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Have you seen the latest Telephone Consumer Protection Act (TCPA) class action lawsuit? TCPA litigations in the communications, energy and media industries are dominating the headlines, with companies paying up to millions of dollars in damages. Consumer disputes have increased more than 500 percent in the past five years, and regulations continue to tighten. Now more than ever, it’s crucial to build effective and cost-efficient contact strategies. But how? First, know your facts. Second, let us help. What is the TCPA? As you’re aware, TCPA aims to safeguard consumer privacy by regulating telephone solicitations and the use of prerecorded messages, auto-dialed calls, text messages and unsolicited faxes. The rule has been amended and more tightly defined over time. Why is TCPA compliance important? Businesses found guilty of violating TCPA regulations face steep penalties – fines range from $500 to $1500 per individual infraction! Companies have been delivered hefty penalties upwards of hundreds of thousands, and in some cases, millions of dollars. Many have questions and are seeking to understand how they might adjust their policies and call practices. How can you protect yourself? To help avoid risk for compliance violations, it’s integral to assess call strategies and put best practices in place to increase right-party contact rates. Strategies to gain compliance and mitigate risk include: Focus on right and wrong-party contact to improve customer service: Monitoring and verifying consumer contact information can seem like a tedious task, but with the right combination of data, including skip tracing data from consumer credit data, alternative and other exclusive data sources, past-due consumers can be located faster. Scrub often for updated or verified information: Phone numbers can continuously change, and they’re only one piece of a consumer’s contact information. Verifying contact information for TCPA compliance with a partner you can trust can help make data quality routine. Determine when and how often you dial cell phones: Or, given new considerations proposed by the CFPB, consider looking at collections via your consumers’ preferred communication channel – online vs. over the phone. Provide consumers user-friendly mechanisms to opt-out of receiving communications At Experian, our TCPA solutions can help you monitor and verify consumer contact information, locate past-due consumers, improve your right-party contact rates and automate your collections process. Get started

Consumer behavior is constantly evolving — from the channels they prefer to the economic trends spurring varying interest and activity. It’s no surprise that businesses find it challenging to know what their customers want today or tomorrow. But knowing and understanding this information is essential to growing your bottom line. Through years of working with businesses across every vertical, we’ve found that a solid approach to growing your business revolves around your customers. The better you know your customers, the better you can achieve your goals. Seeing the future. How well can you identify and rank your current customer population? Are you leveraging that insight to acquire new customers, manage current customers and prioritize collections efforts? If so, you’re probably using custom models in your business strategy. But if your organization is like many businesses, you may use a more traditional approach. In our highly competitive market, strategy and decisions must be based on the right data and insights. No excuses. The data is there, and we can help you turn it into actionable insights. Implementing a custom model can maximize your return on investment and help you make more profitable business decisions — now and in the future. No palm reading required. Without visiting your local fortuneteller, you still can predict the future. You need a model, but not the “runway” type. What constitutes a highly predictive and effective model? Many factors. A highly predictive custom model should incorporate robust data, advanced modeling methodologies, analytical expertise and attributes. Having these foundational components is essential to knowing your customers and making confident decisions. Models aren’t one-size-fits-all. When you take an innovative approach to model development, the model is targeted to support your specific business goals while providing the documentation required for regulatory reviews. Consider these items as you develop your custom model: Data — It all starts with the right data. Combining multiple data assets — your master-file data, our credit data and any additional data sources — is key to developing a robust model development sample. In other words, a model development sample should represent your future through-the-door population. Model design — To ensure the custom model is designed to help you achieve your specific goals, you’ll want to incorporate the latest analytics and modeling methodologies. An experienced analytics team will be essential here. Segmentation — With the right model development and segmentation strategies, you can identify optimal segments that will result in a more predictive custom model. This way, each consumer is scored on a scorecard developed using a credit profile similar to theirs. Validation — To ensure the model’s predictive ability and longevity, validate each custom model on a holdout sample and compare it with other scores to ensure it accounts for the current and future (through-the-door) consumer populations, as well as policy rule and behavioral changes. Regulatory review — Don’t forget about the documentation needed for compliance. While audits are unpleasant , fines and extensive scrutiny can significantly impact your business. Take your fortunetelling to the next level. Machine learning is all the rage. This cutting-edge technology can be embedded in your predictive models to help uncover patterns in data that may not be apparent otherwise. This can be done by comparing the performance of the machine learning model with your existing models. Once you know that machine learning can add the lift you’re looking for, you can apply that methodology to develop a custom model focused on stability, cost-efficiency, transparency and predictive performance. Predicting behavior across the Customer Life Cycle. How can a custom model benefit you? From improving baseline performance and increasing profitability by approving more good accounts to uncovering opportunities within your target market, custom models can provide the confidence needed to grow your business. Which one of these models can help you achieve your business goals? When it comes to accurately predicting customer behavior, you don’t need a crystal ball. You need a well-built, highly predictive custom model. Use the data that’s available to gain insight into your customers and grow your bottom line. If you need help, we’re here. We have the data, analytics and expertise to help you get started.

Digital channels undoubtedly create convenient experiences for consumers. We have the luxury of applying for loans or creating investment accounts from the comfort of home. However, the same opportunities are available to fraudsters. Fraudsters continue to find creative and innovative ways to expose vulnerabilities across all types of businesses. They prey on inexperienced or low-bandwidth teams that have not invested in the appropriate fraud tools in the past. Despite the imminent fraud risk involved, both consumers and businesses continue to embrace digital channels. With 90 percent of consumers worldwide conducting personal banking online, how do we protect these digital platforms with finite resources? A leading digital financial services company was forced to address this question when they experienced a large-scale fraud attack. But they weren’t in this fight alone. Download the full case study to see how our risk analyst used FraudNet to prevent millions of dollars in fraudulent funding. Client: A leading digital financial services company that operates with zero in-person branches with more than 7,000 employees Challenge/Objective: In October 2018, fraudsters deployed a large-scale, scripted attack against a North American financial services company. The fraud team was extremely understaffed. The fraud team was unable to detect and respond to the attack quickly. The fraudulent account opening activities eventually blended into account takeovers. Resolution: Our risk analyst worked quickly to analyze the geolocation, velocity and device rules firing within FraudNet for Account Opening. By having these rules in place, FraudNet was able to flag and outsort thousands of suspicious applications. Despite being a small team, the fraud investigators were able to work efficiently within the FraudNet workbench and review the true, high-risk applications. Results: Thanks to our risk analyst’s quick remediation and the FraudNet proprietary device rules: 23,800 fraudulent applications were outsorted for review. An estimated $35.7 million in fraudulent funding was prevented. However, the fight against fraud is ongoing. Our risk analyst continues to work closely with the fraud team to develop an effective strategy to prepare against future attacks.


