Tag: technology
DDigitalization, also known as the process of using digital technology to provide new opportunities for revenue and growth, continues to remain a top priority for many organizations in 2021. In fact, IDC predicts that by 2024, “over 50% of all IT spending will be directly for digital transformation and innovation (up from 31% in 2018).”[1] By combining data and analytics, companies can make better and more instant decisions, meet customer expectations, and automate for greater efficiency. Advances in AI and machine learning are just a few areas where companies are shifting their spend. Download our new white paper to take a deep dive into other ongoing analytics trends that seem likely to gain even greater traction in 2021. These trends will include: Increased digitalization – Data is a company’s most valuable asset. Companies will continue utilizing the information derived from data to make better data-driven decisions. AI for credit decisioning and personalized banking – Artificial intelligence will play a bigger role in the world of lending and financial services. By using AI and custom machine learning models, lending institutions will be able to create new opportunities for a wider range of consumers. Chatbots and virtual assistants – Because customers have come to expect excellent customer services, companies will increase their usage of chatbots and virtual assistants to facilitate conversations. Cloud computing – Flexible, scalable, and cost-effective. Many organizations have already seen the benefits of migrating to the cloud – and will continue their transition in the next few years. Biometrics – Physical and behavioral biometrics have been identified as the next big step for cybersecurity. By investing in these new technologies, companies can create seamless interactions with their consumers. Download Now [1] Gens, F., Whalen, M., Carnelley, P., Carvalho, L., Chen, G., Yesner, R., . . . Wester, J. (2019, October). IDC FutureScape: Worldwide IT Industry 2020 Predictions. Retrieved January 08, 2021,
Experian recently announced the new members named to its Fintech Advisory Board. The board and its members provide Experian with valuable insights and key perspectives into the unique and quickly evolving needs of the fintech industry. “For years Experian has been committed to partnering with innovators in the fintech industry to bring better opportunities to businesses and consumers alike,” said Experian North American CEO Craig Boundy. “We appreciate the thought leadership we get from our Fintech Advisory Board members and the challenge and the push that comes along with it,” he said. The board met virtually last month, welcoming representatives from across the fintech ecosystem representing payments, personal and secured loan lenders, credit card issuers, investors and others. “This was my first board meeting with Experian, and I’m very pleased to see the investment Experian has put into being the best of the three major bureaus in having the best technology to enable us to turnaround our models more quickly, and better data and alternative data sources like Boost,” said one of the new executives appointed to the board. “We are delighted to gather this group of innovators together to ensure we are consistently meeting the needs of our fintech partners,” said Experian Vice President Jon Bailey, who oversees the fintech vertical. “Now more than ever it’s important that we work alongside them in shaping the industry and helping them meet their goals for the future,” he said. Experian’s fintech vertical provides leading-edge solutions and data across the credit lifecycle specifically designed to impact Fintech and marketplace lending companies and their customers. For more information on Experian’s fintech services or the advisory board, click here.
The COVID-19 pandemic and resulting rush to transition to a remote lifestyle made it clear that many businesses need a refreshed digital authentication and fraud prevention strategy that includes an investment in technology and provides consumer assurance. This is particularly important when it comes to identity, as many of the standard in-person verification methods and tools are currently unavailable. The meaning of identity is growing and shifting Technology trends are intersecting with social trends to create heightened awareness, and a whole new public conversation has emerged around customer trust and privacy. Attitudes and ideas are changing—even to the point of what we mean by “identity.” An identity is no longer just a name, date of birth, and SSN. Now, there are digital manifestations everywhere you look: screen names, email addresses, mobile phone numbers, device identifiers, and the other “exhaust” we leave behind as we travel the internet. This leads to concerns about what an identity is, who owns it, and who manages and protects it. Businesses have to be able to prove to their ability to protect their customers’ identities through investment in technology and a robust fraud strategy. Consumer attitudes are changing Several years ago, consumers were excited by all the new digital capabilities and the speed, ease, and convenience they provided. Last year, Experian found that consumers still wanted those things, with 70% willing to provide more information to businesses if there was a perceived benefit. However, they also wanted more security in the balance. In Experian’s most recent Global Identity and Fraud Report, we found that 74% of consumers say that security is the most important factor when deciding to engage with a business. Consumers are particularly more tolerant of friction during the enrollment process—as a means of building trust. But, when they return to the app or website, they want to be recognized. This means achieving a balance by using layered technologies, some of which are active and visible to the consumer, and some of which are invisibly working in the background to confirm the identity of returning consumers. Consumer attitudes vs. regulatory pressure The drivers behind the business changes are twofold: shifting consumer attitudes and regulatory changes. While regulations are becoming stricter on a national and global level, they’re not keeping pace with technology and social change. The digital world is evolving at a rapid pace, opening up more new ways for companies to collect information about consumers and use it to identify and verify, and also to target goods and services. With all of this data available, it’s important for businesses to use the tools in the market to help protect identity information. Next steps in technology The bottom line is, businesses can’t wait for regulations to dictate how best to protect information. Instead, they should be looking to technologies like physical and behavioral biometrics to help provide identity authentication and protection – layering those solutions with information from the user and from third parties to give a holistic consumer view. Businesses should adopt a platform approach for identity and fraud in order to be able to adapt quickly, whether to incorporate new kinds of technology or to prevent emerging types of fraud. By investing in technology now, even in the midst of the COVID-19 pandemic, businesses can build the flexibility needed to respond to future crises and help offset future fraud losses. In turn, those fraud-loss savings can then be used to help grow the business in the future. Learn more about Experian’s commitment to helping businesses maximize their investment in technology to safeguard against fraud. Learn more
This week, Experian released a new version of our CrossCore® digital identity and fraud risk platform, adding new tools and functionality to help businesses quickly respond to today’s emerging fraud threats. The ability to confidently recognize your customers and safeguard their digital transactions is becoming an increasing challenge for businesses. Fraud threats are already rising across the globe as fraudsters take advantage of the global health crisis and rapidly shifting economic conditions. CrossCore combines risk-based authentication, identity proofing and fraud detection into a single cloud platform, which means businesses can more quickly respond to an ever-changing environment. And with flexible decisioning orchestration and advanced analytics, businesses can make real-time risk decisions throughout the customer lifecycle. “Now more than ever, businesses need to lean on capabilities and technology that will allow them to rapidly respond in these challenging times, increase identity confidence in every transaction, and provide a safe and convenient experience for customers,” said E.K. Koh, Experian’s Senior Vice President of Global Identity & Fraud Solutions in a recent press release. “This new CrossCore release enables businesses to easily leverage best-in-class, pre-integrated identity and fraud services through simple self-service.” This new version of CrossCore features a cloud architecture, modern user interface, progressive risk assessments, faster response times, self-service workflow configuration, and a transactional volume reporting dashboard. These enhancements give you a simpler way to manage how backing applications are utilized, allow you to analyze key performance indicators in near real-time, and empower you to catch more fraud faster - without impacting the customer experience. “Recent Aite Group research shows that many banks have seen digital channel usage increase 250% in the wake of the pandemic, so ensuring a seamless and safe customer experience is more important than ever,” said Julie Conroy, Research Director at Aite Group. “Platforms such as CrossCore that can enable businesses to nimbly respond to changing patterns of customer behavior as well as rapidly evolving attack tactics are more important than ever, as financial services firms work to balance fraud mitigation with the customer experience.” CrossCore is the first identity and fraud platform that enables you to connect, access, and orchestrate decisions across multiple solutions. With the newest version, Experian enhances your ability to consolidate numerous fraud risk signals into a single, holistic assessment to improve operational processes, stay ahead of fraudsters, and protect your customers. Read Press Release Learn More About CrossCore
Last week, artificial intelligence (AI) made waves in the news as the Vatican and tech giants signed a statement with a set of guidelines calling for ethical AI. These ethical concerns arose as the usage of artificial intelligence continues to increase in all industries – with the market for AI technology projected to reach $190.61 billion by 2025, according to a report from MarketsandMarkets™. In the “Rome Call for Ethics,” these new principles require that AI systems must adhere to ethical AI guidelines to protect basic human rights. The doctrine says AI must be developed with a focus on protecting and serving humanity, and that all algorithms should be designed by the principles of transparency, inclusion, responsibility, impartiality, reliability, security and privacy. In addition, according to the document, organizations must consider the “duty of explanation” and ensure that decisions made as a result of these algorithms are explainable, transparent and fair. As artificial intelligence becomes increasingly used in many applications and ingrained into our everyday lives (facial recognition, lending decisions, virtual assistants, etc.), establishing new guidelines for ethical AI and its usage has become more critical than ever. For lenders and financial institutions, AI is poised to shape the future of banking and credit cards. AI is now being used to generate credit insights, reduce risk and make credit more widely available to more credit-worthy consumers. However, one of the challenges of AI is that these algorithms often can’t explain their reasoning or processes. That’s why AI explainability, or the methods and techniques in AI that make the results of the solution understandable by human experts, remains a large barrier for many institutions when it comes to AI adoption. The concept of ethical AI goes hand-in-hand with Regulation B of the Equal Opportunity Act (ECOA), which protects consumers from discrimination in any aspect of a credit transaction and requires that consumers receive clear explanations when lenders take adverse action. Adverse action letters, which are intended to inform consumers on why their credit applications were denied, must be transparent and incorporate reasons on why the decision was made – in order to promote fair lending. While ethical AI has made recent headlines, it’s not a new concept. Last week’s news highlights the need for explainability best practices for financial institutions as well as other organizations and industries. The time is now to implement these guidelines into algorithms and business processes of the present and future. Join our upcoming webinar as Experian experts dive into fair lending with ethical and explainable AI. Register now
While many companies are interested in implementing technology with advanced analytic capabilities, the concepts behind the technology can often be hard to understand. Demystifying the terminology around artificial intelligence and machine learning is one of the first steps for successful implementation. Discover what they mean for your financial institution in our new infographic: Learn more
Machine learning, once a mysterious and unknown field, has come a long way throughout the years. Now, it\'s being implemented across a variety of industries - and expertise in all things related to machine learning is in high demand. Take a journey through the history of machine learning in our new infographic: Read the e-book
It may be a new decade of disruption, but one thing remains constant – the consumer is king. As such, customer experience (and continually evolving digital transformations necessary to keep up), digital expansion and all things identity will also reign supreme as we enter this new set of Roaring 20s. Here are seven of the top trends to keep tabs of through 2020 and beyond. 1. Data that does more – 100 million borrowers and counting Traditional, alternative, public record, consumer-permissioned, small business, big business, big, bigger, best – data has a lot of adjectives preceding it. But no matter how we define, categorize and collate data, the truth is there’s a lot of it that’s untapped, which is keeping financial institutions from operating at their max efficiency levels. Looking for ways to be bigger and bolder? Start with data to engage your credit-worthy consumer universe and beyond. Across the entire lending lifecycle, data offers endless opportunities – from prospecting and acquisitions to fraud and risk management. It fuels any technology solution you have or may want to implement over the coming year. Additionally, Experian is doing their part to create a more holistic picture of consumer creditworthiness with the launch of Experian LiftTM in November. The new suite of credit score products combines exclusive traditional credit, alternative credit and trended data assets, intended to help credit invisible and thin-file consumers gain access to fair and affordable credit. \"We\'re committed to improving financial access while helping lenders make more informed decisions. Experian Lift is our latest example of this commitment brought to life,” said Greg Wright, Executive Vice President and Chief Product Officer for Experian Consumer Information Services. “Through Experian Boost, we\'re empowering consumers to play an active role in building their credit histories. And, with Experian Lift, we\'re empowering lenders to identify consumers who may otherwise be excluded from the traditional credit ecosystem,” he said. 2. Identity boom for the next generation Increasingly digital lifestyles have put personalization and frictionless transactions on hyperdrive. They are the expectation, not a nice-to-have. Having customer intelligence will become a necessary survival strategy for those in the market wanting to compete. Identity is not just for marketing purposes; it must be leveraged across the lending lifecycle and every customer interaction. Fragmented customer identities are more than flawed for decisioning purposes, which could potentially lead to losses. And, of course, the conversation around identity would be incomplete without a nod to privacy and security considerations. With the roll-out of the California Consumer Privacy Act (CCPA) earlier this month, we will wait to see if the other states follow suit. Regardless, consumers will continue to demand security and trust. 3. All about artificial intelligence and machine learning We get it – we all want the fastest, smartest, most efficient processes on limited – and/or shrinking – budgets. But implementing advanced analytics for your financial institution doesn’t have to break the bank. And, when it comes to delivering services and messaging to customers the way they want it, how to do that means digital transformation – specifically, leveraging big data and actionable analytics to evaluate risk, uncover industry intel and improve decisioning. One thing’s for certain, financial institutions looking to compete, gain traction and pull away from the competition in this next decade will need to do so by leveraging a future-facing partner’s expertise, platforms and data. AI and machine learning model development will go into hyperdrive to add accuracy, efficiency, and all-out speed. Real-time transactional processing is where it’s at. 4. Customer experience drives decisioning and everything Faster, better, more frictionless. 2020 and the decade will be all about making better decisions faster, catering to the continually quickening pace of consumer attention and need. Platforms and computing language aside, how do you increase processing speed at the same time as increasing risk mitigation? Implementing decisioning environments that cater to consumer preferences, coupled with best-in-class data are the first two steps to making this happen. This can facilitate instant decisioning within financial institutions. Looking beyond digital transformation, the next frontier is digital expansion. Open platforms enable financial institutions to readily add solutions from numerous providers so that they can connect, access and orchestrate decisions across multiple systems. Flexible APIs, single integrations and better strategy and design build the foundation of the framework to be implemented to enhance and elevate customer experience as it’s known today. 5. Credit marketing that keeps up with the digital, instant-gratification age Know your customer may be a common acronym for the financial services industry, but it should also be a baseline for determining whether to send a specific message to clients and prospects. From the basics, like prescreen, to omni-channel marketing campaigns, financial institutions need to leverage the communication channels that consumers prefer. From point of sale to mobile – there are endless possibilities to fit into your consumers’ credit journey. Marketing is clearly not a one-and-done tactic, and therefore multi-channel prequalification offers and other strategies will light the path for acquisitions and cross-sell/up-sell opportunities to come. By developing insights from customer data, financial institutions have a clear line of sight into determining optimal strategies for customer acquisition and increasing customer lifetime value. And, at the pinnacle, the modern customer acquisition engine will continue to help financial institutions best build, test and optimize their customer channel targeting strategies faster than ever before. From segmentation to deployment, and the right data across it all, today and tomorrow’s technology can solve many of financial organizations’ age-old customer acquisition challenges. 6. Three Rs: Recession, regulatory and residents of the White House Last March, the yield curve inverted for the first time since 2007. Though the timing of the next economic correction is debated, messaging is consistent around making a plan of action now. Whether it’s arming your collections department, building new systems, updating existing systems, or adjusting rules and strategy, there are gaps every organization needs to fill. By leveraging the stability of the economy now, financial institutions can put strategies in place to maximize profitability, manage risk, reduce bad debt/charge-offs, and ensure regulatory compliance among their list of to-do’s, ultimately resulting in a more efficient, better-performing program. Also, as we near the election later this year, the regulatory landscape will likely change more than the usual amount. Additionally, we will witness the first accounts of what CECL looks like for SEC-filing financial institutions (and if that will suggest anything for how non-SEC-filing institutions may fare as their deadline inches closer), as well as see the initial implications of the CCPA roll out and whether it will pave a path for other states to follow. As system sophistication continues to evolve, so do the risks (like security breaches) and new regulatory standards (like GDPR and CCPA) which provide reasons for organizations to transform. 7. Focus on fraud (in all forms) With evolving technology, comes evolved fraudsters. Whether it’s loyalty and rewards programs, account openings, breaches, there are so many angles and entry points. Synthetic identity fraud is the fastest-growing type of financial crime in the United States. The cost to businesses is estimated to grow to $1.2 billion by 2020, according to the Aite Group. To ensure the best protection for your business and your customers, a layered, risk-based approach to fraud management provides the highest levels of confidence in the industry. Balance is key – while being compliant with regulatory requirements and conscious of user experience, ensuring consumers’ peace of mind is priority one. Not a new trend, but recognizing fraud and recognizing good consumers will save continue to save financial institutions money and reputational harm, driving significant improvement in key performance indicators. Using the right data (and aggregating multiple data sets) and digital device intelligence tools is the one-two punch to protect your bottom line. For all your needs in 2020 and throughout the next decade, Experian has you covered. Learn more
With nearly seven billion credit card and personal loan acquisition mailers sent out last year, consumers are persistently targeted with pre-approved offers, making it critical for credit unions to deliver the right offer to the right person, at the right time. How WSECU is enhancing the lending experience As the second-largest credit union in the state of Washington, Washington State Employees Credit Union (WSECU) wanted to digitalize their credit decisioning and prequalification process through their new online banking platform, while also providing members with their individual, real-time credit score. WSECU implemented an instant credit decisioning solution delivered via Experian’s Decisioning as a ServiceSM environment, an integrated decisioning system that provides clients with access to data, attributes, scores and analytics to improve decisioning across the customer life cycle. Streamlined processes lead to upsurge in revenue growth Within three months of leveraging Experian’s solution, WSECU saw more members beginning their lending journey through a digital channel than ever before, leading to a 25% increase in loan and credit applications. Additionally, member satisfaction increased with 90% of members finding the simplified process to be more efficient and requiring “low effort.” Read our case study for more insight on using our digital credit solutions to: Prequalify members in real-time at point of contact Match members to the right loan products Increase qualification, approval and take rates Lower operational and manual review costs Read case study Interested in learning more? Watch our video:
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
To provide consumers with clear-cut protections against disturbance by debt collectors, the Consumer Financial Protection Bureau (CFPB) issued a Notice of Proposed Rulemaking (NPRM) to implement the Fair Debt Collection Practices Act (FDCPA) earlier this year. Among many other things, the proposal would set strict limits on the number of calls debt collectors may place to reach consumers weekly and clarify requirements for consumer-facing debt collection disclosures. A bigger discussion Deliberation of the debt collection proposal was originally scheduled to begin on August 18, 2019. However, to allow commenters to further consider the issues raised in the NPRM and gather data, the comment period was extended by 20 days to September 18, 2019. It is currently still being debated, as many argue that the proposed rule does not account for modern consumer preferences and hinders the free flow of information used to help consumers access credit and services. The Association of Credit and Collection Professionals (ACA International) and US House lawmakers continue to challenge the proposal, stating that it doesn’t ensure that debt collectors’ calls to consumers are warranted, nor does it do enough to protect consumers’ privacy. Many consumer advocates have expressed doubts about how effective the proposed measures will be in protecting debtors from debt collector harassment and see the seven-calls-a-week limit on phone contact as being too high. In fact, it’s difficult to find a group of people in full support of the proposal, despite the CFPB stating that it will help clarify the FDCPA, protect lenders from litigation and bring consumer protection regulation into the 21st century. What does this mean? Although we don’t know when, or if, the proposed rule will go into effect, it’s important to prepare. According to the Federal Register, there are key ways that the new regulation would affect debt collection through the use of newer technologies, required disclosures and limited consumer contact. Not only will the proposed rules apply to debt collectors, but its provisions will also impact creditors and servicers, making it imperative for everyone in the financial services space to keep watch on the regulation’s status and carefully analyze its proposed rules. At Experian, our debt collection solutions automate and moderate dialogues and negotiations between consumers and collectors, making it easier for collection agencies to connect with consumers while staying compliant. Our best-in-class data and analytics will play a key role in helping you reach the right consumer, in the right place, at the right time. Learn more
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.
Financial institutions preparing for the launch of the Financial Accounting Standard Board’s (FASB) new current expected credit loss model, or CECL, may have concerns when it comes to preparedness, implications and overall impact. Gavin Harding, Experian’s Senior Business Consultant and Jose Tagunicar, Director of Product Management, tackled some of the tough questions posed by the new accounting standard. Check out what they had to say: Q: How can financial institutions begin the CECL transition process? JT: To prepare for the CECL transition process, companies should conduct an operational readiness review, which includes: Analyzing your data for existing gaps. Determining important milestones and preparing for implementation with a detailed roadmap. Running different loss methods to compare results. Once losses are calculated, you’ll want to select the best methodology based on your portfolio. Q: What is required to comply with CECL? GH: Complying with CECL may require financial institutions to gather, store and calculate more data than before. To satisfy CECL requirements, financial institutions will need to focus on end-to-end management, determine estimation approaches that will produce reasonable and supportable forecasts and automate their technology and platforms. Additionally, well-documented CECL estimations will require integrated workflows and incremental governance. Q: What should organizations look for in a partner that assists in measuring expected credit losses under CECL? GH: It’s expected that many financial institutions will use third-party vendors to help them implement CECL. Third-party solutions can help institutions prepare for the organization and operation implications by developing an effective data strategy plan and quantifying the impact of various forecasted conditions. The right third-party partner will deliver an integrated framework that empowers clients to optimize their data, enhance their modeling expertise and ensure policies and procedures supporting model governance are regulatory compliant. Q: What is CECL’s impact on financial institutions? How does the impact for credit unions/smaller lenders differ (if at all)? GH: CECL will have a significant effect on financial institutions’ accounting, modeling and forecasting. It also heavily impacts their allowance for credit losses and financial statements. Financial institutions must educate their investors and shareholders about how CECL-driven disclosure and reporting changes could potentially alter their bottom line. CECL’s requirements entail data that most credit unions and smaller lenders haven’t been actively storing and saving, leaving them with historical data that may not have been recorded or will be inaccessible when it’s needed for a CECL calculation. Q: How can Experian help with CECL compliance? JT: At Experian, we have one simple goal in mind when it comes to CECL compliance: how can we make it easier for our clients? Our Ascend CECL ForecasterTM, in partnership with Oliver Wyman, allows our clients to create CECL forecasts in a fraction of the time it normally takes, using a simple, configurable application that accurately predicts expected losses. The Ascend CECL Forecaster enables you to: Fulfill data requirements: We don’t ask you to gather, prepare or submit any data. The application is comprised of Experian’s extensive historical data, delivered via the Ascend Technology PlatformTM, economic data from Oxford Economics, as well as the auto and home valuation data needed to generate CECL forecasts for each unsecured and secured lending product in your portfolio. Leverage innovative technology: The application uses advanced machine learning models built on 15 years of industry-leading credit data using high-quality Oliver Wyman loan level models. Simplify processes: One of the biggest challenges our clients face is the amount of time and analytical effort it takes to create one CECL forecast, much less several that can be compared for optimal results. With the Ascend CECL Forecaster, creating a forecast is a simple process that can be delivered quickly and accurately. Q: What are immediate next steps? JT: As mentioned, complying with CECL may require you to gather, store and calculate more data than before. Therefore, it’s important that companies act now to better prepare. Immediate next steps include: Establishing your loss forecast methodology: CECL will require a new methodology, making it essential to take advantage of advanced statistical techniques and third-party solutions. Making additional reserves available: It’s imperative to understand how CECL impacts both revenue and profit. According to some estimates, banks will need to increase their reserves by up to 50% to comply with CECL requirements. Preparing your board and investors: Make sure key stakeholders are aware of the potential costs and profit impacts that these changes will have on your bottom line. Speak with an expert
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