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Tips for an Agile, Digital-first Debt Collection Agency

The State of the U.S. Debt Collections Industry in 2023 

Let’s start from the data. The U.S. debt collections industry is worth $20 billion in 2023, according to IBIS World research. Given that the industry was estimated to be worth only $11.5 billion in 2018, the growth has been remarkable—approximately 73.9% in just five years.

About half of the market share is dominated by the 50 largest ARM companies, over a total of almost 7,000 businesses.

As the industry continues to grow, it has become challenging for executives to keep up with the times. While recovery rates are a key factor influencing competitiveness, technological innovation is the other element defining a company’s success. Digital transformation is no longer a “plus” for agencies, but rather a “must,” and while many ARM companies have embraced change, there is still a long way to go.

In this article, we’ll discuss what it means for a debt collection agency to be agile and adopt a digital-first approach and we’ll go over a few examples of types of technology that agencies are adopting.

What Does It Mean for a Debt Collection Agency to Be Agile?

Business agility is defined as the ability to make changes and decisions quickly. Usually, companies become agile by prioritizing data-driven decision-making, efficiency, flexibility, and innovation. In other words, agility is the exact opposite of stagnation.

According to Entrepreneur, agile decision-making can be related to a variety of issues, such as responding to new competitors or market changes; solving problems as they emerge; launching new products and services; and minimizing time spent internally.

Why is it important to be agile? McKinsey has found that companies that undergo a successful agile transformation gain a 30% increase in operational performance, efficiency, and customer satisfaction.

Digital transformation is a key process influencing agility.

“Some ARM companies have been slow to adopt new technologies and, as a consequence, they are now at a competitive and operational disadvantage,” explained Scott Carroll, industry veteran. “Some didn’t know they needed technology, or they didn’t know exactly where to look and where to start. But now the industry is quickly catching up.”

Carroll explained that tight regulations, concerns over compliance, and widespread litigation are some of the reasons why the industry has been lagging behind in innovation. “Businesses have been naturally more cautious. But now, as they get a better understanding of the regulations, they’re finally looking toward technology to improve their operational efficiency,” he said.

One strength the collections industry has is that it’s usually prepared to pivot: “Because of fast-changing regulations and client needs, the industry needs to be prepared to respond to change.”

How the Industry Is Catching Up by Becoming Digital-first and Tech-savvy

A growing interest in innovation is driving the push toward agility in the ARM industry. Staying updated on new technologies, monitoring emerging tech companies and solutions, and investigating how leading technologies like artificial intelligence can be applied to debt collection are the key tips to implement an agile transformation.

In January 2023, the industry held its first-ever conference entirely dedicated to technology. ARMTech, which took place in Nashville, was a four-day event aimed at helping executives understand the technology that is revolutionizing how debts are collected. The event was organized by Mike Gibb, industry leader and editor of the website AccountsRecovery.net.

The industry is moving toward a digital-first model, as it’s evident that consumers prefer to deal with companies offering omnichannel services and interact through digital channels. Omnichannel includes a wide range of channels, such as website, mobile app, social media, telephony, chatbot, voicebot, SMS, and email.

Telephony systems and dialing platforms are essential for any contact center, including a collection agency, whose business largely depends on outbound and inbound calling. These platforms include TCN, Twilio, Genesys, LiveVox, RingCentral, 8×8, Five9, and more.

Collection management software is the other most common type of software adopted by collection agencies. These systems of record enable agencies to manage their portfolios in one easy-to-use, centralized platform updated regularly by the agents.

Conversational Voice AI, the technology behind voicebots, is gaining ground as a widely popular technology in the ARM industry. Skit.ai has developed an AI-powered Digital Collection Agent, which handles human-like outbound calls to collect payments from consumers. The voicebot intelligently interacts with the consumer, handling payment reminders, negotiation, and processing. The Digital Collection Agent does not substitute the human agents but rather augments their work by handling the most repetitive and tedious tasks. This solution can be easily integrated with the other tools in use.

Voice AI should not be confused with IVR (interactive voice response) systems, a legacy technology that requires consumers to navigate lengthy menus through DTMF inputs or basic voice-enabled inputs.

Key players in the industry are also adopting business intelligence and analytics solutions that support agents during and after their calls with consumers. Prodigal’s solution offers real-time agent assistance, auto-writes call summaries, and analyzes collection calls on dozens of parameters to monitor and boost performance and compliance.

What’s Next?

It looks like 2023 will be a defining year for the collections industry in regard to digital transformation and agility.

“Agility is a key operating factor for success,” advised Scott Carroll. “My tip is to stay current on technology, investigate new tools, stay on top of the latest trends, and keep your eyes open for anything that helps you increase your margins and reduce your exposure. This will ultimately lead to increased collections.”

Entering a New Era of Debt Collections with Conversational Voice AI

Debt collection companies have been automating various parts of their operations, much like companies in other industries. However, one of their core problems—the inability to automate complex conversations with consumers—has impacted their ability to solve their core challenges.

Connecting with consumers to recover payments is at the core of what a debt collection company does. According to a new survey by TransUnion and Datos, communicating with consumers is a top priority for collection agencies. A growing number of agencies are exploring new methods of communication for debt collection, focusing primarily on AI-powered chatbots and voicebots, as well as text messaging.

Conversational Voice AI, with its capability to automate collection calls, solves all significant challenges and ushers in a new era of debt collections. In this blog post, we’ll learn how this technology is dramatically changing the landscape of collections.

How is Voice AI Changing Debt Collections Forever?

100% Account Penetration: A Voice AI solution can initiate and handle millions of calls within minutes, covering an agency’s entire debt portfolio in an impressively short amount of time. This level of automation has never been possible until recently; it’s important to note that over a third of an agency’s files often remain untouched.

Less Dependence on Human Agents: It is hard to recruit a skilled collector, and having a consistent team that can scale up when needed has been extremely challenging for agencies, especially the smaller ones. AI provides the benefit of instant and infinite scalability, making the issue of staffing less concerning. Thanks to end-to-end automation of consumer calls, agencies can scale up and down as needed.

Augmenting Agent Productivity: Voice AI enables live agents to focus on more complex and revenue-generating tasks. Without call automation with Conversational AI, this would be impossible, as live agents would have to spend a lot of time establishing right-party contacts (RPC) and handling time-consuming, repetitive tasks that should be automated.

File Segmentation for Better Recovery: For the first time, collectors can now see the entire picture of their portfolio. As the Voice AI solution goes through the entire portfolio, collectors can see the set of right-party contacts (RPCs), the propensity to pay, and other crucial data that can inform a more strategic and data-driven recovery strategy, ultimately improving collections.

Remarkably Lower Collection Costs: Calls handled by Voice AI cost approximately one-third of a traditional collection call handled by a human agent.

Voice AI Comes with Other Remarkable Benefits. Here Are a Few: 

Lower Compliance and Legal Risk: Voice AI has the potential to improve compliance and reduce the risk of legal issues for agencies. The debt collection space is heavily regulated, and collectors must follow strict compliance rules. With our Augmented Voice Intelligence platform, compliance rules and guidelines such as call frequency, the Mini-Miranda, and other important regulations — both at the federal and state levels — are built into the technology to ensure the Voice AI solution follows them. Voice AI never goes off-script and never has a bad day, protecting both the consumers and the agencies.

Better Decision-making with Data Analytics: Artificial intelligence can analyze consumer data and make informed decisions on the best course of action. For example, Voice AI can use data on a consumer’s payment history, income, and expenses to determine the best payment plan for them. This data-driven approach can lead to more efficient and practical debt resolution outcomes and a better customer experience (CX).

Unprecedented Automation: One of the main benefits of Conversational Voice AI in debt collections is that it automates much of the manual work involved in the recovery process. Debt collectors can use Voice AI to automate tasks such as calling consumers, sending out payment reminders, and recording consumer interactions. This saves time and allows collectors to focus on more complex tasks, such as negotiating payment plans and resolving disputes.

How to Choose the Right Conversational Voice AI Solution Provider for Your Company

The most important thing to remember about a Voice AI solution is that it either works and satisfies the consumer, leading to positive outcomes and recovery, or it will lead to consumer frustration and significantly adverse outcomes. Hence the choice of vendor is highly vital. Here are a few things to consider:

Proven Track Record: To ensure a successful implementation, working with a Voice AI provider with a proven track record in the accounts receivables industry and who can provide a comprehensive and integrated solution is essential. Collection executives prefer to adopt solutions that have been in business in the accounts receivables industry for at least six months.

Ease of Integration: Another priority when implementing Voice AI in debt collections is ensuring the technology is integrated with existing systems and processes. The provider’s capability to integrate with existing systems and other vendors—such as payment gateways—is one of the significant factors that must be considered while selecting a Voice AI vendor.

Ease of Deployment and Use: One of the critical challenges in implementing Voice AI in debt collections is ensuring that the technology is user-friendly for debt collectors and consumers. Make sure that your vendor’s solution is easy to deploy and to use.

Speed of Deployment: The solution must be ready. No promise of building a solution in a few months should be considered, because no viable, working product is ready. Select a vendor who is ready to go live immediately after a series of well-defined tasks required on your end.

Positive Business Outcomes: Look at the results the AI vendors have been about to achieve in the recent past with companies similar to yours. See if these business outcomes and success metrics align with the outcomes you’re hoping to achieve.

Make the Right Choice 

Conversational AI technology is remarkable and has proved its worth in our industry and beyond. The only thing left for debt collectors is the selection of the right Voice AI vendor. Select the right vendor, and it will help you gain a competitive edge and show your tangible positive outcomes in a matter of weeks.

Voice AI technology is about to change debt collections forever; don’t miss out!

To learn more about how Voice AI can help solve your staffing challenges and improve your recovery strategy, use the chat tool below to schedule a call with one of our experts.

What Is User Experience Research (UXR) in Voice AI?

What Is User Experience Research (UXR)?

When building any product, solution, or interface, you want the end result to be as user-friendly as possible. To achieve this, companies typically conduct a thorough background research of the product’s prospective users. That’s where User Experience Research comes into play.

User Experience Research (UXR) is the study of target users, their behavior, and their needs; this multi-step process enhances the design process with a user-centric approach.

A Conversational Voice AI solution — i.e. a voicebot — is no different. Skit.ai relies on a team of CUX (Conversational User Experience) designers and UX researchers to build its Digital Voice Agents for new clients and use cases. In this article, I’ll walk you through the research process required to build a Digital Voice Agent.

How Does the CUX Process Work?

Building the Conversational User Experience for a Digital Voice Agent typically involves five main steps: planning, design, testing, deployment, and maintenance. In the table below, you can see the different steps and the sub-steps they involve:

Sourced from presentation; by Divya Verma Gogoi, Director, Skit.ai

How does the research process work? First of all, the CUX researcher meets with the client, the Solutions Product Manager, and the CUX designer. Together, they identify the company and brand’s values for a preliminary persona ideation of the voicebot. More on that later.

Secondary Research: Industry, Competitors, Use Cases

The researcher conducts in-depth research on the client’s industry, the use cases (or functions) that the Digital Voice Agent will need to address and help customers with, and the target audience the voice bot will cater to.

Additionally, the researcher conducts a competitor analysis to assess the existing landscape, the competitors’ offerings, and their target audiences. For example, the researcher might look into which FAQs are addressed by the competitors’ offerings. Through the competitive analysis, the researcher might identify windows of opportunity and help the client gain a competitive edge.

Primary Research: User and Customer Service Agent Interviews

At this stage of the process, the researcher conducts interviews with both internal and external stakeholders. Internal stakeholders are team members currently working for our company, while external users are usually customer service agents who operate in a specific industry or company; these often include the client’s live agents.

The researcher usually interviews the client’s top-performing agents to get insights into their approach and techniques. The agents are asked to solve some example scenarios, provide a process view of their call flow, and share any insights they have gathered from their experience.

Through this round of interviews, the researcher seeks to learn more about the client’s product or solution, the frequently asked questions (FAQs), and what makes a call successful. Any call data analyses that the client can provide are helpful, too.

At the end of this step, the researcher usually gathers all of the findings in a comprehensive, data-based analysis.

Voicebot Persona Research

Every company has its own voice, and therefore every company deserves a custom-made voicebot. The Digital Voice Agent can also be tailored to the company’s voice and brand, as it will inevitably become another expression of the brand itself.

The persona design is not always performed, but it’s often an essential part of the design process. It involves shaping the bot persona around the company’s values and brand identity, which are expressed through the way the voicebot communicates and interacts with the consumers.

User Research: User Flow, User Journey, and User Behavior

Another important aspect of the research process is the study of the users that will ultimately be interacting with the Digital Voice Agent. This step is essential for the CUX Designer to be able to create useful and meaningful conversation flows for the voice bot.

User flows are diagrams used by designers to understand the patterns users may take when interacting with the voicebot. User flows will change significantly depending on the use case and the customer’s needs. User flows are usually granular and detailed.

The user journey is a more macro view of the user experience during the interaction with the voicebot.

User behavior depends on the audience that the company commissioning the Voice AI solution is targeting. With thorough user research, the CUX researcher aims to understand the users’ behavior, needs, and the approach they typically prefer. Studying user behavior helps researchers and writers make the solution more user-friendly.

The team creates user personas and dialogued interactions in order to see how each user is likely to interact with the Digital Voice Agent. For example, one user persona could be Jane, a 33-year-old entrepreneur and micro-influencer who lives in Green Point, Brooklyn. Three years ago, Jane took a loan to launch he
custom embroidery t-shirt brand. Today, Jane receives a call from the Digital Voice Agent on behalf of a collections agency about her overdue loan. The designer will draft a sample conversation between Jane and the voicebot.

User Experience Research is just the beginning of the process. These research insights are then converted to meaningful design actionables. Design and testing follow, with deployment completing the process.

Are you curious to learn more about Voice AI and its applications across various industries and use cases? Check out our blog!