Data & Analytics
Premier Awards Program Recognizes Breakthrough Financial Technology Products and Companies Experian’s Ascend Intelligence Services was selected as a winner of the “Consumer Lending Innovation Award” category in the fifth annual Fintech Breakthrough Awards conducted by Fintech Breakthrough, an independent market intelligence organization that recognizes the top companies, technologies and products in the global fintech market today. The Fintech Breakthrough Awards is the premier awards program founded to recognize the fintech innovators, leaders and visionaries from around the world in a range of categories, including digital banking, personal finance, lending, payments, investments, RegTech, InsurTech and many more. The 2021 Fintech Breakthrough Awards attracted more than 3,850 nominations from across the globe. One of the latest developments on Experian's trusted, award-winning Ascend platform, Ascend Intelligence Services empowers financial services firms with Experian’s revolutionary managed analytics solutions and services, delivered on a modern-tech AI platform. Ascend Intelligence Services includes rapid model development, seamless deployment, optimized decision strategies, ongoing performance monitoring and continuous retraining. The technology-enabled service uses a secure cloud-based AI platform to harness the power of machine learning, and deliver unique capabilities covering the entire credit lifecycle, through an easy-to-use web portal. “To stay ahead of the latest economic conditions, fintechs need high-quality analytical models running on large and varied data sets that empower them to act quickly and decisively. The breakthrough Ascend Intelligence Services platform answers this immediate market need,” said James Johnson, Managing Director, Fintech Breakthrough. “Congratulations to Experian and the Ascend team on winning our ‘Consumer Lending Innovation Award’ for 2021 with this game-changing solution.” “Data scientists are spending too much time on manual, repetitive and low value-add tasks, and organizations cannot afford to do this is in a state of constant change,” said Srikanth Geedipalli, Experian’s SVP Global Analytics/AI Products. “While building and deploying high-quality analytical models can be time-consuming and expensive, Ascend Intelligence Services streamlines this process by harnessing the power of machine learning and Experian’s rich data assets to drive better, faster and smarter decisions. We have been able to deliver analytical solutions to clients up to 4X faster, significantly improving decision automation rates and increasing approval rates by double digits. We are proud that Ascend Intelligence Services is being recognized as a breakthrough solution in the 2021 Fintech Breakthrough Awards program,” he said. Ascend Intelligence Services is comprised of four modules: Ascend Intelligence Services Challenger™ is a powerful, dynamic and collaborative model development service that enables Experian to rapidly build a model and quantify the benefit to business. Businesses can review, comment on and approve the model, all from within the web portal, while it’s being built. The resulting score is available for testing through an API endpoint and can be deployed in production with a few easy steps. Reports are customizable, downloadable and regulatory compliant. Ascend Intelligence Services Pulse™ is a proactive model monitoring and validation service, which aids companies in monitoring the health of models that drive their business decisions. Pulse, provides convenient dashboards that include a model health index, performance summary, stress-testing results, model risk management reporting, model health alerts and more. Additionally, Pulse automatically builds challengers for champion models, providing an estimated performance lift and financial benefit. Ascend Intelligence Services Strategy Advance™ is a powerful business strategy development service, enabling clients to make optimal lending decisions on their applicants. Strategy Advance uses Experian’s powerful optimization engine to build the right credit policy for clients, including sophisticated decision rules, model overlays and client specified knock-out rules. The resulting decision is available for testing through an API endpoint and can be deployed in production with a few easy steps. Ascend Intelligence Services Limit™ is a credit limit optimization service, enabling clients to make the right credit limit decisions at account origination and during account management. Limit uses Experian’s data, predictive risk and balance models and our powerful optimization engine to design the right credit limit strategy that maximizes product usage, while keeping losses low. The limit decision is available for testing through an API endpoint and can be deployed in production with a few easy steps. To learn more about how Ascend Intelligence Services can support your business, please explore our solutions page. Learn more For a list of all award winners selected for the Fintech Breakthrough Awards, read the full press release here.
The pandemic changed nearly everything – and consumer credit is no exception. Data, analytics, and credit risk decisioning are gaining an even more significant role as we grow closer to the end of the global crisis. Consumers face uneven roads to recovery, and while some are ready to spend again, others are still dealing with pandemic-related financial stress. We surveyed nearly 9,000 consumers and 2,700 businesses worldwide about how consumers are stabilizing their finances and businesses are returning to growth for our new Global Decisioning Report. In this report, we dive into: Key business priorities in 2021 Financial concerns for consumers How to navigate an uneven recovery Business priorities for the year ahead The importance of the online experience As we begin to near the end of the pandemic, businesses need to prioritize technology that enables a responsive, flexible, efficient and confident approach. This can be done by leveraging advanced data and analytics and integrating machine learning tools into model development. By investing in the right credit risk decisioning tools now, you can help ensure your future. Download the report
As quarantine restrictions lift and businesses reopen, there is still uncertainty in the mortgage market. Research shows that more than two million households face foreclosure as moratoriums expire. And with regulators, like the Consumer Financial Protection Bureau (CFPB), urging mortgage servicers to prepare for an expected surge in homeowners needing assistance, lenders need the right resources as well. One of the resources mortgage lenders rely on to help gain greater insight into their borrower’s financial picture is income and employment verification. The challenge, however, is striking the right balance between gaining the insights needed to support lending decisions and creating a streamlined, frictionless mortgage process. There are three main barriers on the path to a seamless and digital verification process. Legacy infrastructure Traditional verification solutions tend to rely on old technology or processes. Whether a lender’s verification strategy is centered around a solution built on older technology or a manual process, the time to complete a borrower verification can vary from taking a day to weeks. Borrowers have grown accustomed to digital experiences that are simple and frictionless and experiencing a drawn out, manual verification process is likely to impact loyalty to the lender’s brand. Stale employment and income data The alternative to a manual process is an instant hit verification solution, with the aim to create a more seamless borrower experience. However, lenders may receive stale borrower income and employment data back as a match. Consumer circumstances can change frequently in today’s economic environment and, depending on the data source the lender is accessing, data may be out of date or simply incorrect. Decisioning based on old information is problematic since it can increase origination risk. Cost and complexity Lenders that use manual processes to verify information are adding to their time to close and ultimately, their bottom line by way of time and resources. Coupled with pricing increases, lenders are paying more to put their borrowers through a cumbersome and sometimes lengthy process to verify employment and income information. How can mortgage lenders avoid these common pitfalls in their verification strategy? By seeking verification solutions focused on innovation, quality of data, and that are customer-centric. The right tool, such as Experian VerifyTM, can help provide a seamless customer experience, reduce risk, and streamline the verification process. Learn more
The tax gap—the difference between what taxpayers should pay and what they actually pay on time—can have a substantial impact on states’ budgets. Tax agencies and other state departments are responsible for helping states manage their budgets by minimizing expected revenue shortfalls. Underreported income is a significant budget complication that continues to frustrate even the most effective tax agencies, until the right tools are brought into play. The Problem Underreporting is a large, complex issue for agencies. The IRS currently estimates the annual tax gap at $441 billion. There are multiple factors that comprise that total, but the most prevalent is underreporting, which represents 80% of the total tax gap. Of that, 54% is due to underreporting of individual income tax. In addition to being the largest contributor to the tax gap, underreporting is also extremely challenging to identify out of the millions of returns being filed. With 85% of taxes owed correctly reported and paid, finding underreporting can be like trying to locate a needle in the proverbial haystack. Making this even more challenging is the limited resources available for auditing returns, which makes efficiency key. The Solution Data, combined with artificial intelligence (AI) equals efficient detection. The problem with trying to detect which returns are most likely to have underreported income is similar to many other challenges Experian has solved with AI. Partnerships between Experian and state agencies combine what we know about consumers with what their agency knows about their population. We can take the data and use AI to separate the signal from the noise, finding opportunities to recoup lost revenue. Read our case study on how Experian was able to help an agency identify instances of underreporting, detecting an estimated $80 million annual lost revenue from underreported income. Download case study Contact us
The COVID-19 pandemic has created shifting economic conditions and rapidly evolving consumer preferences. Lenders must keep up by re-evaluating their strategies to accelerate growth and beat the competition. Here's how AI/ML can help your organization evolve post-COVID-19: With the democratization of AI/ML, lenders of all sizes can now use this technology to grow their lending and optimize for strategic growth. Register for our upcoming webinar to see how lenders like Elevate have incorporated this new technology into their business processes. Register now
For credit unions of all sizes, choosing a strategic partner with the right tools, capabilities, and industry expertise to support growth while minimizing expenses is a decision critical to the bottom line. This is especially important, since the goal of achieving sustainable growth has continued to be a trending topic for credit unions since the start of the pandemic. According to this CU Times analysis of NCUA data, the fourth quarter of 2020 showed that high overhead per assets was the main factor holding down net income, and credit unions with less than $1 billion in assets fared the worst. These high overhead costs kept margins low and served to be a key contributing factor in gauging a credit union’s profitability. Overcoming this problem lies not only in improving operational efficiency, but in seeking out partners that can provide innovative insight and “right-sized,” scalable solutions to help credit unions effectively grow at a strategic pace. The less money a credit union spends earning each dollar, the more operationally efficient and resource-savvy it becomes—which in turn generates more value for both the credit union and its members. So how can a credit union successfully assess a potential partner’s ability to help them achieve goals for sustainable growth? Asking three key questions can reveal a potential partner’s operational prowess and their ability to understand and offer the right solutions tailored for an individual credit union’s need. Minimize Overhead with a Partner Who Can Help Accelerate and Support Sustainable Growth: Evaluation Questions to Ask 1. Does my potential partner offer solutions to ease the strain on staff, or help automate time-consuming, repetitive tasks and processes? Automation is not only for large credit unions. Employees at credit unions with $4 billion and less in assets often wear many hats and manage the full spectrum of credit activities, leaving leaders to ponder how much time staff is spending on rote, manual tasks throughout the end-to-end member lifecycle. As a result, credit unions are turning to automated decisioning to streamline repetitive tasks and meet increasing member expectations, while also reducing risk. To drive sustainable growth, credit unions will want to look at current processes as a means of measuring efficiency. Can existing programs handle growth to scale in all areas of the business? How can digital lending automation be increased and free up more time for staff to focus attention where it is needed most, such as high-value engagements with members and delivering a personalized member experience? Can self-service tools save your credit union valuable time and increase employee satisfaction? 2. Does my potential partner have access to the right data, advanced analytics and technology to help optimize credit decisioning? As credit unions consider different ways to minimize overhead and accelerate growth, the last few years have shown that automation, coupled with advanced analytics and technology, has taken on a second wave of focus and intense interest. A significant opportunity pertaining to automation is supporting decisioning throughout the member lifecycle, again, eliminating the need for manual processes that cannibalize time and resources. For example, access to advanced analytics and data at the onset of account acquisition can quickly inform a lender as to whether a new account should be approved or declined. Furthermore, it also presents an opportunity to lend deeper. Credit unions can leverage expanded datasets to perform an analysis on rejected applicants and make more predictive decisions – leading to incremental loans. Additionally, lenders have identified other areas where automated decisioning could speed up processes that once required manual evaluation – from account and portfolio management, to marketing and prescreening efforts, to managing early and late-stage delinquent accounts. By leveraging a partner who can support optimizing credit decisioning with the freshest data and analytics, credit unions can routinely and consistently be sure they’re making the right offers and decisions to the right customer at the right time. 3. Does my potential partner offer digital-first strategies and solutions that help reduce friction and improve the member experience? More and more members are interacting and engaging with their credit unions via digital channels. To meet their demands, credit unions – who have historically prioritized other initiatives over digital transformation– are quickly pivoting and rethinking their digital strategy to offer best-in-class digital banking and borrowing experiences, while also reducing friction. Part of this strategy includes smart, easy and well-designed applications that support sustainable growth simply by streamlining offers and reducing abandonment. When considering a potential partner, take into consideration their ability to assist with digital-first solutions, including: Real-time income and employment verification, and fraud tools to quickly and accurately confirm important factors, including the legitimacy of members, and streamline the borrowing process with minimal friction. Instant prescreen, self-service prequalification and instant credit to offer fast, easy, and convenient real-time credit decisions for members. Additionally, improving lending economics with a digital-first pre-qualification tool can not only better serve members, but also drive more apps and grow loans. Artificial intelligence, machine learning and other innovative technologies to enhance underwriting and decrease both hard inquiries on applications and the need for extensive underwriter review. Prequalification tools powered by innovative technology solutions can lead to efficient use of underwriter resources and act as a filter in front of the LOS to remove unqualified applications from hard inquiries. Technology that integrates with multiple lending and core systems and delivers solutions that integrate with multiple systems and channels. For example, to help improve conversion, the borrower experience can be offered a simple application that is designed to “get to offer” as fast as possible. This helps reduce abandonment. The process can be further streamlined by integrating data sources for ID verification, auto fill assistance and adding integrations with existing lending and core systems. To learn more about Experian and how our solutions can support and grow your credit union, contact us now. Contact Us
Forrester recently named Experian to their Programs of the Year awards, which recognize outstanding achievements in a particular area in sales, marketing and product functions. Forrester gives this award to companies who achieve the successful implementation of Forrester’s research, frameworks and best practices to improve functional performance. At Experian, innovation is at the heart of what we do. We strive for continuous improvement, and look for ways to progress our products and services to better serve businesses and consumers. Over the last year, Experian’s Decision Analytics Portfolio Marketing team engaged with Forrester’s SiriusDecisions group to refine the programs they employ to assess and respond to market needs while meeting their stated growth and performance goals. Experian’s Keir Breitenfeld, Vice President, Portfolio Marketing, Experian Decision Analytics, who presented the team’s results at the recent Forrester B2B summit said, “I’m proud of the Decision Analytics Portfolio Marketing team for what they accomplished while working alongside Forrester SiriusDecisions. We were able to reframe how we assess market opportunities for increased impact as we highlight Experian’s areas of expertise to better serve businesses and the consumers that rely on them.” To learn more about the Programs of the Year award and how Experian innovation helps businesses achieve their goals, visit us or request a call. Contact us
To grow in today’s economic climate and beat the competition, financial institutions need to update their acquisition and cross-sell strategies. By doing so, they are able to drive up conversions, minimize risk, and ultimately connect consumers with the right offers at the right time. Businesses and consumers are spending more time online than ever before, with 40% of consumers increasing the number of businesses they visit online. They’ve also made it clear that they expect easy, frictionless transactions with their providers. This includes new accounts and offers of credit – creating the need for better delivery systems. Effective targeting and conversion come down to more than just direct mail and email subject lines, especially now in a volatile economy where consumers are seeking appropriate products for their current situation. Be the first to meet consumers’ needs by leveraging the freshest data, advanced analytics, and automated decision systems. For example, when a consumer tries to open a checking account, the system can initiate a “behind-the-scenes” real-time prescreen request while assessing information needed to open the deposit account. The financial institution can then see if the consumer qualifies for overdraft protection, refinancing offers, loans, credit cards, and more. By performing the pre-approval process in seconds, financial institutions can be sure that they're making the right offers to the right customer, and doing it at the right time. All of this helps to increase the offer acceptance rate, improving customer retention, and maximizing customer account life-time value. The pandemic upended a lot of the ways that your businesses run day-to-day – from where you work to how you (better) engage with customers. Arguably, some of the changes have been long overdue, particularly the acceleration to digital and better customer acquisition strategies. Ahead lies the opportunity to grow – strategies enacted now will determine the extent of that opportunity. To learn more about how Experian can help you assess your prescreen strategy and grow, contact us today. Request a call
Recently, I wrote about how Experian is assisting NASWA (National Association of State Workforce Agencies) with identity verification to help mitigate the spike in fraudulent unemployment insurance claims. Because of this I was not all that surprised when I found a letter in my mailbox from the Texas Workforce Commission with a fraudulent claim using my identity, inspiring me to follow up on this topic with a focus on fraud prevention best practices. Identity theft is on the rise According to Experian data analysis and a recent study on unemployment insurance fraud, at least 25% of new claims are a result of identity theft. This is 50 times higher than what we have traditionally seen in the highest ID theft fraud use case, new credit card applications, which generally amounts to less than 0.5% of new applications. Increasing digitization of the last few years—culminating in the huge leap forward in 2020—has resulted in a massive amount of information available online. Of that information, a reported 1.03 billion records were exposed between 2016 and 2020. There are currently approximately 330 million Americans, so on average more than three records per person have been exposed, creating an environment ripe for identity theft. In fact, a complete identity consisting of name, address, date of birth, and Social Security number (SSN) can be purchased for as little as $8. This stolen data is then often leveraged by both criminal rings who are able to perpetrate fraud on a large scale and smaller scale opportunists – like the ones in Riverside, CA leveraging access to identities of prison inmates. Fraud prevention through layered identity controls In the 20 years that I have been combatting ID theft both in the private and public sectors, I’ve learned that the most effective identity proofing goes beyond traditional identity resolution, validation, and verification. To be successful, you must take advantage of all available data and incorporate it into a layered and risk-based approach that utilizes device details, user behavior, biometrics, and more. Below, I outline three key layers to design an effective process for ID proofing new unemployment insurance claims. Layer 1: Resolve and Validate Identities Traditional identity data consists of the same basic information—name, address, date of birth, telephone number, and SSN—which is now readily available to fraudsters. These have been the foundation for ID proofing in the past and are still critical to resolving the identity in question. The key is to also include additional identity elements like email address and phone number to gain a more holistic view of the applicant. Layer 2: Assess Fraud Risk Determining an identity belongs to a real-life subject is not sufficient to mitigate the risk of ID theft associated with a new unemployment insurance claim. You must go beyond identity validation to assess the risk associated with their claim. Risk assessment risk falls into two categories – identity and digital risk. Identity Risk When assessing a claim, it’s important to check the identity for: Velocity: How often have you (or other states) seen the information being presented with this application? Has the information been associated with multiple identities? Recency of change: How long has the identity been associated with the contact information (phone, email, address, etc.)? Red flags: Has the subject been a recent victim of ID theft, or are they reported as deceased? Synthetic Identity: Are there signs that the identity itself is fictitious or manipulated and does not belong to a real-life person? Digital Risk Similar to the identity risk layer above, the device itself and how the subject interacts with the device are significantly important in identifying the likelihood a new claim is fraudulent. Device risk can be assessed by utilizing geolocation and checking for inconsistent settings or high-risk browsers, while behavioral risk might check for mouse movement, typing speed, or screen pressure. Layer 3: Verify Highest Risk Subjects The final stage in this process is to require additional verification for the highest risk claims, which helps to balance the experience of your valid subjects while minimizing the impact of fraud. Additional steps might include: Document verification: Scanning a government-issued ID (driver’s license, passport, or similar), which includes assessing for document security features and biometric comparison to the applicant. One-time passcode (OTP): It is key to deploy this sparingly only to phone numbers that have been associated with the subject for a significant time frame and incorporate checks to determine if it is at high risk (e.g., recently ported or forwarded). Knowledge-based verification (KBV): Leveraging non-public information from a variety of sources. By adding additional, context-based identity elements, it becomes possible to improve the three main objectives of most agencies’ identity proofing process – get good constituents through the first time, protect the agency and citizens from fraud, and deliver a smooth and secure customer experience in online channels. While there’s no quick fix to prevent unemployment insurance fraud, a layered identity strategy can help prevent it. Finding a partner that has a single, holistic solution empowers agencies to defend against unemployment insurance fraud while minimizing friction for the end-user, and preparing for future fraud schemes. To learn more about how you can protect your constituents and your agency from unemployment insurance fraud request a call today. Contact us
At some point a lender may need to issue an RFI or an RFP for a credit decisioning system. In this latest installment of “working with vendors” let’s dive into some best practices for writing RFIs and RFPs that will help you more quickly and efficiently understand the capabilities of a vendor. First, have one person (or at most a very small group) review the document before it goes out to vendors. Too often these kinds of documents seem like they’re just cut and pasted together without any concern if they paint a coherent picture. If it’s worth the time to write an RFI/RFP, then it’s worth the time to get it right so that the vendor responses make sense. If your document paints an inconsistent picture, a vendor may not know what products will best serve your requirements. In turn, precious time will be wasted in discussions around what’s being proposed. Here are some things to make clear in the document: For what part of the credit life cycle does this RFI/RFP apply (prospecting, origination, account management or collections)? If the request covers more than one part of the life cycle, make clear which questions apply to which part of the life cycle. Do you need a system that processes in batch or real-time requests (or both)? For example, a credit card account management solution can process accounts in batch (for proactive line management), in real time (for reactive requests) or possibly even both. Let the vendor know what it is you’re trying to do, as there may be different systems involved in processing these requests. Do you want this system hosted at the vendor, a third party (like AWS, Azure, etc.) or installed on premises? If you have a preference, let the vendor know. If you have no preference, ask the vendor what they can support. In general, consider playing down or skip detailed pricing questions. There’s nothing wrong with asking for a price range. For credit decisioning systems, detailed pricing is difficult for the vendor since there are often high levels of unknown customization to do. A better question might be, “What things will the vendor have to know in order to accurately price the solution? What are the logical next steps to get more accurate pricing? What’s the typical range of pricing in a solution such as this and what drives that range?” Will you be acting as an aggregator? Sometimes systems are created as front ends to several lenders. For example, a client may want to create a website where a borrower can “shop” among several lenders. This is certainly doable but carries with it a whole host of legal, compliance, business and technical questions. In my opinion, I’d skip the RFI/RFP in this situation and have a robust sit down directly with the vendors. This option will likely be far more productive. Ask more open-ended questions. “How does the solution perform task X?” as opposed to, “Do you support Y?” Often, there’s more than one way to accomplish a task. Asking more open-ended questions will yield a more comprehensive answer from the vendor rather than a simple yes or no response. It also gives you the opportunity to learn about the latest decisioning techniques. Be careful that you have not copied old RFP questions that are no longer relevant. I’ve had clients ask if we support Bernoulli Boxes (a mid-80s kind of floppy disk), or whether we support OS/2, etc. I’ve even had questions about supporting a particular printer. These kinds of questions are centered on the support of the operating system and not a particular vendor’s credit decisioning software. Instead of asking yes/no technology questions, ask for a typical sample architecture. Ask what kinds of APIs are supported (REST, SOAP/XML, etc.). Ask about the solution’s capabilities to call third-party systems (both internal and external). Ask fewer, but more in-depth questions. If the solution needs screens, be clear which screens you’re talking about. Do you need screens to make rule adjustments or configuration changes? Do you need screens for manual review or some sort of case management? Do you need consumer-facing screens where borrowers can type in their application data? If you need screens, be clear on the task the screens should perform. If you have particular concerns, ask them in an open-ended way. For example, “The solution will have to exchange file-based data with a mainframe. How can your solution best satisfy this requirement?” In general, state your requirement not the technology to use. A preamble or brief executive summary is useful to get the big picture across before the vendor delves into any questions. A paragraph or two can go a long way to help the vendor better assess your requirements and provide more meaningful answers to you. This works well because it’s easier to give the big picture in a few paragraphs as opposed to sprinkled around in multiple questions. To summarize, be clear on your requirements and provide a more open-ended format for the vendor to respond. This will save both you and the vendor a lot of time. In section three, I’ll cover evaluating vendors.
Digitalization, 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, from https://www.idc.com/getdoc.jsp?containerId=US45599219
Perhaps your loan origination system (LOS) doesn’t have the flexibility that you require. Perhaps the rules editor can’t segment variables in the manner that you need. Perhaps your account management system can’t leverage the right data to make decisions. Or perhaps your existing system is getting sunset. These are just some of the many reasons a company may want to investigate the marketplace for new credit decisioning software. But RFIs and RFPs aren’t the only way to find new decisioning software. After working in credit services decisioning for over 20 years — and seeing hundreds of RFPs and presenting thousands of solutions and proposed architectures — I’ve formed a few opinions about how I would go about things if I were in the customer’s seat and have broken that into a three-part series. Part 1 will cover everything up to issuing an RFI or RFP. Part 2 will discuss writing an RFP or RFI. Part 3 will cover evaluating vendors. Let’s go. If you’re looking to buy new decisioning software, your first inclination might be to issue an RFI or an RFP. However, that may not be the best idea. Here’s an issue that I frequently see. Vendors are constantly evolving their products. How a product did feature X two years ago might be completely different now. The terminology that the industry uses might have changed, and new capabilities (like machine learning) might have come about and changed whole sets of functionalities. The first decision point is to ask yourself a question, “Do I know exactly what I want or am I trying to generally learn what is out there?” An RFI or RFP isn’t always the greatest way to exchange information about a product. From a vendor’s standpoint, a feature-rich, complex system has to be reduced down to a few text answers or (worst yet) a series of yes or no answers. It all boils down to nuance. On many occasions, I’ve faced a dilemma when answering an RFP question, “This question is unclear; if the customer means X, the answer is yes; if they mean Y, the answer is no.” If I were in a room with the customer, I could ask them the question, they could provide clarification and I could then provide the accurate answer. There would be more opportunity to have a back and forth, “Oh when you said X, this is what you meant ….” All of that back and forth is lost with an RFI or RFP, or at least delayed until the (hopefully selected) vendor gets a chance to present in front of a live audience. Also, consider that vendors are eager to educate you about their product. They know exactly how the product works and they’re happy to answer your questions. It’s perfectly reasonable to go to a vendor with prewritten questions and thoughts and to pose those questions during a call or demonstration with the vendor. Nothing would prevent a customer from using the same questions for each vendor and evaluating them based on their answers. All of this can be done without issuing an RFI or RFP. In conclusion, I’d offer the following points to think about before issuing an RFI or RFP: A customer can provide questions that they want answered during a demonstration of a credit decisioning product. These same questions can be used to provide an initial assessment of several vendors. A customer’s understanding of a vendor’s capabilities is likely 10x faster and deeper with an interactive session versus reading the answers in a questionnaire. Nuanced and follow-up questions can be asked to gather a complete understanding. Alternative solutions can be explored. This exercise doesn’t have to replace an RFP but instead can better inform the customer about the questions they need answered in order to issue an RFP. Don’t be afraid to talk to a vendor, even if you’re not sure what you want in a new product. In fact, talk to several vendors. More than likely, you’ll learn a lot more via a discussion than you will via an RFI questionnaire. What’s good about an RFI or RFP is coming in with prepared questions. That way, you can judge each vendor using the same criteria but, if possible, get the answers to those questions via an interactive session with the vendors. Next: How to write an effective RFP or RFI.
The ongoing COVID-19 pandemic has facilitated an increase in information collection among consumers and organizations, creating a prosperous climate for cybercriminals. As businesses and customers adjust to the “new normal,” hackers are honing in on their targets and finding new, more sophisticated ways to access their sensitive data. As part of our recently launched Q&A perspective series, Michael Bruemmer, Experian’s Vice President of Data Breach Resolution and Consumer Protection, provided insight on emerging fraud schemes related to the COVID-19 vaccines and how increased use of digital home technologies could lead to an upsurge in identity theft and ransomware attacks. Check out what he had to say: Q: How did Experian determine the top data breach trends for 2021? MB: As part of our initiative to help organizations prevent data breaches and protect their information, we release an annual Data Breach Forecast. Prior to the launch of the report, we analyze market and consumer trends. We then come up with a list of potential predictions based off the current climate and opportunities for data breaches that may arise in the coming year. Closer to publication, we pick the top five ‘trends’ and craft our supporting rationale. Q: When it comes to data, what is the most immediate threat to organizations today? MB: Most data breaches that we service have a root cause in employee errors – and working remotely intensifies this issue. Often, it’s through negligence; clicking on a phishing link, reusing a common password for multiple accounts, not using two-factor authentication, etc. Organizations must continue to educate their employees to be more aware of the dangers of an internal breach and the steps they can take to prevent it. Q: How should an organization begin to put together a comprehensive threat and response review? MB: Organizations that excel in cybersecurity often are backed by executives that make comprehensive threats and response reviews a top corporate priority. When the rest of the organization sees higher-ups emphasizing the importance of fraud prevention, it’s easier to invest time and money in threat assessments and data breach preparedness. Q: What fraud schemes should consumers be looking out for? MB: The two top fraud schemes that consumers should be wary of are scams related to the COVID-19 vaccine rollout and home devices being held for ransom. Fraudsters have been leveraging social media to spread harmful false rumors and misinformation about the vaccines, their effectiveness and the distribution process. These mistruths can bring harm to supply chains and delay government response efforts. And while ransomware attacks aren’t new, they are getting smarter and easier with people working, going to school and hosting gatherings entirely on their connected devices. With control over home devices, doors, windows, and security systems, cybercriminals have the potential to hold an entire house hostage in exchange for money or information. For more insight on how to safeguard your organization and consumers from emerging fraud threats, watch our Experian Symposium Series event on-demand and download our 2021 Data Breach Industry Forecast. Watch now Access forecast About Our Expert: Michael Bruemmer, Experian VP of Data Breach Resolution and Consumer Protection, North America Michael manages Experian’s dedicated Data Breach Resolution and Consumer Protection group, which aims to help businesses better prepare for a data breach and mitigate associated consumer risks following breach incidents. With over 25 years in the industry, he has guided organizations of all sizes and sectors through pre-breach response planning and delivery.
When I worked as a junior analyst for one of the largest credit card issuers in the United States, the chief credit risk officer required the development of a “light switch report” and strongly encouraged everyone in her organization to read the report every day. She called it the light switch report because every morning when she walks into her office and the lights switch on, she would read the report and understand what’s going on with the business. I took her advice and developed the habit of reading the light switch report every morning — for more than a decade while I was with the organization. I knew the volume of applications, the approval rate and the average line of credit of approvals. I developed an informed idea of how delinquency rates would look six months into the future based on the average credit score of approvals today. Her advice was valuable, and the discipline she shared helped me develop my skill sets as a junior analyst, a people manager and head of a retail business line. Performance reports are foundational and are one of the key elements of a sound and prudent risk management framework. Regulators require effective monitoring reports and provide guidance on report generation as part of its examination process. (Office of the Comptroller of the Currency. Comptroller’s Handbook, Retail Lending Safety and Soundness. April 2017. Page 15.) While supporting lender clients on strategy designs and development, I have an opportunity to review various performance reports. I’d like to take this time to reiterate some of the basic components of a good performance report. Knowledge of audience is primary. Good performance reports are tailored for specific audiences who can make decisions that will affect specific outcomes. Performance reports for day-to-day monitoring would be different from reports designed for executive leadership. Transparency and accuracy are required and when reports are designed in support of areas of responsibility, those reports become meaningful and transformative. Relevant metrics matter. Once you identify the report’s audience, the metrics you choose to appear in the report become the next important exercise. Metrics should be relevant and consistent with the audience who’s expected, upon reviewing the report, to make statements such as the business is doing well and stable, or corrective action is needed. For example, a report on the predictive power of credit risk scores intended for model developers will likely contain metrics such Kolmogorov-Smirnov (KS), Gini index or worst scoring capture rate. Such reports won’t include the average handling time of an application, which will be more appropriate for an operations team. Metrics become even more powerful for decision-makers when calculated at a segment level. I’m a big fan of vintage reports. They tell the story of current lending practices (e.g., approval rates, average loan amount, average booked credit risk score), and more significantly they often foretell future performance (e.g., delinquency rates, charge-off rates). These foresights allow analysts and managers to plan and develop strategies today to manage the future state. If approve or decline decisions use a dual score matrix, generate a report showing the volume of applications on the dual score matrix. It’s quicker to spot unusual distributions compared to expectations when data is presented at this sublevel. The benefit is swifter modification or new actions when needed. If statistical designs are utilized, such as test or control segments and champion or challenger segments, metrics calculated at these levels become insightful. They allow validation of a randomized process and support statistical analysis and statements. Timeliness of reports is critical. Some reports for operational or technology purposes require constant and continuous reporting. Daily reports are important especially when new strategies are implemented. Sometimes daily reports are far more relevant within the first two or three weeks of a new strategy implementation. When daily reports show stabilization and alignment to expectations, switching to weekly or monthly reports is acceptable. Most retail products are designed for review on a cycle or monthly basis. Monthly and quarterly reports are milestones and provide good health checks of the business. Don’t forget formats. If a picture is worth a thousand words, then use charts and graphs to display data and capture audience attention. We’re all used to seeing data presented in tables, but there are far more applications today that allow us to read reports with compelling graphics, trendlines and patterns that grab our curiosity and draw us into the story. I like narratives even if they appear as headlines on a report. Succinct comments show discipline and convey understanding of a report’s contents. Effective performance reports evolve as the business changes. Audience, metrics and segments will change, but the basic components provide general guidelines on developing consistent and relevant reports.
The ongoing COVID-19 crisis and the associated rise in online transactions have made it more important than ever to keep customer information accurate and company databases up to date. By ensuring your organization’s data quality, you can allocate resources more effectively, minimize costs and safely serve your customers. As part of our recently launched Q&A perspective series, Suzanne Pomposello, Experian’s Strategic Account Director for CEM vertical markets, and William Palmer, Senior Sales Engineer, provided insight on how utility providers can manage and maintain accurate client data during system migrations and modernizations, achieve a single customer view and implement an operational data quality program. Check out what they had to say: Q: What are the best practices for effective data quality management that utility providers should follow? SP: To ensure data quality, we advise starting with a detailed understanding of the data your organization is currently maintaining and how new data entering your systems is being utilized. Conducting a baseline assessment and being able to properly validate the accuracy of your data is key to identifying areas that require cleansing and enrichment. Once you know what improvements and corrections need to be made, you can establish a strategy that will empower your organization to unlock the full potential of your data. Q: How does Experian help clients improve their data hygiene? SP: Experian has over 30 years of expertise in data cleansing, which is tapped to help clients deploy tactics and strategies to ensure an acceptable level of data integrity. First, we obtain a complete picture of each organizations objectives and challenges. We then assess the quality of their data and identify sources that require remediation. Armed with insight, we work alongside organizations to develop a phased action plan to standardize and enhance their data. Our data management solutions satisfy a wide range of needs and can be consumed in real-time, bulk and batch form. Q: Are there any protection regulations to be aware of when obtaining updated data? WP: Unlike Experian’s regulated divisions, most Experian Data Quality data elements are not burdened by complex regulations and restrictions. Our focus is on organizations’ main customer data points (e.g., address, email address and phone). We reference this data against unregulated source systems to validate, append and complete customer profiles. Experian’s data quality management tools can serve as a foundation for many regulatory, compliance and governance requirements, including, Metro 2 reporting, TCPA and CCPA. Q: Are demos of Experian’s data management solutions available? If so, where can they be accessed? WP: Yes, you can visit our website to view product functionality clips and recorded demonstrations. Additionally, we welcome the opportunity to explore our comprehensive data quality management tools via tests and live demonstrations using actual client data to gain a better understanding of how our solutions can be used to improve operational efficiency and the customer experience. For more insight on how to cleanse, standardize, and enhance your data to make sure you get the most out of your information, watch our Experian Symposium Series event on-demand. Watch now Learn more About Our Experts: Suzanne Pomposello, Strategic Account Director, Experian Data Quality, North America Suzanne manages the energy vertical for Experian’s Data Quality division, supporting North America. She brings innovative solutions to her clients by leveraging technology to deliver accurate and validated contact data that is fit for purpose. William Palmer, Senior Sales Engineer, Experian Data Quality, North America William is a Senior Sales Engineer for Experian’s Data Quality division, supporting North America. As an expert in the data quality space, he advises utility clients on strategies for immediate and long-term data hygiene practices, migrations and reporting accuracy.