time. These algorithms provide organizations with a more efficient path to leveraging advanced analytics. Descriptive, predictive, and prescriptive analytics vary in complexity, sophistication, and their resulting capability. In simplistic terms, descriptive algorithms describe what happened, predictive algorithms anticipate what will happen, and prescriptive algorithms can provide recommendations on what to do based on set goals. The last two are the focus of machine learning initiatives used today. Machine learning components - supervised, unsupervised and reinforcement learning Machine learning can be broken down further into three main categories, in order of complexity: supervised, unsupervised and reinforcement learning. As the name might suggest, supervised learning involves human interaction, where data is loaded and defined and the relationship to inputs and outputs is defined. The algorithm is trained to find the relationship of the input data to the output variable. Once it delivers accurately, training is complete, and the algorithm is then applied to new data. In financial services, supervised learning algorithms have a litany of uses, from predicting likelihood of loan repayment to detecting customer churn. With unsupervised learning, there is no human engagement or defined output variable. The algorithm takes the input data and structures it by grouping it based on similar characteristics or behaviors, without a defined output variable. Unsupervised learning models (like K-means and hierarchical clustering) can be used to better segment or group customers by common characteristics, i.e. age, annual income or card loyalty program. Reinforcement learning allows the algorithm more autonomy in the environment. The algorithm learns to perform a task, i.e. optimizing a credit portfolio strategy, by trying to maximize available rewards. It makes decisions and receives a reward if those actions bring the machine closer to achieving the total available rewards, i.e. the highest acquisition rate in a customer category. Over time, the algorithm optimizes itself by correcting actions for the best outcomes. Even more sophisticated, deep learning is a category of machine learning that involves much more complex architecture where software-based calculators (called neurons) are layered together in a network, called a neural network. This framework allows for much broader, complex data ingestion where each layer of the neural network can learn progressively more complex elements of the data. Object classification is a classic example, where the machine ‘learns’ what a duck looks like and then is able to automatically identify and group images of ducks. As you might imagine, deep learning models have proved to be much more efficient and accurate at facial and voice recognition than traditional machine learning methods. Whether your financial institution is already seeing the returns for its AI transformation or is one of the 61% of companies investing in this data initiative in 2019, having a clear picture of what is available and how it can impact your business is imperative. How do you see AI and machine learning impacting your customer acquisition, underwriting and overall customer experience?
Over the years, businesses have gathered a plethora of datasets on their customers. However, there is no value in data alone. The true value comes from the insights gained and actions that can be derived from these datasets. Advanced analytics is the key to understanding the data and extracting the critical information needed to unlock these insights. AI and machine learning in particular, are two emerging technologies with advanced analytics capabilities that can help companies achieve their business goals. According to an IBM survey, 61% of company executives indicated that machine learning and AI are their company’s most significant data initiatives in 2019. These leaders recognize that advanced analytics is transforming the way companies traditionally operate. It is no longer just a want, but a must. With a proper strategy, advanced analytics can be a competitive differentiator for your financial institution. Here are some ways that advanced analytics can empower your organization: Provide Personalized Customer Experiences Business leaders know that their customers want personalized, frictionless and enhanced experiences. That’s why improving the customer experience is the number one priority for 80 percent of executives globally, according to an Experian study. The data is already there – companies have insights into what products their customers like, the channels they use to communicate, and other preferences. By utilizing the capabilities of advanced analytics, companies can extract more value from this data and gain better insights to help create more meaningful, personalized and profitable lending decisions. Reduce Costs Advanced analytics allows companies to deploy new models and strategies more efficiently – reducing expenses associated with managing models for multiple lending products and bureaus. For example, OneMain Financial, was able to successfully drive down risk modeling expenses after implementing a solution with advanced analytics capabilities. Improve Accuracy and Speed to Market To stay ahead of the competition, companies need to maintain fast-moving environments. The speed, accuracy and power of a company’s predictive models and forecasts are crucial for success. Being able to respond to changing market conditions with insights derived from advanced analytics is a key differentiator for future-forward companies. Advanced analytic capabilities empower companies to anticipate new trends and drive rapid development and deployment, creating an agile environment of continual improvement. Drive Growth and Expand Your Customer Base With the rise of AI, machine learning and big data, the opportunities to expand the credit universe is greater than ever. Advanced analytic capabilities allow companies to scale datasets and get a bird’s eye view into a consumer’s true financial position – regardless of whether they have a credit history. The insights derived from advanced analytics opens doors for thin file or credit invisible customers to be seen – effectively allowing lenders to expand their customer base. Meet Compliance Requirements Staying on top of model risk and governance should always remain top of mind for any institution. Analytical processing aggregates and pulls new information from a wide range of data sources, allowing your institution to make more accurate and faster decisions. This enables lenders to lend more fairly, manage models that stand up to regulatory scrutiny, and keep up with changes in reporting practices and regulations. Better, faster and smarter decisions. It all starts with advanced analytics. Businesses must take advantage of the opportunities that come with implementing advanced analytics, or risk losing their customers to more future-forward organizations. At Experian, we believe that using big data can help power opportunities for your company. Learn how we can help you leverage your data faster and more effectively. Learn More
A few months ago, I got a letter from the DMV reminding me that it was finally time to replace my driver’s license. I’ve had it since I was 21 and I’ve been dreading having to get a new one. I was especially apprehensive because this time around I’m not just getting a regular old driver’s license, I’m getting a REAL ID. For those of you who haven’t had this wonderful experience yet, a REAL ID is the new form of driver’s license (or state ID) that you’ll need to board a domestic flight starting October 1, 2020. Some states already offered compliant IDs, but others—like California, where I’m from—didn’t. This means that if I want to fly within the U.S. using my driver’s license next year, I can’t renew by mail. It’s Easier Than It Looks Imagine my surprise when I started the process to schedule my appointment, and the California DMV website made things really easy! There’s an online application you can fill out before you get to the DMV and they walk you through the documents to bring to the appointment (which I was able to schedule online). Despite common thought that the DMV and agencies like it are slow to adopt technology, the ease of this process may indicate a shift toward a digital-first mindset. As financial institutions embrace a similar shift, they’ll be better positioned to meet the needs of customers. Case in point, the electronic checklist the DMV provided to prepare me for my appointment. I sailed through the first two parts of the checklist, confirming that I’ll bring my proof of identity and social security number, but I paused when I got to the “Two Proofs of Residency” screen. Like many people my age—read: 85% of the millennial population, according to a recent Experian study—I don’t have a mortgage or any other documents relating to property ownership. I also don’t have my name on my utilities (thanks, roomie) or my cell phone bill (thanks Mom). I do however have a signed lease with my name on it, plus my renter’s insurance, both of which are acceptable as proof of residency. And just like that, I’m all set to get my REAL ID, even though I don’t have some of the basic adulting documents you might expect, because the DMV took into account the fact that not all REAL ID applicants are alike. Imagine if lenders could adopt that same flexibility and create opportunities for the more than 45 million U.S. consumers1 who lack a credit report or have too little information to generate a credit score. The Bigger Picture By removing some of the usual barriers to entry, the DMV made the process of getting my REAL ID much easier than it might have been and corrected my assumptions about how difficult the process would be. Experian has the same line of thought when it comes to helping you determine whether a borrower is credit-worthy. Just because someone doesn’t have a credit card, auto loan or other traditional credit score contributor doesn’t mean they should be written off. That’s why we created Experian BoostTM, a product that lets consumers give read-only access to their bank accounts and add in positive utility and telecommunications bill payments to their credit file to change their scores in real time and demonstrate their stability, ability and willingness to repay. It’s a win-win for lenders and consumers. 2 out of 3 users of Experian Boost see an increase in their FICO Score and of those who saw an increase, 13% moved up a credit tier. This gives lenders a wider pool to market to, and thanks to their improved credit scores, those borrowers are eligible for more attractive rates. Increasing your flexibility and removing barriers to entry can greatly expand your potential pool of borrowers without increasing your exposure to risk. Learn more about how Experian can help you leverage alternative credit data and expand your customer base in our 2019 State of Alternative Data Whitepaper. Read Full Report 1Kenneth P. Brevoort, Philipp Grimm, Michelle Kambara. “Data Point: Credit Invisibles.” The Consumer Financial Protection Bureau Office of Research. May 2015.
The future is, factually speaking, uncertain. We don\'t know if we\'ll find a cure for cancer, the economic outlook, if we\'ll be living in an algorithmic world or if our work cubical mate will soon be replaced by a robot. While futurists can dish out some exciting and downright scary visions for the future of technology and science, there are no future facts. However, the uncertainty presents opportunity. Technology in today\'s world From the moment you wake up, to the moment you go back to sleep, technology is everywhere. The highly digital life we live and the development of our technological world have become the new normal. According to The International Telecommunication Union (ITU), almost 50% of the world\'s population uses the internet, leading to over 3.5 billion daily searches on Google and more than 570 new websites being launched each minute. And even more mind-boggling? Over 90% of the world\'s data has been created in just the last couple of years. With data growing faster than ever before, the future of technology is even more interesting than what is happening now. We\'re just at the beginning of a revolution that will touch every business and every life on this planet. By 2020, at least a third of all data will pass through the cloud, and within five years, there will be over 50 billion smart connected devices in the world. Keeping pace with digital transformation At the rate at which data and our ability to analyze it are growing, businesses of all sizes will be forced to modify how they operate. Businesses that digitally transform, will be able to offer customers a seamless and frictionless experience, and as a result, claim a greater share of profit in their sectors. Take, for example, the financial services industry - specifically banking. Whereas most banking used to be done at a local branch, recent reports show that 40% of Americans have not stepped through the door of a bank or credit union within the last six months, largely due to the rise of online and mobile banking. According to Citi\'s 2018 Mobile Banking Study, mobile banking is one of the top three most-used apps by Americans. Similarly, the Federal Reserve reported that more than half of U.S. adults with bank accounts have used a mobile app to access their accounts in the last year, presenting forward-looking banks with an incredible opportunity to increase the number of relationship touchpoints they have with their customers by introducing a wider array of banking products via mobile. Be part of the movement Rather than viewing digital disruption as worrisome and challenging, embrace the uncertainty and potential that advances in new technologies, data analytics and artificial intelligence will bring. The pressure to innovate amid technological progress poses an opportunity for us all to rethink the work we do and the way we do it. Are you ready? Learn more about powering your digital transformation in our latest eBook. Download eBook Are you an innovation junkie? Join us at Vision 2020 for future-facing sessions like: - Cloud and beyond - transforming technologies - ML and AI - real-world expandability and compliance
Today is National Fintech Day – a day that recognizes the ever-important role that fintech companies play in revolutionizing the customer experience and altering the financial services landscape. Fintech. The word itself has become synonymous with constant innovation, agile technology structures and being on the cusp of the future of finance. Fintech challengers are disrupting existing financial models by leveraging data, advanced analytics and technology – both inspiring traditional financial institutions in their digital transformation strategies and giving consumers access to a variety of innovative financial products and services. But to us at Experian, National Fintech Day means more than just financial disruption. National Fintech Day represents the partnerships we have carefully fostered with our fintech clients to drive financial inclusion for millions of people around the globe and provide consumers with greater control and more opportunities to access the quality credit they deserve. “We are actively seeking out unresolved problems and creating products and technologies that will help transform the way businesses operate and consumers thrive in our society. But we know we can’t do it alone,” said Experian North American CEO, Craig Boundy in a recent blog article on Experian’s fintech partnerships. “That’s why over the last year, we have built out an entire team of account executives and other support staff that are fully dedicated to developing and supporting partnerships with leading fintech companies. We’ve made significant strides that will help us pave the way for the next generation of lending while improving the financial health of people around the world.” At Experian, we understand the challenges fintechs face – and our real-world solutions help fintech clients stay ahead of constantly changing market conditions and demands. “Experian’s pace of innovation is very impressive – we are helping both lenders and consumers by delivering technological solutions that make the lending ecosystem more efficient,” said Experian Senior Account Executive Warren Linde. “Financial technology is arguably the most important type of tech out there, it is an honor to be a part of Experian’s fintech team and help to create a better tomorrow.” If you’d like to learn more about Experian’s fintech solutions, visit us at Experian.com/Fintech.
The fact that the last recession started right as smartphones were introduced to the world gives some perspective into how technology has changed over the past decade. Organizations need to leverage the same technological advancements, such as artificial intelligence and machine learning, to improve their collections strategies. These advanced analytics platforms and technologies can be used to gauge customer preferences, as well as automate the collections process. When faced with higher volumes of delinquent loans, some organizations rapidly hire inexperienced staff. With new analytical advancements, organizations can reduce overhead and maintain compliance through the collections process. Additionally, advanced analytics and technology can help manage customers throughout the customer life cycle. Let’s explore further: Why use advanced analytics in collections? Collections strategies demand diverse approaches, which is where analytics-based strategies and collections models come into play. As each customer and situation differs, machine learning techniques and constraint-based optimization can open doors for your organization. By rethinking collections outreach beyond static classifications (such as the stage of account delinquency) and instead prioritizing accounts most likely to respond to each collections treatment, you can create an improved collections experience. How does collections analytics empower your customers? Customer engagement, carefully considered, perhaps comprises the most critical aspect of a collections program—especially given historical perceptions of the collections process. Experian recently analyzed the impact of traditional collections methods and found that three percent of card portfolios closed their accounts after paying their balances in full. And 75 percent of those closures occurred shortly after the account became current. Under traditional methods, a bank may collect outstanding debt but will probably miss out on long-term customer loyalty and future revenue opportunities. Only effective technology, modeling and analytics can move us from a linear collections approach towards a more customer-focused treatment while controlling costs and meeting other business objectives. Advanced analytics and machine learning represent the most important advances in collections. Furthermore, powerful digital innovations such as better criteria for customer segmentation and more effective contact strategies can transform collections operations, while improving performance and raising customer service standards at a lower cost. Empowering consumers in a digital, safe and consumer-centric environment affects the complete collections agenda—beginning with prevention and management of bad debt and extending through internal and external account resolution. When should I get started? It’s never too early to assess and modernize technology within collections—as well as customer engagement strategies—to produce an efficient, innovative game plan. Smarter decisions lead to higher recovery rates, automation and self-service tools reduce costs and a more comprehensive customer view enhances relationships. An investment today can minimize the negative impacts of the delinquency challenges posed by a potential recession. Collections transformation has already begun, with organizations assembling data and developing algorithms to improve their existing collections processes. In advance of the next recession, two options present themselves: to scramble in a reactive manner or approach collections proactively. Which do you choose? Get started
While it’s a word that has only recently made its way into financial circles, consumers and businesses alike have been enjoying life in a platform world. Digital platforms connect riders with drivers, friends with family, manufacturers with buyers and sellers, and the list goes on. Digital platforms are technology-enabled business models that work to enhance efficiency, flexibility, scalability, integration, and ultimately user engagement. They’re integral to the operation and success of some of the most valuable companies in the world, including Google, Facebook, and Amazon. While digital platforms have made their way beyond high-tech to other industries, like supply chain management and logistics, financial institutions have fallen behind. The reasons why are understandable: a quickly evolving marketplace, regulatory induced risk aversion, and the need to protect data and privacy. Most of the digital platform adoption that has occurred in the financial industry has revolved around open banking, with a focus on enriching the customer experience. BBVA, for instance, recently launched a platform to enable their business clients to use white-labeled versions of BBVA products and services on-demand. But the value of digital platforms for the financial industry can go beyond how the consumer interfaces with his or her bank or credit union. Financial institutions could see the same efficiency, flexibility, and integration benefits by implementing technology platforms into their internal systems. Traditionally, financial institutions have used contrasting technology and systems across their customers’ lifecycle. From financial marketing and targeting, to acquisition and underwriting, there is ample opportunity to streamline and integrate these systems by adopting a platform architecture. The most future-forward platforms not only enable financial institutions to integrate their internal systems, but they also allow companies to seamlessly integrate their customer data with third-party data resources. The powers of data-driven answers combined with platform technology can help overcome business challenges and satisfy consumer and client demands. Is it time you and your company stepped up to the platform?
2018 was a whirlwind of a year – though it was not surprising when Google’s 2018 “most-searched” list showed Fornite GIFs ruled the internet, Black Panther was the most-Googled movie, and the Keto diet was trending (particularly in late December and early January, go figure). But, while Google’s most-searched terms of 2018 present pure pop-culture entertainment, they miss the mark on the trends we find most meaningful being principals of the financial services industry. What about the latest news in fintech? According to Business Insider, fintech companies secured $57.9 billion in funding in the first half of 2018 alone, nearing the previous annual record of $62.5 billion set in 2015. Taking it a step further, CBInsights reports that 24 of 39 fintech unicorns are based in North America. We won’t blame Google for this oversight. Faced with the harsh reality that the “most-searched” results are based on raw-data, perhaps it’s possible that people really do find Fortnite more exciting than financial services trends – but not us at Experian. We have been closely following disruption in the financial services space all while leading the charge in data innovation. When competing in environments where financial institutions vie for customer acquisition and brand loyalty, digital experience is not enough. Today’s world demands finance redefined – and fintechs have answered the call. Fintechs are, by far, among the most innovative technology and data-driven companies in the financial services industry. That’s why we built a team of seasoned consultants, veteran account executives and other support staff that are 100% dedicated to supporting our fintech partners. With our expert team and a data accuracy rate of 99.9%, there isn’t a more reliable fintech source. Perhaps this is one financial services trend that Google can’t ignore (we see you Google)! For more information regarding Experian’s fintech solutions, check out our video below and visit Experian.com/fintech.
The business case for identity verification and risk assessment tools is most compelling when it includes a broad range of both direct and indirect factors. Here are 3 indirect measures we suggest you consider: Customer experience improvement — With 72% of businesses focused on service, according to Forrester Research,* the value of reduced friction can’t be overstated Reputation and brand protection — The monetary cost of fraud losses can be high, but the impact on customer relationships and brand integrity can be even higher. Compliance — Noncompliance costs an average of 2.65 times more than investing in a technology-based compliance solution. Justifying investment in fraud prevention technology can be challenging. A business case built on the right data can pave the way to upgrading your identity verification and risk assessment technology. Learn more in our buyer\'s guide>
It’s clear the digital marketplace is here to stay. Online activities among consumers reflect the increased adoption of digital commerce. In fact, recent findings from our 2018 Global Fraud and Identity Report show the top activity on mobile devices is online shopping, followed closely by personal banking. Consumers trust technology and, by proxy, the businesses that help enable it. It’s critical for organizations to continue to build trust online without disrupting the consumer experience. It’s the goal — and the responsibility — of businesses. Learn more
For most businesses, the customer experience is at the heart of every strategy. Debt collection shouldn’t be different. Here’s why: 21% of visits to an online debt recovery system were made outside the traditional working hours of 8 a.m. to 8 p.m. Of the consumers who committed to a repayment plan, only 56% did so in a single visit. PricewaterhouseCoopers reported that 46% of consumers use only digital channels to conduct banking, avoiding traditional offline channels. Conversely, data collected by Gallup between 2013 and 2016 showed that 48% of American banking customers would only consider using a bank that offered physical branches. The debt collection process is an often-overlooked opportunity to build customer relationships and loyalty. Leverage data and technology to replace outdated approaches, minimize charge-offs and create environments that value each customer. Learn more>
Everyone loves a story. Correction, everyone loves a GOOD story. A customer journey map is a fantastic tool to help you understand your customer’s story from their perspective. Perspective being the operative word. This is not your perspective on what YOU think your customer wants. This is your CUSTOMER’S perspective based on actual customer feedback – and you need to understand where they are from those initial prospecting and acquisition phases all the way through collections (if needed). Communication channels have expanded from letters and phone calls to landlines, SMS, chat, chat bots, voicemail drops, email, social media and virtual negotiation. When you create a customer journey map, you will understand what channel makes sense for your customer, what messages will resonate, and when your customer expects to hear from you. While it may sound daunting, journey mapping is not a complicated process. The first step is to simply look at each opportunity where the customer interacts with your organization. A best practice is to include every department that interacts with the customer in some way, shape or form. When looking at those touchpoints, it is important to drill down into behavior history (why is the customer interacting), sociodemographic data (what do you know about this customer), and customer contact patterns (Is the customer calling in? Emailing? Tweeting?). Then, look at your customer’s experience with each interaction. Again, from the customer’s viewpoint: Was it easy to get in touch with you? Was the issue resolved or must the customer call back? Was the customer able to direct the communication channel or did you impose the method? Did you offer self-serve options to the right population? Did you deliver an email to someone who wanted an email? Do you know who prefers to self-serve and who prefers conversation with an agent, not an IVR? Once these two points are defined: when the customer interacts and the customer experience with each interaction, the next step is simply refining your process. Once you have established your baseline (right channel, right message, right time for each customer), you need to continually reassess your decisions. Having a system in place that allows you to track and measure the success of your communication campaigns and refine the method based on real-time feedback is essential. A system that imports attribute – both risk and demographic – and tracks communication preferences and campaign success will make for a seamless deployment of an omnichannel strategy. Once deployed, your customer’s experience with your company will be transformed and they will move from a satisfied customer to one that is a fan and an advocate of your brand.
Newest technology doesn’t mean best when it comes to stopping fraud I recently attended the Merchant Risk Conference in Las Vegas, which brings together online merchants and industry vendors including payment service providers and fraud detection solution providers. The conference continues to grow year to year – similar to the fraud and risk challenges within the industry. In fact, we just released analysis, that we’ve seen fraud rates spike to 33% in the past year. This year, the exhibit hall was full of new names on the scene – evidence that there is a growing market for controlling risk and fraud in the e-commerce space. I heard from a few merchants at the conference that there were some “cool” new technologies out to help combat fraud. Things like machine learning, selfies and other two-factor authentication tools were all discussed as the latest in the fight against fraud. The problem is, many of these “cool” new technologies aren’t yet efficient enough at identifying and stopping fraud. Cool, yes. Effective, no. Sure, you can ask your customer to take a selfie and send it to you for facial recognition scanning. But, can you imagine your mother-in-law trying to manage this process? Machine Learning, while very promising, still has some room to grow in truly identifying fraud while minimizing the false positives. Many of these “anomaly detection” systems look for just that – anomalies. The problem is, we’re fighting motivated and creative fraudsters who are experts at avoiding detection and can beat anomaly detection. I do not doubt that you can stop fraud if you introduce some of these new technologies. The problem is, at what cost? The trick is stopping fraud with efficiency – to stop the fraud and not disrupt the customer experience. Companies, now more than ever, are competing based on customer experience. Adding any amount of friction to the buying process puts your revenue at risk. Consider these tips when evaluating and deploying fraud detection solutions for your online business. Evaluate solutions based on all metrics What is the fraud detection rate? What impact will it have on approvals? What is the false positive rate and impact on investigations? Does the attack rate decline after implementing the solution? Is the process detectable by fraudsters? What friction is introduced to the process? Use all available data at your disposal to make a decision Does the consumer exist? Can we validate the person’s identity? Is the web-session and user-entered data consistent with this consumer? Step up authentication but limit customer friction Is the technology appropriate for your audience (i.e. a selfie, text-messaging, document verification, etc...)? Are you using jargon in your process? In the end, any solution can stop 100% of the fraud – but at what cost. It’s a balance - a balance between detection and friction. Think about customer friction and the impact on customer satisfaction and revenue.
Happy holidays! It’s the holiday season and a festive time of year. Colorful lights, comfort food and holiday songs – all of these things contribute to the celebratory atmosphere which causes many people to let their guards down and many businesses to focus more on service than on risk. Unfortunately, fraudsters and other criminals can make one of the busiest shopping times of the year, a miserable one for their victims. The nature of the stolen data has the potential to create long-term headaches for the organization and tens of millions of individuals. Unlike a retailer or financial breach, where stolen payment cards can be deactivated and new ones issued, the theft of permanent identity information is, well, not easily corrected. You can’t simply reissue Social Security numbers, birth dates, names and addresses. For individuals, we need to internalize this fact: our data has likely been breached, and we need to become vigilant and defend ourselves. Sign-up for a credit monitoring service to be alerted if your data or ID is being used in ways that indicate fraud. Include your children, as well. A child’s identity is far more valuable to a fraudster as they know it can be several years before their stolen identity is detected. The good news is, in addition to the credit bureau, many banks and auto clubs now offer this as a service to their customers. For organizations, the focus should be on two fronts: data protection and fraud prevention. Not just to prevent financial theft, but to preserve trust — trust between organizations and consumers, as well as widespread consumer trust. Organizations must strive to evolve data protection controls and fraud prevention skills to minimize the damage caused by stolen identity data. There are dozens of tools in the industry for identifying that a consumer is who they say they are – and these products are an important part of any anti-fraud strategy. These options may tell you that the combination of elements is the consumer, but do you know that it is the REAL consumer presenting them? The smart solution is to use a broad data set for not only identity verification, but also to check linkage and velocity of use. For example: Is the name linking to other addresses being presented in the past week? Is the phone number showing up to other addresses and names over the past 30 days? Has the SSN matched to other names over the past 90 days? Since yesterday the address matches to four phone numbers and two names – is this a problem? And it must be done in ways that reinforce the trust between consumers and organizations, enhance the customer experience, and frustrate criminals. Click here to learn more about Experian’s products and services that can help. As we go walking in the winter wonderland, remember, the holiday season is a time for cheer… and vigilance!
Since 1948, International Credit Union Day – a time to recognize the credit union movement – has been celebrated the third Thursday of October. The day is the perfect time to remind your members and consumers about all of the services and benefits your credit union offers. This year’s theme, “The Authentic Difference,” celebrates what makes credit unions stand out. Here are 10 reasons CUs deserve a spotlight: Credit unions are non-profit cooperatives, owned and operated by its members. That means they emphasize consumer value to more than 217 million members worldwide. Profits go back to members in the form of reduced fees, higher savings rates and lower loan rates. Personal relationships are key. Credit unions pride themselves on developing relationships with their members, and CUs are typically staffed by friendly reps who know customers by name. Checking accounts are free. Roughly 80 percent of credit unions offer free checking accounts, compared to less than 50 percent of banks, according to economic research firm Moebs Services. Few ATM fees. Many credit union customers are able to avoid ATM fees because CUs typically give them access to a large network of ATMs by sharing branches and other resources. Savings rates are above average. Because credit unions don\'t have to pay dividends to shareholders and are exempt from federal taxes they can offer high rates on saving accounts. The average credit union offers CD, money market, and savings rates well above the national banking rates average. Lower interest rates. Credit unions offer lower interest rates on some loans. The difference between banks and credit unions was greatest in car-loan interest rates, according to a September report by SNL Financial. The average 36-month used-car loan interest rate offered by CUs was 2.67 percent compared to 4.45 percent for banks. For new-car loans, CUs offered an average interest rate for 48 months of 2.60 percent compared to 3.94 percent for banks. Invested in the community. A credit union’s core values are focused on its members and the communities where they live and work. Many provide financial education and outreach to consumers. It’s easier to get credit. CUs don’t have to abide by loan restrictions and qualifications mandated by a corporate office, so they have more flexibility to make loans when possible. Small-business support: CUs may know borrowers and are able to take into account intangibles like community reputation and accountability. Also, they understand the value to the community of a small business, its market and credit needs. Joining is easy. Many credit unions base eligibility simply on where you live, instead of restricting membership to a particular employer. Since expanding eligibility, credit union membership has grown by about two percent a year for the past decade.
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