
In this article…
Lorem ipsum dolor sit amet, consectetur adipiscing elit. Phasellus at nisl nunc. Sed et nunc a erat vestibulum faucibus. Sed fermentum placerat mi aliquet vulputate. In hac habitasse platea dictumst. Maecenas ante dolor, venenatis vitae neque pulvinar, gravida gravida quam. Phasellus tempor rhoncus ante, ac viverra justo scelerisque at. Sed sollicitudin elit vitae est lobortis luctus. Mauris vel ex at metus cursus vestibulum lobortis cursus quam. Donec egestas cursus ex quis molestie. Mauris vel porttitor sapien. Curabitur tempor velit nulla, in tempor enim lacinia vitae. Sed cursus nunc nec auctor aliquam. Morbi fermentum, nisl nec pulvinar dapibus, lectus justo commodo lectus, eu interdum dolor metus et risus. Vivamus bibendum dolor tellus, ut efficitur nibh porttitor nec.
Pellentesque habitant morbi tristique senectus et netus et malesuada fames ac turpis egestas. Maecenas facilisis pellentesque urna, et porta risus ornare id. Morbi augue sem, finibus quis turpis vitae, lobortis malesuada erat. Nullam vehicula rutrum urna et rutrum. Mauris convallis ac quam eget ornare. Nunc pellentesque risus dapibus nibh auctor tempor. Nulla neque tortor, feugiat in aliquet eget, tempus eget justo. Praesent vehicula aliquet tellus, ac bibendum tortor ullamcorper sit amet. Pellentesque tempus lacus eget aliquet euismod. Nam quis sapien metus. Nam eu interdum orci. Sed consequat, lectus quis interdum placerat, purus leo venenatis mi, ut ullamcorper dui lorem sit amet nunc. Donec semper suscipit quam eu blandit. Sed quis maximus metus. Nullam efficitur efficitur viverra. Curabitur egestas eu arcu in cursus.
H1
H2
H3
H4
Lorem ipsum dolor sit amet, consectetur adipiscing elit. Vestibulum dapibus ullamcorper ex, sed congue massa. Duis at fringilla nisi. Aenean eu nibh vitae quam auctor ultrices. Donec consequat mattis viverra. Morbi sed egestas ante. Vivamus ornare nulla sapien. Integer mollis semper egestas. Cras vehicula erat eu ligula commodo vestibulum. Fusce at pulvinar urna, ut iaculis eros. Pellentesque volutpat leo non dui aliquet, sagittis auctor tellus accumsan. Curabitur nibh mauris, placerat sed pulvinar in, ullamcorper non nunc. Praesent id imperdiet lorem.
H5
Curabitur id purus est. Fusce porttitor tortor ut ante volutpat egestas. Quisque imperdiet lobortis justo, ac vulputate eros imperdiet ut. Phasellus erat urna, pulvinar id turpis sit amet, aliquet dictum metus. Fusce et dapibus ipsum, at lacinia purus. Vestibulum euismod lectus quis ex porta, eget elementum elit fermentum. Sed semper convallis urna, at ultrices nibh euismod eu. Cras ultrices sem quis arcu fermentum viverra. Nullam hendrerit venenatis orci, id dictum leo elementum et. Sed mattis facilisis lectus ac laoreet. Nam a turpis mattis, egestas augue eu, faucibus ex. Integer pulvinar ut risus id auctor. Sed in mauris convallis, interdum mi non, sodales lorem. Praesent dignissim libero ligula, eu mattis nibh convallis a. Nunc pulvinar venenatis leo, ac rhoncus eros euismod sed. Quisque vulputate faucibus elit, vitae varius arcu congue et.
Ut convallis cursus dictum. In hac habitasse platea dictumst. Ut eleifend eget erat vitae tempor. Nam tempus pulvinar dui, ac auctor augue pharetra nec. Sed magna augue, interdum a gravida ac, lacinia quis erat. Pellentesque fermentum in enim at tempor. Proin suscipit, odio ut lobortis semper, est dolor maximus elit, ac fringilla lorem ex eu mauris.
- Phasellus vitae elit et dui fermentum ornare. Vestibulum non odio nec nulla accumsan feugiat nec eu nibh. Cras tincidunt sem sed lacinia mollis. Vivamus augue justo, placerat vel euismod vitae, feugiat at sapien. Maecenas sed blandit dolor. Maecenas vel mauris arcu. Morbi id ligula congue, feugiat nisl nec, vulputate purus. Nunc nec aliquet tortor. Maecenas interdum lectus a hendrerit tristique. Ut sit amet feugiat velit.
- Test
- Yes

Traditional credit attributes provide immense value for lenders when making decisions, but when used alone, they are limited to capturing credit behavior during a single moment of time. To add a deeper layer of insight, Experian® today unveiled new trended attributes, aimed at giving lenders a wider view into consumer credit behavior and patterns over time. Ultimately, this helps them expand into new risk segments and better tailor credit offers to meet consumer needs. An Experian analysis shows that custom models developed using Trended 3DTM attributes provide up to a 7 percent lift in predictive performance when compared with models developed using traditional attributes only. “While trended data has been shown to provide additional insight into a consumer’s credit behavior, lack of standardization across different providers has made it a challenge to gain those insights,” said Steve Platt, Experian’s Group President of Decision Analytics and Data Quality. “Trended 3D makes it easy for our clients to get value from trended data in a consistent manner, so they can make more informed decisions across the credit life cycle and, more importantly, give consumers better access to lending options.” Experian’s Trended 3D attributes help lenders unlock valuable insights hidden within credit reports. For example, two people may have similar balances, utilization and risk scores, but their paths to that point may be substantially different. The solution synthesizes a 24-month history of five key credit report fields — balance, credit limit or original loan amount, scheduled payment amount, actual payment amount and last payment date. Lenders can gain insight into: Changes in balances over time Migration patterns from one tradeline or multiple tradelines to another Variations in utilization and credit limits Changes in payment activity and collections Balance transfer and debt consolidation behavior Behavior patterns of revolving trades versus transactional trades Additionally, Trended 3D leverages machine learning techniques to evaluate behavioral data and recognize patterns that previously may have gone undetected. To learn more information about Experian’s Trended 3D attributes, click here.

Many data furnishers are experiencing increases in dispute rates. It’s a tough spot to be in. Data furnishers are not only obligated under the FCRA to investigate and respond to all consumer disputes – reviewing every Automated Consumer Dispute Verification – but they must also do so within less than 30 days. As the number of disputes rise, resources become taxed and the risk of not meeting Fair Credit Reporting Act (FCRA) obligations increases. Let’s face it, consumer disputes aren’t going away, but understanding the reported data and metrics behind disputes can help data furnishers minimize them and defend reporting strategies and processes. 5 Way to Uncover Data Inaccuracy 1. Gain perspective against the industry and peers. Depending on the industry you service, the general benchmarks for dispute rates can vary. It’s important to understand where you fall in regards to dispute rates. Are you trending high or low? As an annualized average, we’ve recently experienced the following industry dispute rates through the end of the year: However, industry averages are just the tip of the iceberg. Measurement against peers can provide a clearer picture of where you fall. Are you an outlier or on par? How do you respond in comparison to peers? Are you deleting the trade as the result of the dispute at a higher rate? This could be an indicator of a systemic problem that needs addressing. 2. Implement pre-submission quality checks. Once you know where you stand, make sure your data is accurate before it heads out the door and hits the consumer’s credit report. Implement manual checks against Metro 2 rules. Build SQL queries to perform your checks. Better yet, use data validation software to automatically identify, track and remediate errors before sending the file to the bureaus. These steps can catch disputes before they happen. 3. Review any data being rejected after submission. Even if your new reporting motto is ‘know before it goes’; once the data has been transmitted, you’ll still want to monitor data being rejected due to Metro 2® errors. When data is rejected that means the update you provided did not make it to file. This leaves room for disputes. Incorporating a robust review of all rejected data in a timely and detailed manner, with updates made before the next reporting period, can improve the accuracy of your data. 4. Audit to identify and correct any stale data on file. An audit for any stale data – which includes open accounts with a balance greater than zero that have not been updated recently – should be performed at least annually. Review, research and remediate any outdated data that could affect your customer, making it susceptible to a dispute. 5. Educate your customers. Why are your customers disputing? Are there common themes within your customer base? Often, a dispute can be eliminated before it happens, with some explanation on the way an account is reported. By providing proactive access to materials and resources that help demystify the credit reporting process, a potentially negative interaction can be turned into a positive learning opportunity, helping the overall customer experience. Learn more about data accuracy solutions.

Credit card balances grew to $786.6 billion at the end of 2017, a 6.7% increase to the previous year and the largest outstanding balance in over a decade. And while the delinquency rate increased slightly to 2.26%, it is significantly lower than the 4.73% delinquency rate in 2008 when outstanding balances were $737 billion. The increase in credit card balances combined with the slight growth in delinquencies points to a positive credit environment. Stay up to date on the latest credit trends to maximize your lending strategies and capitalize on areas of opportunity. Get more credit trends and insights at our webinar on March 8. Register here


