State-level Regulations Are Just as Important as the Federal Ones
Virtually everyone working in the accounts and receivables industry is familiar with Reg F, the law passed in 2021 to update the Fair Debt Collections Practices Act (FDCPA). Reg F provides parameters for call frequency in debt collections; in particular, the 7x7x7 rule, which allows a maximum of 7 calls in a 7-day period, and allows the collector to follow up only 7 days after having had a conversation with the consumer.
However, some states have stricter laws when it comes to the debt collection industry and call frequency.
When training new agents or deploying a new software solution for your collection strategy, it’s important not to forget these state-level regulations, which are just as important as the federal ones.
Examples of State-specific Regulations for Collection Calls
Here are three examples of state-level regulations that limit call frequency permissions further than Reg F.
Massachusetts: According to the Attorney General’s regulations, creditors and collection agencies are allowed to make a maximum of 2 attempts of communication via telephone (calls or text) in a 7 consecutive day period.
New York: New York’s law is similar to Massachusetts’. Also here, collectors are not allowed more than 2 attempts of communication (calls, texts, letters, emails, etc.) in a 7-day period.
North Carolina: Collection agencies are allowed to make only 1 attempt of communication to a particular third party in a 7-day consecutive period to obtain location information.
How Skit.ai’s Compliance Filters Tackle State Regulations
Working with legal and compliance experts, at Skit.ai we’ve compiled the different state-level regulations and have integrated them into our Voice AI solution’s compliance filters.
Our solution identifies the state of the consumer through the zip code of their most recent address and identifies the applicable regulations in real-time during the campaign initiation process. This way, Skit.ai’s solution never dials out a non-compliant call to a consumer.
Want to learn more about how Conversational AI can help you streamline your collection strategy and comply with all regulations? Schedule a call with one of our experts using the chat tool below.
It’s unlikely, for anyone working in the accounts and receivables industry, to not have heard about Voice AI. Whether you’ve attended an industry event or you’ve visited an industry website, you’ve encountered this technology, which many collection agencies across the country have been adopting to accelerate and improve their collection strategy.
There are many benefits to using conversational Voice AI for debt recovery. Automation, compliance, business growth, cost-effectiveness—different organizations benefit from it differently. Many agencies have reported that, since adopting Voice AI, they’ve been able to acquire larger debt portfolios, thanks to the increased call volume. Others have reported that the consistency of the technology has been a game changer; after all, artificial intelligence “never has a bad day.”
But what are some of the lesser-known benefits of adopting Voice AI for collection calls?
Inbound Traffic Boost
This is every collector’s dream—increasing the inbound traffic from consumers who want to speak to an agent and resolve their debt. Thanks to Voice AI, which acts as a first line of communication with consumers, you can automate most of your outbound traffic, RPC, and even PTP. The solution can easily transfer calls to your agents, informing them of the relevant context and previous interactions.
“Skit.ai is helping us optimize agent bandwidth, as it enables our agents to spend more time answering high-value inbound calls,” said one of our clients, Rebecca Roberts-Stewart, COO of LJ Ross Associates. “With Skit.ai as our first filter, our long-term goal is to ramp up call automation and increase inbound calls. The Voice AI platform has already helped us take steps in that direction, with the 40% boost in inbound traffic as a testimony to the solution’s efficacy.”
Intelligent Conversations
Both our clients and the consumers interacting with our conversational AI solution are positively impressed with how intelligent the bot sounds. No matter what the user on the call says, the solution knows how to handle it, offering relevant and timely information and finding ways to solve problems in real-time.
The solution is context-rich, meaning that it keeps track of previous interactions to offer the best possible experience to the user.
Positive Customer Experience (CX)
Consumers who have interacted with one of Skit.ai’s virtual assistants can testify to its ability to deliver a positive customer experience.
First of all, with Voice AI, consumers don’t have to wait—they get the assistance they need right away, without having to listen to a Mozart symphony or to a time-consuming IVR menu.
Voice AI establishes right-party contact (RPC) in less than a minute; if the call is transferred to a live agent, consumers won’t need to repeat the RPC step, as their identity has already been authenticated.
According to industry data, the vast majority of consumers (88%) expect organizations to provide self-service support. We’re not surprised: the back-and-forth with Voice AI is easy and painless.
Rigorous Compliance
With a multitude of ever-evolving federal and state regulations, collection executives and collectors often struggle to keep up with the changes. Compliance is one of the most significant pain points and concerns for the industry, as non-compliance can result in major financial losses for creditors and agencies.
Artificial intelligence can make your compliance more rigorous and your collection strategy more secure. Skit.ai’s Voice AI solution adheres to all telephony, data security, and collection-related regulations, such as the FDCPA, Reg F, and TCPA, among others.
Voice AI never goes off script or forgets a regulation; you can trust that, with all the correct compliance filters in place, the solution will rigorously follow every rule, including the Mini-Miranda and call frequency restrictions.
Perfect Timing
You can always count on artificial intelligence to be timely and precise.
An important aspect of the regulatory environment for debt recovery is call frequency, as outlined by Reg F and other state-level laws. Voice AI always complies with those rules, only initiating calls at the right time of the day and never exceeding the maximum number of call attempts allowed by the applicable regulations.
Additionally, follow-up timings with AI are always precise. If a consumer tells the AI that they’re not able to speak at a given moment and asks the solution to call back at a different time, you can be sure that the AI will call back at the exact time requested by the consumer.
Are you interested in learning how Conversational AI can accelerate your collection strategy? Use the chat tool below to schedule a call with one of our experts.
Data Breaches Are No Joke, and They’ve Been Spiking
Data breaches are no joke, and many collection agencies have learned it the hard way—with pricey settlements or even facing bankruptcy as a consequence. A data breach usually involves the leak of user data such as names, email addresses, and passwords. The second quarter of 2023 saw a 156% increase in data breaches globally, with North America leading as the most affected region, according to a new report published by Surfshark and shared by our friends at Accounts Recovery. The United States accounted for 49.8 million leaked accounts in Q2.
The disturbing data highlights the importance of taking data protection measures for collection agencies in the U.S. In a time dominated by digital transactions and interactions, it’s hard to overstate the significance of data security.
For collection agencies, which handle sensitive financial and personal information on a consistent basis, maintaining strong data security measures is not just a legal requirement; it’s a critical aspect of building trust with clients and safeguarding sensitive information.
How can collection agencies better protect their customers’ data and prevent a breach? How should agencies prepare themselves in the event of a breach? What’s a good incident response plan? In this article, we’ll answer these questions and also provide notable examples of data breaches at debt collection agencies in recent years.
Data Security: Legal and Regulatory Requirements
The best-known U.S. law for enforcing the protection of sensitive patient health information is HIPAA. However, there are several other laws that enforce data security for ARM companies.
The Gramm-Leach-Bliley Act (GLBA) is the main privacy law aimed at financial institutions, including collection agencies, and it has been updated with two rules: the Safeguards Rule (2003) and the Final Rule (2021). The latest update to the law includes new requirements, such as encrypting all customer information; multi-factor authentication; secure disposal of customer information; and security awareness training for the staff.
Other data protection and privacy laws collection agencies should be aware of are the Fair Credit Reporting Act and the Dodd-Frank Wall Street Reform and Consumer Protection Act.
Notable Examples of Data Breaches at Debt Collection Agencies
American Medical Collection Agency (AMCA) (2019)
In 2019, the third-party debt collection agency American Medical Collection Agency filed for bankruptcy in the aftermath of a data breach that affected at least 20 million U.S. citizens. Sensitive data such as social security numbers and credit card information were compromised in the breach. In 2021, the company reached a settlement with multiple states.
Professional Finance Company (PFC) (2022)
In 2022, Professional Finance Company (PFC), a Colorado-based collection agency, informed more than 650 of its healthcare provider clients that their data may have been compromised in a massive breach, which affected about 1.9 million patients. The information that was compromised included patient names, addresses, social security numbers, and health insurance data.
NCB Management Services (2023)
Earlier in 2023, the collection agency and debt buyer NCB Management Services said it was the target of a data breach exposing the sensitive information of nearly 1.1 million individuals. The company claimed that the attackers no longer had any of the information on their systems, possibly after an alleged ransom payment had been made.
What Are the Best Practices for Data Security?
Standards and Certifications
Following the relevant standards and seeking the relevant certifications for your business is a key starting point to ensure rigorous data security. One is the Payment Card Industry Data Security Standard (PCI DSS), the main information security standard used by the major card brands. ISO 27002 is an international standard that provides best practices on information security controls; ISO 27001 is a framework for implementing information security management systems (ISMS) to protect sensitive information. Additionally, SOC certifications provide assurance over a service organization’s controls, ensuring security, compliance, risk management, and transparency for stakeholders.
Encryption
Encryption is crucial for both data storage and transmission. It protects the data from unauthorized use and can be implemented on data whether it’s in transit or at rest.
Access Controls
Limiting access to data within the company is a way to protect it from malicious parties. Depending on their roles and responsibilities, employees should have role-based access to sensitive data and documents.
Security Audits and Assessments
Security audits and assessments should be routinely conducted to ensure that the protection measures are up-to-date and effective. Keep in mind that third-party auditors are generally better than self-assessments, even though they are more costly. Audits can help you identify vulnerabilities and enable you to act fast and address them.
Employee Training
Security awareness training platforms such as Vanta and MetaCompliance offer easily digestible online training sessions to sensitize your employees to the importance of data security. These platforms can train employees to recognize phishing attempts, use diverse and strong passwords, etc.
Vendor Management
As a collection agency, you’re likely using third-party vendors for several processes. Whenever you select and onboard a new vendor, always inquire into their data security practices, as they’ll likely have access to your consumers’ data.
Monitoring and Logging
By consistently tracking and recording all system activities and access, debt collection agencies can detect and respond to any suspicious or unauthorized activities. This proactive approach enables agencies to safeguard sensitive data and ensures compliance with regulations.
Incident Response Plan
What’s your collection agency’s incident response plan? What steps will you follow in case there is a data breach? You’ll need to notify the affected parties, work with regulatory bodies, and more.
When It Comes to Data Protection, Technology Is Your Friend
There are several tools you can use to safeguard your collection agency’s data. Here we are listing the most important ones.
Intrusion Detection Systems (IDS): These systems monitor network traffic and can identify malicious activities or unauthorized access to your data. Whenever the system detects a threat, it sends an alert or takes action to stop it.
Firewalls: These are barriers between your internal networks and external ones, monitoring traffic between the two. They’re a good first line fo defense against cyber-attacks.
Data Loss Prevention (DLP): These solutions can detect unauthorized sharing of sensitive data by monitoring your data whether it’s at rest, in motion, or in use.
Multi-factor Authentication: One of the most “annoying” measures, MFA requires your employees to take multiple steps to log into your systems rather than only relying on a password.
API Security: Given that every cloud-based system is heavily dependent on API-based integrations, API security is another topic you will want to dive deeper into when securing sensitive data.
Conclusion: How Skit.ai Protects Consumer Data
At Skit.ai, we are deeply committed to protecting our clients’ sensitive data and ensuring the privacy of their consumers. From encryption for data at rest and in transit to the ISO 27001: 2013 certification, from strict access management to physical security controls, we’ve implemented multiple measures to ensure maximum data protection.
If you would like to learn more about it, reach out to one of our experts using the chat tool below!
How Human Cognition Impacts the Way Users Interact with Voice AI
When developing and configuring a conversational Voice AI solution, it’s imperative to take into account the experience that end-users will have when interacting with the solution. No matter what the use case is, users should be able to utilize the voicebot to reach a satisfactory resolution, while also having a pleasant experience.
CX is one of the elements that drive the work of Conversational User Experience (CUX) Designers, who ask themselves multiple questions when designing a Voice AI solution: Who is the client and what is its brand identity? What target persona will be interacting with the voicebot, and what use cases will the solution help them with?
To maximize the quality of the user experience and the consequent CX, conversation designers take into account cognitive science. The goal is to design intuitive, effective, and engaging interactions; cognitive science can provide insight into how users process information, make decisions, and interact with technology.In order to understand the role of cognitive science in CUX, we must first define the term “cognitive load.” According to the American Psychological Association, cognitive load (or mental load) is the “relative demand imposed by a particular task, in terms of mental resources required.” As humans, we can only hold so much information in our minds at any given time; our minds are limited, and we can’t overload them. That is why minimizing the cognitive load plays an important role in ensuring a positive user experience.
Let’s analyze these aspects one by one:
Natural language processing: CUX designers take into consideration the way users process language, including speech recognition and text-to-speech conversion, as well as the interplay between different elements of speech, such as prosody, pitch, emphasis, and the consequent tonality, which further contributes to perceptual and contextual semantics. NLP is essential for building effective conversational systems. This process also includes researching and implementing algorithms that accurately recognize and respond to human speech.
Memory and recall: The user’s ability to remember and recall information when necessary is essential to conversation design. The cognitive load is directly affected by the complexity and quantity of the information given to the user. Designers consider how the information is presented and stored, and ensure that users can easily and quickly retrieve it.
Attention and distraction: Understanding how people allocate their attention, what contributes to selectivity in attention in a given context, and how easily users can be distracted. Designers must structure the conversation to keep the user’s attention focused on the task at hand, resulting in better engagement and performance.
Emotion and motivation: Emotions play a significant role in shaping human behavior and decision-making. Designers consider how users may feel about the interaction and how to motivate them to engage with the voicebot. Secondary UX research about user demographics and socio-economic and geo-cultural backgrounds can provide valuable insights to improve CX.
Decision-making and problem-solving: Conversations often involve decision-making and problem-solving, and understanding how people process information and make decisions is crucial for effective conversation design. Factors include biases, heuristics, and cognitive load.
How Do You Reduce Cognitive Load in Conversation Design?
What are the best ways for conversation designers to reduce the users’ cognitive load in a conversation with a Voice AI solution, consequently improving the customer experience? Here are some guidelines you can follow:
Simplify prompts and confirmations: Using as few and simple prompts and confirmations as possible helps reduce the need for users to remember and respond to multiple options, ultimately leading to an optimal cognitive load and user experience. This is easier to accomplish with a well-designed conversational Voice AI than with legacy technologies such as IVR systems, in which users are forced to listen to long menus of mostly irrelevant options.
For example, a legacy IVR system will offer a lengthy menu of options, such as: “For your account balance, press 1; for information on your upcoming payment, press 2; to update your personal information, press 3 … To hear this options again, please press #.”
Instead, a Voice AI solution will simply ask: “How can I help you?”
Another example is the prompt for a user’s date of birth. A poorly-designed voicebot will say: “Please enter your date of birth in the following format—two digits for the month, two digits for the day, four digits for the year,” or a similarly lengthy and confusing prompt.
Instead, a well-designed voicebot will ask: “Could you please say or enter your date of birth?”
Use natural language: Use natural language and avoid complex sentence structures to reduce the cognitive effort required to understand the conversation.
See below an example that highlights the difference between a more robotic language choice and an alternative with more natural-sounding language.
Robotic language: Unfortunately, the payment amount that you have given is less than the acceptable minimum amount of $50. Can you please state an amount that is equal to or higher than $50?”
Natural-sounding language: “Sorry, but the minimum we can accept is $50. Can you please tell me how much above that amount you can afford to pay today?”
Provide clear cues: Open-ended questions can prompt a multitude of responses from the users; the voicebot might not understand many of the possible answers. Therefore, using clear cues to indicate when the user should speak, and using audio cues to confirm that the system has understood the user’s response should be adopted as a standard practice.
For example, here’s what the Voice AI solution will say to negotiate a payment plan: “We offer a choice of 2-month, 4-month, and 8-month payment plans. Which payment plan would you like?”
Another way to provide clear cues is the use of an audio signal informing the user that something is happening; in jargon, this is knows as an “earcon” (a brief, characteristic, harmonized and structured sound and its job is to communicate a specific message, event, status to a user or convey a task being performed).
This type of audio signal gives the user a cue that something is happening (e.g. a payment is being processed), instead of just having plain silence, which can lead to confusion. An earcon, for example, could be the sound of someone typing on a keyboard, which signals that the information is being processed.
Use progressive disclosure:Progressive disclosure is a strategy in interaction design to reveal information gradually and start only with the most essential information. Providing information to the user in a step-by-step manner, rather than overwhelming them with too much information at once, leads to increased engagement and enhanced experience.
See the example below:
Voicebot: “To set up a payment plan, can you tell me how much you are comfortable paying each month?”
User: “$60.”
Voiebot: “Thanks! Based on a $60 monthly payment, we can set up a payment plan with a duration of 4 months. Your payment plan will start on the next billing cycle. How does that sound?”
The reiteration of the monthly payment amount also serves as an implicit confirmation.
Contextual design: Using context to guide the conversation reduces the need for the users to provide additional information. For example, just as we do when we talk with a waiter at a restaurant, if the user has already provided their name, the system should use that name in subsequent interactions. As the conversation progresses, the voicebot will have more and more context and will be able to utilize the information it has collected to improve the user experience.
The voicebot shouldn’t just rely on context of the specific conversation taking place, but also on the context of previous interactions with the same user. Acknowledging previous interactions is a good idea.
Test and iterate: Testing the bot’s conversations with users and iterating the flows based on their feedback helps improve the user experience (UX) and reduce the cognitive load. The conversation flow can be optimized based on the different users’ needs. Additionally, different types of debt, different users, different demographics often require slightly different approaches.
There is no doubt that leveraging cognitive science in the design and development of conversational Voice AI solutions can significantly enhance the customer experience (CX).
By understanding how human cognition impacts user interactions, conversation designers can create intuitive and engaging interactions that reduce cognitive load, leading to more positive user experiences.
By applying these insights and best practices, business can rely on voicebots to meet their customers’ needs and optimize the use of their own resources. As the technology continues to advance, the potential for Voice AI continues to grow.
Want to learn how Conversational AI can transform your business? Use the chat tool below to schedule a meeting with one of our experts!
Debt Collection and Positive CX: Is It an Oxymoron?
Discussing customer experience and debt collection in the same sentence might sound like an oxymoron: for most people, the experience of being reminded about an outstanding debt is not particularly thrilling. Yet, the fact that collection calls are not the most welcome calls a customer may receive does not mean their experience should be dry—even negative.
At Skit.ai, we offer an effective and easy-to-deploy conversational voice AI solution for the ARM industry. There are many ways to make the interaction between a user and a voice AI efficient, easy to navigate, and painless.
What is the role of Conversation User Experience (CUX) Design in fostering a positive customer experience (CX) in AI-powered debt collection calls? In this blog post, we’ll share the best practices we’ve adopted to enhance CX in our automated collection calls.
The Role of CUX Design in Improving the Customer Experience
When creating and configuring our conversational voice AI solution for collections, our designers prioritize three components, all of which are essential and will ultimately influence the customer experience when interacting with the voicebot: voice, verbiage, and interaction.
Voice is the audio component of the voicebot: Does it sound male or female? Young or old? What accent does it have? What’s the inflection of the voice? How does it sound—friendly, professional, clear, direct? How fast does it speak? Fast enough to keep the user engaged, but slow enough for the average user to understand? All these questions are taken into consideration when designing the voice AI solution. There are no correct answers, as different use cases and demographics require different characteristics.
Verbiage is the content of the voice AI’s communications during the call with the user. The aim is to make the voice AI solution speak in a natural language so that the interaction can flow smoothly and naturally. Designers take into account grammar, choices of terminology, and other utterances to ensure that the voicebot sounds natural.
Regarding terminology, designers usually seek to balance industry-specific jargon and simple terminology to accommodate users lacking the background and context around the call.
Voice and verbiage, paired together, contribute to creating the digital agent’s “Persona.” For example, that could be a 30-something-year-old female agent, with a confident yet empathetic voice, sounding efficient and eager to help the customer; she could have a midwestern accent and a friendly, yet professional attitude.
The interaction capability of the voice AI solution is the third key element that defines the user experience. This element is the voicebot’s ability to handle an effective back-and-forth with the user. Timing, here, is crucial: when does the AI pause, and for how long? The devil is in the details: missing a comma can change the meaning of a sentence and make it difficult for the user to understand.
How long does the AI wait to reply after the user has spoken?
How does the AI express its prompts? For example, at the beginning of the call, the voicebot will want to verify the user’s identity for authentication purposes; to do this, it will likely suggest the preferred format of the user’s response:
Example: Can you please verify your date of birth? For example, “July 1st, 1985.”
If the AI pauses between the question and the suggested response, the user might respond before the suggestion, leading to mistimings, disfluencies, interruptions, and a potentially failed interaction. To optimize the interaction, a CUX designer will configure the prompt so that the back-and-forth can take effect as smoothly as possible.
The success of the voice AI solution depends on these three pillars. But the customer experience goes well beyond that—let’s explore more aspects in the following sections.
Common CX Concerns: Quality of Speech Recognition and Agent Transfers
One common concern related to customer experience with conversational voice AI is the quality of the ASR, i.e., speech recognition. The fear is that the technology won’t understand the user’s responses and extract the correct “intents” and thus fail to deliver a smooth, natural-sounding interaction. The technology behind speech recognition and natural language understanding has dramatically evolved over the last few years. While this used to be a major problem a few years ago, today it’s less of a concern.
Of course, poor connection or background noise can still hinder the tech’s ability to understand what the user is saying. That’s where a repair strategy comes into play to take the conversation back on track and prevent misunderstandings. Whenever the AI fails to hear the user’s response, it can politely ask them to repeat or rephrase it. Similarly, when the user is uncertain about how to respond, it can offer to repeat it more clearly or rephrase it using different words.
Another common concern relates to agent transfers. Users often fear that the voice AI solution won’t let them easily transfer the call to a live agent if requested. That’s not the case with Skit.ai’s solution. Whenever the customer’s needs are too complex for the AI to handle, and whenever the customer requests it, the solution will always transfer the call to a live agent from the collection agency.
The Role of Personalization as an Effective CX Tool
To achieve a seamless customer experience, a company must know its customers. That is why, in addition to outlining the voice AI’s persona, we also consider the user persona, i.e., the user demographics. Incorporating personalization into the conversation with the voice AI solution helps make it more engaging and fosters trust. However, it’s important to maintain a balance—while personalization is great, you also don’t want to overdo it in order to protect the user’s privacy. This was recently highlighted in data showing that the majority of consumers expect personalization, as long as the data is handled responsibly.
One small touch is incorporating the user’s first name throughout the conversation. For example, after the user authentication is completed, the voicebot can say: “Thank you, Sarah,” to confirm that it’s verified the user’s identity.
Showing that the voice AI solution is aware of the context of the conversation can also improve CX. For example, during an inbound call, the voicebot may say: “I see that you have an outstanding balance of 241 dollars and 50 cents. Is this what you are calling about?”
After the user has made a payment, the voicebot can express enthusiasm like this: “Good news, Sarah! I received your payment of 241 dollars and 50 cents.”
Regional languages and dialects also ensure that the solution is tailored to specific markets. For example, Skit.ai’s voice AI solution speaks over half a dozen languages along with understanding several regional accents.
Incorporating Empathy in Automated Collection Calls
When it comes to sensitive use cases such as debt collection and medical-related calls, empathy is an important component of the voice AI solution’s capabilities. The choice of words, tone, and inflection used by the voicebot can greatly affect the voicebot’s ability to convey empathy, particularly when a user expresses their inability to pay off their debt.
For example, the user may say: “I just lost my job, I can’t deal with this right now.”
How should the voice AI solution respond? The role of empathy in AI is a complex matter: If the voicebot says, “I’m sorry to hear that,” it might irritate the user, given that a computer cannot truly grasp the emotions of someone who has lost their job. However, a common phrase like “I completely understand the situation” is a conventional expression to indicate that the AI solution has acknowledged the user’s challenge.
The voice AI solution is designed to offer options to reach a satisfactory resolution. If the user can’t pay off the debt right away, the solution can offer a few alternatives, such as a payment plan or the ability to connect again in the future.
When designing the voicebot to express empathy, we want to avoid the so-called “uncanny valley” effect. If the voicebot switches abruptly from an overly empathetic statement to a neutral tone, it can cause the user to experience unease and irritation. Therefore, there needs to be consistency in the voicebot’s naturalness and tone, avoiding excessive variation and unexpected changes in its behavior.
And Finally… Regular Quality Checks
While old systems were static and rigid, new-generation conversational voice AI solutions like Skit.ai are dynamic and adaptive. The solution is built to improve over time. Additionally, after the solution is implemented, CUX Designers regularly perform quality checks and listen to calls with customers to ensure that the voice AI functions correctly. This way, they’re able to regularly train the solution to add new capabilities, understand more user utterances and intents, and offer the most appropriate responses.
Are you curious to watch Skit.ai’s Conversational AI solution for collection calls in action? Contact us using the chat tool below and schedule an appointment with one of our collection experts!
IVR stands for “Interactive Voice Response,” and it’s a legacy technology that enables companies to automate both inbound and outbound calls by using a pre-recorded voice that interacts with consumers and guides them through a pre-set menu, which can be navigated by inputting DTMF (dual-tone multi-frequency) from the phone keyboard.
Virtually everyone has interacted with an IVR system at some point. Whether you’ve called a business, a bank, a pharmacy, a doctor’s office, or a phone service provider, you are certainly familiar with prompts like: “For hours of operations, press 1.”
Call automation for call centers and businesses is not a new concept. IVR became popular in the 1980s when it emerged as an essential customer service technology. Debt collection agencies have been using IVR for over a decade, for both outbound calls (such as payment reminders) and inbound calls (such as consumer inquiries).
However, the fact that IVR is so common does not mean that it’s an optimal solution. In this blog post, we’ll go over the limitations of IVR and explain why adopting a conversational Voice AI solution is a far better option for collection agencies.
Why IVR Is Overwhelmingly Unpopular
IVR reduces wait time for consumers, but it does not eliminate it, as it forces users to listen to lengthy menus that are for the most part irrelevant. At least 61% of consumers think that IVR systems make for a poor customer experience (CX).
A survey conducted by Vonage with Opinion Matters in 2019 revealed that having to listen to seemingly endless, irrelevant menu options is the primary factor that contributes to the consumers’ negative experience. Additionally, the respondents complained that IVR menus are usually too long, that the reason for their call is sometimes not even listed, and the system prevents them from speaking directly to a live customer representative.
Building the right IVR for your company can be tricky. When the system is not designed well, users will get frustrated and abandon the call. IVR is notoriously difficult to navigate, especially when a business offers different services or targets various sets of consumers.
In one sentence: consumers don’t like IVR. So what’s the alternative?
Voice AI Is the Best Alternative to IVR
Conversational Voice AI is the cutting-edge technology behind what is commonly referred to as a “voicebot.” It enables companies to automate both inbound and outbound calls with customers without the involvement of a human being. In recent years, SaaS platforms offering Voice AI solutions have become more affordable and easier to deploy.
In the ARM industry, Voice AI can transform the operations of collection agencies for the better; these solutions are infinitely scalable and can handle the vast majority of calls with consumers. The AI can handle the most repetitive and mundane calls, empowering live agents to focus on the most important and revenue-generating calls.
Skit.ai’s solution can handle intelligent, personalized, and effective conversations with consumers, eliminating wait times and significantly cutting costs for the company adopting it. The AI is aware of the context and will tailor the service it offers based on the specific needs of the user. The technology not only understands what the user says but also the semantics of the conversation.
Voice AI for Outbound Collection Calls
Collectors are usually expected to go through thousands of files per month; a large number of those files remain untouched since it’s impossible for a human collector to contact and speak with so many consumers. This process leads to substantial losses in potential revenue for the agency.
When fed with large quantities of files, a Voice AI platform can initiate and handle an extraordinarily high number of calls. These are some of the solution’s capabilities:
The solution can easily transfer the more complex calls to a live agent when it cannot reach a satisfactory resolution. When agents see that a call is being transferred from the Voice AI, they know the customer is usually inclined to make a payment or reach a settlement.
Why You Should Not Use IVR for Outbound Collection Calls
Using IVR for debt collection calls is limiting and is unlikely to lead to a successful debt recovery on a consistent basis. The system can’t capture meaningful dispositions and is capable of handling a limited number of actions. Let’s say the consumer refuses to pay or disputes the debt—can your IVR capture the reason? Let’s say the consumer is willing to pay but can only pay off part of the debt at this time; can your IVR handle a negotiation? If the consumer is busy right now, is your IVR able to capture call-back dates and times? Probably not.
Voice AI for Inbound Queries
When a customer calls the collection agency, rather than having to deal with an annoying IVR menu, they get to interact with the Voice AI solution.
The AI picks up the call right away, eliminating the wait time of a regular call; additionally, the user does not have to patiently listen to a long list of options. The AI typically authenticates the caller’s identity and, if relevant, informs them of their due balance. Here the customer gets to have an intelligent, effective, multi-turn conversation with the Voice AI solution.
In revenue-generating inbound calls, the Voice AI can easily help the customer make a payment. In non-revenue-generating inbound calls, the solution will answer the customer’s questions based on the information it has on file, and will transfer the call to an agent when needed.
Why You Should Not Use IVR for Inbound Queries
Whenever a consumer is interested in making a payment and resolving their debt, they might be turned off by the poor customer experience offered by the IVR. In non-revenue generating inbound calls, the IVR system is often incapable of resolving the query, and therefore will likely transfer the call to a live agent.
U.S. debt collection agencies report that their agents spend about 20% of their time answering inbound calls! Many of these calls are not revenue-generating, so they consume time and resources that could be easily allocated to collection calls.
The Benefits of Adopting Voice AI for Debt Collection Agencies
Here are some of the benefits reported by collections agencies that have adopted Skit.ai’s Voice AI platform:
Interested in learning more about how Conversational AI can help you streamline your collection strategy and reach your full potential? Schedule a call with one of our experts using the chat tool below!
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.”
There have been a total of 13.7 million car sales in the U.S. in 2022, according to an IBISWorld estimate. Car sales have been declining since the beginning of the COVID-19 pandemic due to many factors, including the growing prevalence of remote work, supply chain issues, and a looming recession.
As a consequence, interest rates have been rising significantly, hitting over 6.0% and negatively affecting the number of car sales. With higher prices, bigger loans, and higher interest rates, comes an increase in delinquencies. It has become an issue for many auto finance companies to keep up with the high number of delinquent borrowers.
In this article, we’ll discuss how Voice AI (the technology behind a voicebot) can transform auto loan collections in different ways.
What Is Voice AI?
Also referred to as a voicebot, Voice AI is a technology that enables companies to automate calls with customers from start to finish without requiring the involvement of a human agent.
AI-powered Digital Voice Agents are capable of handling intelligent conversations with users. The technology understands what the user needs and helps them effectively resolve the issue in just a few minutes. Voice AI should not be confused with Outbound IVR (Interactive Voice Response), a dated technology that consumers tend to dislike.
Auto finance companies that perform collection calls are now turning to Voice AI to automate many of the repetitive, tedious calls they used to perform manually and allow their live agents to focus on more complex and revenue-generating tasks. The Digital Voice Agent engages with the borrower, verifies their identity, and collects the payment on-call, covering up to 70% of the company’s outbound call volume.
To better understand what Voice AI is, think about Siri or Alexa, but for collections. However, there is one difference. While voice assistants like Alexa can only handle one or two conversation turns, a solution like Skit.ai’s Digital Voice Agent is designed to address issues that often require several conversation turns. Just like humans need to gather the context before solving a problem, a Digital Voice Agent might ask multiple questions before proposing a resolution.
What Are the Most Common Uses of Voice AI in Auto Finance Collections?
Voice AI is just one of the many artificial intelligence trends that are taking the auto industry by storm. Its ability to automate collection calls and other common types of outbound calls to borrowers is particularly appealing to auto finance leaders looking for ways to cut contact center costs and maximize profits.
Let’s dive deeper into the four most common uses of Voice AI (the technology behind Skit.ai’s Digital Voice Agent) in auto finance collections:
Welcome calls: Lenders and auto finance companies typically deliver an initial “welcome call” to borrowers to let them know that they are servicing the loan or in charge of collecting payments. While these calls are important, they are not revenue-generating and utilize the precious time of the company’s live agents.
Skit.ai’s voicebot solution can easily initiate an outbound call to borrowers to deliver the message and then answer some of the customers’ most common questions.
Payment reminders: Auto finance agents typically spend most of their time calling borrowers to remind them of payments that are due soon or payments that are already overdue. Reaching borrowers is not always a straightforward process! Agents have to establish right-party contact, explain who they are, and remind the borrower about the payment. When the volume of loans increases, it can be challenging for managers to scale the contact center to fit the need of the moment.
Skit.ai’s Voice AI solution can offload up to 70% of the calls from live agents, handling payment reminders automatically. Skit.ai’s clients have even reported that some borrowers prefer to interact with a voicebot rather than a human agent, as it can be embarrassing for them to discuss pending payments and the risk of going delinquent. The voicebot can easily establish right-party contact, remind the borrowers of the due balance, and offer different ways to pay it off.
On-call collections: The end goal for any collector is to recover the payment from the borrower; if the borrower is willing to make the payment on-call, even better. While this part of the process is directly revenue-generating, it still takes time and resources to complete.
Skit.ai’s Digital Voice Agent has the capability to collect the payment during the call, making the process significantly cheaper for the company servicing the loan. The collection is processed through a payment gateway of the company’s choice.
Autopay or ACH sign-up: Many auto finance companies servicing loans initiate outbound calls to borrowers to offer them to sign up for autopay. With autopay or ACH, borrowers can automate payments from their credit card or bank account so that they can be processed on a regular basis.
Skit.ai’s Digital Voice Agent can easily call borrowers, explain how autopay works, and offer them to sign up on call. This is an ideal scenario for auto finance companies, as it ensures a regular cash flow.
How Do Auto Finance Collections Work?
Now that we know what Voice AI is and the main use cases in auto finance, let’s go over the main steps of a standard collection call handled by one of Skit.ai’s Digital Voice Agents.
The voicebot follows these steps:
Triggers the outbound call based on pre-determined criteria
Establishes contact with the borrower (RPC) and reminds them about the payment
Collects propensity data and reasons for potential non-payment
If the customer is interested in making the payment right away, the Digital Voice Agent guides them through the process via a payment gateway
Persuades the customer to pay at the earliest, or offers alternate payment plans
Feeds data to the CMS (collection management software) and provides analytics for further action
Performs auto-callback on request, auto-retries, hot transfer to agent
Are you interested in learning more about how Skit.ai’s Augmented Voice Intelligence platform works and how your auto finance company can adopt it? Schedule a call with one of our experts using the chat tool below!
Auto finance companies dealing with collections face a pivotal moment of seemingly unprecedented activity.
Here’s what’s happening right now: car prices have hit a record high, interest rates are skyrocketing, and — as a consequence — the auto finance industry is facing a high number of delinquencies. As they find themselves with very high numbers of loans, lenders and collectors have to drastically scale up the number of outbound calls to borrowers.
While challenging times are not always fun, they also allow us to think outside the box and come up with innovative solutions. In this article, we’ll go over some of the major challenges related to auto finance collections and explain how Voice AI and call automation can solve each of these problems.
A growing number of auto finance companies are starting to look to Voice AI (the use of automated voicebots) as the go-to solution to handle both outbound and inbound calls with customers and borrowers. In particular, voicebots are used for collection calls and payment reminders.
Voice AI-powered Digital Voice Agents can handle human-like conversations with users, eliminating wait times and enabling a much larger number of calls to be handled at the same time. A Voice AI technology like Skit.ai’s Augmented Voice Intelligence platform allows auto finance companies to handle collection campaigns at a fraction of the cost.
Challenge 1: Scalability
Auto loan volume varies significantly depending on the year and the season. Anyone who has been in the industry for a while can tell you that they’ve seen very busy seasons as well as quieter ones. Because of the unpredictability of these changes, it can be difficult for an auto finance company to easily adapt and scale either up or down. When facing a particularly busy period, auto finance companies need the ability to quickly scale up to handle larger volumes of loans and customers.
How Voice AI can help you solve this challenge: Voice AI enables auto finance companies to scale up and down with just a few clicks, deploying as many Digital Voice Agents as they need depending on the year and season. As soon as loan volume goes down, the company can simply scale down its use of the Voice AI solution.
Challenge 2: Cost
Collections can be an expensive process. Agents or collectors typically have very large portfolios, with many accounts to reach out to; because the process still tends to be manual for the most part, it takes time. Additionally, if your collectors take a commission, that can also reduce profits.
How Voice AI can help you solve this challenge: By automating the collection process, Voice AI can significantly augment the work of your live agents on the floor, contact many customers simultaneously, and massively reduce costs. Additionally, an AI-powered Digital Voice Agent does not take commissions!
Challenge 3: Hiring and Training
A poorly-trained team of agents and collectors can be a recipe for disaster. As new loans pile up and many become delinquent, it can be tempting to throw new employees into the midst of the action; but if the agents are not qualified and they are not familiar with the existing laws and regulations, you might find yourself in trouble in no time.
How Voice AI can help you solve this challenge: A Digital Voice Agent requires minimal training at the very beginning of the deployment process. After that, you can easily tweak its conversational flows and capabilities with just a few simple changes to the Voice AI platform, either on your own or with the help of your provider.
Challenge 4: Talent Shortage
Since the pandemic and the Great Resignation, many industries, including the auto finance and debt collection industries, have been faced with a shortage of talent. The lack of human capital poses serious challenges to auto finance companies, whose teams and management need to deal with overwhelming workloads. Attracting talent can be a costly endeavor.
How Voice AI can help you solve this challenge: Automation is the answer to the human capital shortage. Voice AI can fill the gaps created by the lack of talent and help the existing team members handle the most repetitive and mundane calls. The adoption of a debt collection software like Skit.ai’s platform can solve this problem in a very short time.
Challenge 5: Agent Attrition
While it’s hard to define the exact attrition rate in the collections space, from talking to many companies operating in both the collections and the auto finance industries, we know that attrition is a real challenge for them. In a 2016 Consumer Financial Protection Bureau survey, large debt collection agencies reported an average turnover rate of 75% to 100%.
Agents and collectors are often dissatisfied, frustrated, and understimulated, so they hop on to the next job opportunity as soon as they find one, whether it’s because the pay is better or because they think the work will be more rewarding.
Every time your company loses one team member, you’ll have to undergo the process of recruiting, hiring, and training a substitute, which can be costly and time-consuming.
How Voice AI can help you solve this challenge: A Voice AI-powered agent never gets tired of handling repetitive and mundane tasks. With the help of Voice AI, you can also focus on retaining your existing talent, as you can ensure every team member has the opportunity to focus on more rewarding and complex tasks.
Challenge 6: Compliance
The collections industry is affected by so many laws and regulations that, if you haven’t been in this space for a while, it can be overwhelming to understand what you can and cannot do. How often can you call borrowers? Are there any times of the day you can’t call them? What do you do if a borrower asks not to be contacted again? How do you handle the privacy of your customers? How should you safely process payments?
These questions are just the tip of the iceberg when it comes to compliance! Think about the TCPA, the FDCPA, the SCRA, PCI standards, and so many others. Additionally, some of these regulations vary depending on the state where the borrower resides.
An auto finance company pursuing collections must be well-versed in these rules and should stay up to date, as lawsuits abound and regulations change relatively often. Better safe than sorry!
How Voice AI can help you solve this challenge: Digital Voice Agents, unlike live agents, don’t go off-script, misspeak, or get confused. When they are trained to follow a set of regulations, they just stick to it. With the help of Voice AI, you can let the solution do the work while you handle other tasks.
Challenge 7: Recordkeeping
For an auto finance company, few things can be more disastrous than poor recordkeeping! Especially when it comes to collection efforts, notes, documentation, and records are crucial. That’s why total reliance on manual recordkeeping is at best risky and at worst harmful. Collectors should keep track of each interaction with their borrowers so that they can follow up and make progress with each new conversation.
Additionally, other team members — such as fellow collectors and managers — should be able to easily access the notes and track the progress made with each account. Automated notetaking is one possible solution to tackle this challenge.
How Voice AI can help you solve this challenge: A Voice AI platform automatically keeps track of all customer interactions, taking notes of every conversation and capturing payment disposition and propensity to pay. With Voice AI, you get to automate conversations with borrowers, and you can be fully aware of the background and context of each account. Whenever a live agent wants to take over, they can easily do so by looking at the record of the relationship between the auto finance company and the borrower.
Are you curious to learn more about how Skit.ai can transform your auto finance operations, customer interactions, and collection efforts? Schedule a free demo with one of our experts using the chat tool below.
2022 has been a pretty eventful year for Skit.ai! In this article, we will re-live some of our company’s most notable moments in the U.S. in 2022, including media mentions, award recognitions, and more. This was an exceptional year for our company and the Voice AI industry at large. Get a cup of coffee or tea ready, and join us as we go down memory lane!
In the announcement, Skit.ai’s CEO Sourabh Gupta said: “We’re continually listening to our customers, conducting market research, and making enhancements to our artificial intelligence system to deliver a best-in-class solution that helps contact center agents offer modernized and reliable customer service, leaving a lasting impression and positive satisfaction rate for their company. We look forward to expanding our U.S. customer base and building new relationships to help elevate the customer experience, optimize costs, maximize operational efficiency and increase company revenue.”
Skit.ai Mentioned in the Washington Post
In the summer of 2022, Christopher Elliott, a reporter at the Washington Post, quoted Sourabh Gupta in an article about customer service in the travel industry. The piece explained that Skit.ai develops an artificial intelligence-driven voice technology.
Gupta was quoted saying, “Travelers should look for companies that offer round-the-clock assistance and a way to reach key information, even when human support agents might not be available.” The article continued: “You can tell your travel company has this by looking for a ‘contact us’ feature on its site that offers 24/7 phone, chat and email support.”
Skit.ai’s Big Win at the CCW Excellence Awards
In July 2022, Skit.ai was given the “Disruptive Technology of the Year” award at the CCW Excellence Awards Gala held in Las Vegas. The event is part of Customer Center Week and recognizes “the most innovative companies and top-performing executives for their extraordinary contributions to the customer contact profession.”
Upon accepting the award, Gupta said: “We are thrilled to be recognized by CCW. This award underscores the reason for our existence – to improve contact center operations, so both the agents and customers have a more seamless experience. Being recognized for the most disruptive technology solution in contact center operations is a reminder of why we all come to work each day. We’re excited for what the future has in store for our company and the industry at large.”
As part of the Trust Index Employee Survey conducted by GPTW, employees ranked the company favorably on parameters such as Credibility, Respect, Fairness, Pride, and Camaraderie. The certification affirmed the company’s core cultural values of striving for excellence, being a learning organization, building a client-first mindset, exercising constructive disagreement, and fostering commitment at work.
Skit.ai Named Among Best Business Technology Solutions at the International Business Awards
This award recognized Skit.ai’s Augmented Voice Intelligence Platform as an innovative technology solution that fuels effortless contact center conversations to manage customers’ needs more efficiently and painlessly.
The Stevie Awards are the world’s premier business awards that honor and generate public recognition of the achievements and positive contributions of organizations and working professionals worldwide.
Skit.ai’s Other Notable Media Mentions in 2022
CMSWire quoted Skit.ai’s CEO Sourabh Gupta in an article about the ways the COVID-19 pandemic has affected the Voice of the Customer. Gupta said: “Especially in customer service roles such as restaurants and stores — employees have reported that customers are more demanding than ever before. With many employees in this industry switching to better-paying industries, this only increases customer frustration as these establishments try to find help.”
In another article, CMSWire asked Gupta to share his insights on how AI is shaping the future of customer interactions. “With Voice AI, brands can cut down on customer wait times, shorten the time they spend on the phone, and effectively answer their questions faster,” said Gupta.
TechBullion published an extensive interview with Gupta, who shared his vision for the company and the conversational AI industry at large. “Our vision in creating the company is to elevate customer experiences and lay the groundwork for the future of voice interactions,” Gupta said.
Also VentureBeat featured Skit.ai in an article about the ways AI predicts hurricanes and answers calls for help in their aftermath. The reporter noted that, “with emergency hotlines, hospitals and utility call centers being inundated with calls, speaking with a voicebot during a time fraught with anxiety and fear can help.”
“In a sensitive or dangerous situation, Voice AI can be used to provide customers with crucial information in real-time, answer questions and redirect the more complex calls to a human agent,” Gupta told VentureBeat.
Last but not least, Authority Magazine published an extensive interview with Gupta conducted by Tyler Gallagher. In the interview, Skit.ai’s CEO discussed his personal journey, his vision for the company, and the AI industry’s current challenges.
We are looking forward to an even more exciting and productive year in 2023!
