Author: Lucia Herrera

Compliance & Collections: 22 Essential Terms to Know

By on September 8th, 2022 in Compliance, Industry Insights

The world of regulatory compliance can be a complicated place, especially when it comes to debt collection. It can be tricky for non-security and compliance professionals. To help quickly get you up to speed on what auditors are referring to, we’ve put together a glossary, covering some of the most important compliance terms and acronyms.

  • Action Plan: A plan to identify and facilitate remediation steps of current operating practices. 
  • Audit: An unbiased and comprehensive examination of an organization’s compliance and adherence to regulatory guidelines. 
  • Benchmarking: The process of analyzing an organization’s performance data and comparing it against the industry standard. Used to see the effectiveness of a compliance program and if there are any areas that need improvement. 
  • Best Practices: When law and/or regulation is unclear, a “best practice” policy may be implemented to safeguard a business’s compliance.
  • Bona Fide Error Defense: An unintentional mistake or violation that occurred despite the maintenance of procedures reasonably adapted to avoid the mistake/violation. A debt collector may be able to assert a “Bona Fide Error Defense” in a lawsuit alleging violations of the federal Fair Debt Collection Practices Act (FDCPA). 
  • CCPA: The California Consumer Privacy Act (CCPA) gives consumers in California rights over the personal information that businesses collect and process about them.
  • CFPB: The Consumer Financial Protection Bureau (CFPB) is an agency of the United States government responsible for consumer protection in the financial sector.
  • Code of Ethics: A document or guide that is composed of an organization’s values, standards commitments, and a set of principles. 
  • Compliance: The state of adhering to established guidelines or specifications such as a policy, standard, specification, or law.
  • Compliance Management System: A series of integrated policies, processes, tools, internal controls, and functions designed to help an organization manage, monitor, and test  compliance with applicable laws and regulations (e.g., federal, state, local/municipal). A fully functioning compliance management system is designed to continuously minimize risk, prevent consumer harm and limit financial or reputational harm to the organization. An essential in the modern business world.
  • Compliance Risk: Captures the legal, financial, and reputational dangers for failing to act in compliance with laws and regulations.
  • Conflict of Interest: A conflict that happens in a decision-making situation in which an individual or organization is unable to remain impartial and where serving an interest would harm another.
  • Controls: A checks put in place to ensure compliance with a policy and procedure. A control could be automated or manual.  
  • Dodd-Frank Act: Dodd-Frank Wall Street Reform and Consumer Protection Act is a US federal law that governs the financial industry by enforcing transparency and accountability with rules for consumer protection, such as its Unfair Deceptive Acts and Practices provision. 
  • FDCPA: The Fair Debt Collection Practices Act (FDCPA) is a consumer protection law passed by Congress in 1977 to eliminate abusive debt collection practices and insure that those debt collectors who refrain from using abusive debt collection practices are not competitively disadvantaged.
  • Fraud: The act of intentionally lying and cheating in order to obtain an unauthorized benefit. 
  • Governance: A formal framework made up of policy rules, processes, procedures and controls used to control risk and ensure accountability and transparency. 
  • Gray Area: A situation where the rules are not clear and can be open to interpretation.
  • Regulation F: A rule implemented by the Consumer Financial Protection Bureau (CFPB)  providing rules governing activities covered by the Fair Debt Collection Practices Act (FDCPA). It seeks to clarify and expand on the FDCPA, including requiring  collection agencies to provide additional information to consumers as part of the validation disclosure and clarifies rules for the use of digital communications. 
  • Remediation: The process of recognizing a compliance issue or deficiency and implementing an action plan to correct the deficiency or enhance/strengthen an area of compliance.  For remediation to be successful, the new or revised policies, processes or controls must address the deficiency or issue and to minimize risk. 
  • Risk Assessment: The process of identifying and analyzing all potential risks that an organization can face in relation to its legal and regulatory obligations. The results of risk assessments are prioritized based on severity and then used to determine areas of focus for risk mitigation.
  • Safe Harbor: A provision in a statute or regulation that protects against legal or regulatory liability in situations where the safe harbor provision conditions are met.
  • Transparency: The act of being open and honest while disclosing as much information about policies, procedures, and activities as possible.

Now armed with your glossary of terms, get ready to investigate the world of compliance in collections further in our upcoming webinar. Join us Thursday, September 29th at 1pm ET for our interactive webinar, The Future of Collections & Compliance, hosted by TrueAccord Associate General Counsel Lauren Valenzuela and Director User Experience Shannon Brown.  

Reserve your space now for an interactive discussion on:

  • Cutting edge digital collection compliance
  • The role of the legal team in creating a digital collection strategy
  • How cutting edge compliance drives collection revenue
  • The future of digital compliance

Register now for the upcoming webinar»»

How Buy Now, Pay Later is Transforming Online Shopping With Gen Z

By on August 24th, 2022 in Industry Insights, Product and Technology
How Buy Now Pay Later is Transforming Online Shopping With Gen Z

Buy Now, Pay Later (BNPL) plans have taken over as a popular financing option for consumers, partly due to an increase in online shopping demands during the pandemic. In 2021, Americans spent more than $20 billion through BNPL services, taking up a bigger part of the $870 billion-a-year online shopping market. From laptops and airline flights to clothing and furniture, BNPLs make it simple to pay for almost anything in small installments. Since the start of the pandemic, millions of international consumers, especially Gen Z (10-25 years old), have gravitated toward using this service. According to a study by Forbes, BNPL use among Gen Z has grown 600% since 2019. The rise of interest in BNPL is also likely influenced by increased financial uncertainty, high-interest rates and a downward trend in credit card approval. As consumers show preference for digital financial services, BNPL continues to grow and become available at more retailers. 

Why are BNPLs Popular with Gen Z?

Services like Afterpay, Klarna, Affirm and others have gained a lot of popularity in recent years, especially among younger generations who may struggle with cash flow. With BNPL, the first payment is due at the time of purchase, with subsequent interest-free payments usually due within a few weeks or months. 

More and more, BNPL providers are reaching these younger audiences through influencers and brands on TikTok, and the variety of goods and services you can purchase with the service continues to expand. Some popular buy now, pay later items include clothing, concert tickets, cosmetics, electronics, furniture, groceries, hotels and flights.

But, like credit cards, missing payments can result in late fees and other penalties. With Gen Z, there’s already a pattern of missing payments. A survey conducted by Piplsay showed that 43% of Gen Zers missed at least one BNPL payment in 2021. 

Gen Z Favors BNPL More Than Other Generations

Debt types and payment preferences constantly change along with technology. The traditional credit card debt is being replaced by BNPL, specifically when we look at Gen Z. For one, it’s easier to be approved for a BNPL application since the process only requires a soft credit check, unlike a hard credit check that most credit card issuers require. When looking for an alternative to high-interest credit cards, BNPL installment payment plans are a popular option. BNPL consumers know upfront what will be expected of them, and the possibility for large debt build-up is replaced with a finite number of payment installments. This transparency and manageability make it easier to understand. And it’s one that has the potential to continue to evolve for the better by providing consumers with more inclusive credit and payments options.

When it comes to both luxury and essential purchases, younger consumers are more likely to take advantage of BNPL to afford them. A survey from TrustPilot found that 45% of consumers between the ages of 18 and 34 were likely to use such services for basic essentials while 54% would use them for luxury items. For those aged between 34 and 54, these results were 33% and 38% respectively. And for people aged 55 and up, the results were 16% and 24%. 

Since it’s quite easy to sign up for one or more BNPL loans, the likelihood of losing track of payments or overspending is real, especially for Gen Z. According to a report from J.D. Power, about one-third of younger consumers said they spent more than their budget allows with BNPL. And since different retailers offer financing through various BNPL services, it can also be a challenge to track multiple accounts at once. This isn’t surprising as some of the younger generations do not have the financial literacy or experience that older generations have and they’re more likely to face consequences and penalties like missing a payment.

Meet Gen Z Where They Are to Effectively Recover More

The good news is that the outlook for Gen Z BNPL customers that end up with accounts in collection is different than for those who default on credit card debt. On average, BNPL debts see higher and faster repayment rates than similar-sized credit card debts. Higher engagement leads to better repayment rates. According to TrueAccord data, the percent of BNPL customers who make a payment is more than double the like-size credit card accounts at 30 days post placement and 50% higher at 90 days. 

As a debt collection platform that engages digital-native consumers where they are and with a priority on customer experience, many leading BNPL providers partner with TrueAccord to address both early delinquencies and charged-off accounts. After these BNPL customers repay their loans and have a positive experience, they’re able and likely to use the service again, and this time with some experience about how it works. By using this information, TrueAccord can help find the most optimal ways to reach the younger audience and help them pay off their debt from BNPL. 

Want to learn more about how to engage with consumers of any generation in whatever stage of collection they might be in? Schedule a consultation to see what TrueAccord’s digital solutions can do for your debt recovery strategy. 

Further Reading: 

National Financial Awareness Day: Why Financial Literacy is Beneficial For Everyone

By on August 11th, 2022 in Industry Insights

August 14 is National Financial Awareness Day, making it an appropriate time to shine a spotlight on initiatives that can help improve consumer financial awareness in the collections space. Financial literacy is an essential life skill that benefits people throughout their lives, but is often overlooked when it comes to what happens if a payment is late or missed. Financial literacy during delinquency is just as important as planning for the future—and can even play a big part in financial future-planning.

Whether it’s taking out a loan, buying a house, saving for retirement or purchasing goods on a credit card,, people are constantly being asked to make decisions that affect their personal finances. As reported by the Milken Institute, only about 57% of the American population is considered financially literate. In order to address this gap, lenders are in a unique position to help provide customers with educational content that not only improves customers’ financial literacy but helps with their own retention and acquisition strategies by building and maintaining customer trust and loyalty. Providing consistent outreach—especially in early delinquency—will give customers more opportunities to engage, understand, and resolve debt.

Debt levels are on the rise again: according to the New York Federal Reserve, between the national student loan debt topping $1.6 trillion in 2022 and household credit card debt also climbing, we’re seeing the largest quarterly increase in 22 years at $860 billion. And individuals become more susceptible to going further into debt if they don’t have a solid foundational understanding of what happens when they first fall behind. Overall, lower levels of financial literacy end up contributing to increased rates of bankruptcy, defaults, and foreclosures.

As financial services leaders know, maintaining customer relationships—including accounts in early delinquency—is more profitable than writing off bad debt due to ongoing loan and credit losses, and then having to start the acquisition process for a new customer all over again. The Receivables Management Association International (RMAI), a non-profit trade association for businesses in the financial services industry, understands this gap and the need for increased literacy created a website with many useful literacy resources for consumers offering free education on topics like managing personal finance, money, and investing. By sharing tools like this or taking on an array of education initiatives and implementing financial literacy as a component of your debt recovery strategy, businesses can help their customers regain their financial health.

TrueAccord is a certified business through RMAI’s Certification Program requiring an independent audit to confirm compliance with a set of rigorous uniform industry standards of best practice which focus on the protection of the consumer. Interested in learning how TrueAccord can help create a customizable user-beneficial experience for your customers? Schedule a consultation to see what TrueAccord’s digital solutions can do for your debt recovery and education strategy»»

What are We Seeing in Consumer Credit Trends Today? A Video Interview with Ohad Samet

By on August 9th, 2022 in Industry Insights, Industry Interviews, Webinars

The financial landscape for both consumers and businesses is particularly uncertain right now. Many new fintechs and neobanks are experiencing their first delinquency surge and others soon to follow. This year, the challenges of managing delinquencies and navigating an uncertain economy will compound, making it imperative for companies to critically think about their strategy to collect from consumers in debt.

But from the perspective of a seasoned veteran of the financial services industry, what are we really seeing in consumer credit trends today? And what should businesses really be preparing for tomorrow?

We sat down with TrueAccord co-founder Ohad Samet to get his insights on what we’re seeing in consumer credit trends today, managing delinquencies, and how to navigate in this economy. Watch our interview or read the transcript below»»

What are we seeing in consumer credit trends today?

OHAD SAMET, TrueAccord co-founder:
I think we all notice that we’re dealing with a lot of lagging indicators in terms of consumer capacity to pay. Of course, one leading indicator is demand for credit. But in terms of what consumers are able to do—meaning their sentiment—are they willing to pay? Are they able to pay? Do they have enough disposable income? So many of these numbers are trailing indicators.

However, consumer net worth is still high. Why is that? It’s because stocks in primary, the value of primary residences, is calculated in the net worth of consumers. And so if you believe there was a bubble or just a run up in prices because of a lot of demand and very low supply, then that would artificially inflate the net value or net assets of consumers, and we will only discover how consumers are faring realistically in a few months.

Even if from a trailing indicator perspective, meaning delinquencies, net worth and so on, we are not seeing a drop yet. We’re only seeing banks increase their loss reserves in anticipation for losses.

We are definitely seeing a change in consumer sentiment. It can be because they’re running out of money. It can be because of general sentiment in the market. Inflation is up, risk is up, consumers start saving more—but we are definitely seeing that. And that, to me, is a leading indicator that we all need to be aware of.

Interested in learning how you can get ahead and prepare for delinquencies before they happen? Schedule a consultation to learn how TrueAccord can help you get started on your collection strategy»

Bridging the Gap Between Machine Learning and Human Behavior with HeartBeat

By on June 27th, 2022 in Industry Insights, Machine Learning, Product and Technology

When it comes to engaging consumers in debt collection, behavioral science helps us to understand and respond to an individual’s situation, motivations, and contact preferences.

For example, we know that consumers don’t like being called by debt collectors. With that knowledge, behavioral science then helps us determine the optimal way to meet consumers where they are, contact them when they want by using their preferred channels, and lastly sending a message that resonates with them enough to engage.

It starts with a lot of engagement data. At TrueAccord, we’ve been collecting data about how consumers engage with us for nearly 10 years to determine the optimal ways to engage with consumers, and then use that data to generate a special collections experience just for them – from best time, best channel, and best language to engage that individual consumer.

Take content for example, each person is unique and different people respond differently to different communications. They are driven to action by different words and are convinced for different reasons. In writing content, it’s our goal to write content that responds to these individual needs.

There are 2 things we consider when writing content for collection communications: content type and content dimensions.

  • Content type is what we send based on a user’s actions. As an example, following up on a page view—if a consumer is viewing a payment plan, disputing a debt, or thinking about unsubscribing but drops off the page, we will try sending a follow up email or SMS with other plan options, information about the account, a description of how to unsubscribe or dispute for them to view. We will continue to try different content types until we find the right one that engages the consumer.
  • Content dimensions are more established behavioral science frameworks used to ensure that our communications vary in style and tone so that we are speaking to consumers in a unique way that will motivate them to engage. Everyone responds to different motivations so we use a variety of different frameworks until we find the one that connects with the individual

Each piece of content is tagged depending on the content type and dimensions so it can be easily used by HeartBeat, our powerful and intelligent patented-machine learning engine. Good content will lend itself well to automated, data-driven prioritization done by HeartBeat to present customers with the best possible content item at each given time.

How can technology personalize the debt collection experience?

By using technology and behavioral science to determine the best way to communicate with consumers, we are able to personalize each user’s unique experience. Our patented machine learning engine mentioned above, HeartBeat, allows us to do just that. HeartBeat collects engagement data and then, after analyzing multiple solutions, suggests the best possible treatment depending on the individual and their engagement. HeartBeat also uses a real-time feedback loop so the technology can adapt to a consumer’s engagement right as it happens.

Instead of relying on data like age and location, HeartBeat uses engagement data to personalize the communication process. The engagement data is collected every time a consumer engages in a certain way, whether it’s clicking on an email or SMS, visiting a webpage, and/or viewing payment plan options. Our system learns what motivates the consumer and responds with content or payment options that will resonate with them.

For example, if the consumer clicks on an email that uses likable content mentioning “short term cash flow,” our system may determine to send a friendly follow up email letting them know that they can set up a payment plan that starts on a later date when they’ll have the ability to make a payment. We know what motivates an individual may change from day to day depending on their circumstances, so we treat them based on their active engagement and behavior with our system rather than construct a specific profile for each consumer and treat them based on that basic account profile.

By combining behavioral science and machine learning, the best-possible payment options are offered to customers based on their debt situation, previous communication, and engagement data. Whether their actions show that they would benefit from a long-term payment plan, or if it shows that they’d prefer to pay in full, HeartBeat will suggest the best option for that customer. The power of using behavioral science and machine learning is anticipating the needs and preferences of our customers and using that to help them as seamlessly as possible.

Overall, there is no one way of communicating that will work for everyone across all situations, and tailoring communication and collection strategy to align with consumer preferences is better for both the consumer, lenders, and our business. That’s why building the bridge between machine learning and human behavior is essential.

Discover how HeartBeat can help humanize your collection process in our new in-depth eBook, Upgrade Debt Recovery & Collection With HeartBeat, available for download here»

Learn more about behavioral science from TrueAccord’s User Experience Director, Shannon Brown in a new interview in Collector Magazine here»

How Making the Switch to Digital-First Helped Recover $17M with TrueAccord’s Retain Platform

By on June 6th, 2022 in Industry Insights
How Making the Switch to Digital-First Helped Recover $17M with TrueAccord's Retain

When COVID hit in 2020, one Fortune 500 company needed to find an effective way to communicate and collect from the rising overdue accounts, with many of their customers falling into financial hardships. While the company had previously relied on old-school communication tactics like direct mail and an in-house call center to reach customers who had delinquent accounts, they knew a better solution was needed. 

The company had already observed firsthand a rise in customers’ preference for digital communications between mobile apps and online bill pay options, making it clear that this was the best route to go. Rather than build from scratch in-house—which would’ve been costly and time-consuming—the company evaluated third-party options before choosing TrueAccord and implementing Retain, the client-labeled early-stage collections solution. 

Once implemented and customized to fit the company’s needs, TrueAccord helped them collect over 63,000 payments to recover over $17 million. 

Retain’s digital outreach strategy made a significant impact on customer engagement and resolution beyond just payments with improvements across their paid in full rate, overall collections rate, average amount collected daily, and more. And with the help of HeartBeat, TrueAccord’s powerful machine learning decision engine, they were able to observe behavior data and optimize digital touch points and engagement in real-time. In just a few weeks, this digital collections approach caused a major transformation that only continued to improve. 

Discover all the astounding results in our full Case Study and learn more about how Retain helped the company implement the successful solution. 

Want to see how much more your company could recover with Retain? Request a demo! 

Technology in Collection: 21 Must-Know Buzzwords

By on May 24th, 2022 in Industry Insights, Machine Learning, Product and Technology

Your Guide to Key Terms for Today’s Debt Recovery Strategy

Reaching consumers today requires a more sophisticated process than simply dialing the phone or sending a generic email, especially when it comes to debt recovery and collection. But reviewing potential strategies can often leave you lost in a sea full of acronyms and buzzwords. Between terms like AI, machine learning, and data science, it can be difficult to keep up with the different definitions—and understand how they impact your business and bottom line.

To help keep this word salad straight, we’ve compiled a glossary of helpful terms, definitions, and examples to help differentiate them:

  • Accounts per employee (APE), account to collector ratio (ACR): The number of delinquent accounts that can be serviced by an individual recovery agent – often used to measure cost effectiveness.
  • Artificial Intelligence (AI): AI is a blanket term describing a range of computer science capabilities designed to perform tasks typically associated with human beings. Machine learning (ML) is a subset of AI. Through AI, processes like debt collection can become more efficient by developing better outreach and deployment strategies.
  • Big Data: This term means larger, more complex data sets . Big data can save collectors a lot of time by using many variables for analytics-based customer segmentation, insert, insert..
  • Coverage: The percentage of users for whom organizations have digital contact information, such as email addresses or phone numbers.
  • Customer Retention Rate: Measures the total number of customers that a company keeps over time. It’s usually a percentage of a company’s current customers and their loyalty over that time frame.
  • Data Science: ‍A cross-discipline combination of computer science, statistics, modeling, and AI that focuses on utilizing as much as it can from data-rich environments. Data science (which includes machine learning and AI) requires massive amounts of data from various sources (customer features such as debt information or engagement activity) in order to build the models to make intelligent business decisions.
  • Deep Learning (DL): A subset of machine learning. Deep learning controls many AI applications and services and improves automation, performing analytical tasks with human intervention.
  • Delinquency rate: The total dollars that are in delinquency (starting as soon as a borrower misses as a payment on a loan) as a percentage of total outstanding loans.
  • Deliverability: The percentage of digital messages that are actually reaching consumers (e.g., as opposed to ending up in email spam filters).
  • Digital engagement metrics: A range of KPIs that capture how effectively digital channels are reaching and engaging consumers.
  • Digital opt-in: The percentage of users who have indicated their preference to receive digital communications in a particular channel.
  • Efficiency: Measures a company’s ability to use its resources efficiently. These metrics or ratios are at times viewed as measures of management effectiveness.
  • Machine Learning (ML): Technology that uses algorithmic modeling techniques to observe patterns and trends, reassessing the best approach to achieve a goal, and adapting behavior accordingly. It continuously, automatically learns and improves at a massive scale as more data is observed. With the help of machine learning, companies can make sense of all their data and take on new approaches to debt collection processes from better customer experience to more efficient delinquent fund recovery.
  • Net loss rate: The total percentage of loan dollars that get charged off (written off as a loss).
  • Open rate, clickthrough rate: The percentage of users who are actually opening and clicking digital communications.
  • Predictive Analytics: Predicting outcomes is one specific application of machine learning. It allows companies to predict which accounts are more likely to pay sooner and allows them to better plan operations accordingly.
  • Promise to pay kept rate: The percentage of delinquent accounts that maintain a stated commitment to pay.
  • Promise to pay rate: The percentage of delinquent accounts that make a verbal or digital commitment to pay.
  • Right party contact rate: The rate at which a collections team is able to establish contact with the consumer associated with a delinquent account.
  • Roll rate: The percentage of delinquent dollars that “roll” from one delinquency bucket (e.g., 60 days past due) to the next (e.g., 90 days past due) over a given timeframe.
  • SMS: An acronym that stands for “Short Message Service” referring to text messages on cellular devices.

For more information on how to get started integrating innovative technologies into your debt recovery strategy, schedule a consultation today.