Voice AI is becoming mainstream in the ARM industry, and the days of chasing after customers for unrecovered debts in the most haphazard, manual fashion are nearly over. Additionally, thanks to the rising popularity of self-service channels and the ecosystem-led push involving regulatory changes like the Reg F that rewrite the expectations for debt recovery in the U.S. beyond simple automation.
Voice AI conveniently fits the bill for debt collection agencies by fixing the systemized inefficiencies with automation and analytics-driven voice communication outreach. In this article, we will explore why human-like voice interactions handled by AI-powered Digital Voice Agents help debt collection companies drive effective consumer interactions at better collection cost, performance, and efficiency ratio.
7 Ways Voice AI Helps Elevate Debt Collectors’ Productivity
At Skit.ai, we call it Augmented Voice Intelligence — the idea that Voice AI can augment, rather than substitute, the work of live agents and collectors. Let’s dive into the benefits of this strategy:
Human-like Conversations: Voice AI is purpose-built and modeled on human conversations. Digital Voice Agents can hold thousands of outbound customer outreach calls simultaneously, without the involvement of human collectors, helping collection agencies carry out human-like interactions at lesser cost and effort from their human resources.
Seamless Integrations: Voice AI’s integration features feed data from collection calls, such as right-party contact, call-back requests, no response, and more, into the collection management system to provide actionable insights for human collectors to be more proactive.
Higher Portfolio Coverage: Collection agencies can leverage Digital Voice Agents to scale collection outreach calls for different consumer accounts and across diverse portfolios with unique requests for payment alternatives, call-back options, or preferred time of contact.
Versatile and Accurate:Intelligent voice bots can be tailored according to the use case, offer profound insights for analytics on future actions, independently schedule automated triggers, auto call-back on request, and even make intelligent call transfers to human agents/live collectors for complex issues.
Better Compliance and Privacy: Voice AI’s algorithms can be trained to follow regulatory protocols on reaching customers, communication time, frequency or calls, and honoring their requests for discontinuing communication using APIs. It can be challenging to adhere to all the norms when done manually. Also, Voice AI’s strong encryption and consumers’ or cardholders’ data protection features comply with regulatory standards like HIPAA, PCI, FCRA, and more.
Lower Litigation:Voice AI lowers litigation risks compared to human agents, who are more likely to coerce consumers to pay with the hope of meeting targets and receiving higher commissions. Additionally, consumers are generally passive toward Voice AI and pin fewer expectations on the technology to understand their emotions or personal grief, reducing the odds of agencies ending up with lawsuits.
Better Insights and Analysis: Debt collection agencies can draw on the insights gathered by Digital Voice Agents to learn about consumers’ or callers’ experiences and conversations to design or augment debt collection processes for better collection campaigns, collectors’ experiences, and higher recovery rates.
How AI-powered Digital Collectors Can Outperform Live Collectors
While Voice AI embodies the promise of automation with a human touch, collection agencies don’t rely on anecdotal evidence. They look for value-creation and tenacity to transform traditional loan recovery practices with the technologies to a level that human resources alone cannot match. Skit.ai firmly believes in realizing the potential of voice communication in debt recovery by augmenting human support with AI for intelligent human-machine collaboration.
Here are the key differentiating features of Voice AI that match collection requirements and make processes more efficient in responding to various outbound debt collection use cases.
Collection Support Scalability: Voice AI can automate up to 70% of calls, helping curb hiring, recruitment, and training-related requirements in collection agencies. Additionally, Digital Voice Agents help leverage unlimited scalability by simultaneously handling multiple collection calls, which would otherwise be very time consuming and expensive when done manually.
24/7 Support: Digital Collectors can always be at the beck and call of consumers to offer 24/7 support. Delivering 24/7 support with human resources would be extremely costly and unrealistic.
Lower AHT: Voice AI guarantees better performance and can handle multi-turn conversations with prompt query resolution. It reduces average call handling time (AHT) by 40% and augments human agent teams’ efforts by transferring only complex queries and equipping them with real-time analytics and insights.
Higher Debt Collection and Recovery Rate: Skit.ai’sDigital Collectors have repeatedly demonstrated performance at par with average debt collectors while operating at less than 1/5th the cost of a human agent.
Better Account Classification: Unlike manual debt collection efforts, Voice AI’s ML classification models algorithms are trained to segregate consumers as per bankruptcy details, creditworthiness, outstanding loan amounts, blocked accounts, and do-not-call lists, to help collectors or accounts receivable managers respond appropriately.
Higher Accountability and Compliance: Digital Voice Agents are trained to comply with strict practices in debt collections (7/7/7 rule, TCPA, Mini-Miranda, etc.) and refrain from the usage of unsavory language or behavior that can later result in lawsuits to the agency, which would be challenging to regulate in manual collection use cases. Besides the analytics-driven insights on consumer responses and history, Digital Voice Agents guarantee higher accountability.
Complete Campaign Control: Digital Collectors can be turned on or off as per use case to match the call volume requirement or type of consumers’ requests and accounts, unlike calls by live collectors with efficiency issues and too much time, resources, and training.
Consistent Call Quality: Voice AI delivers consistent experiences at any scale and volume. It is humanly impossible to ensure the call experience remains the same and guarantees similar outcomes for all debtors’ conversations from manual collection campaigns.
The Bottom Line: Voice AI is the Key to Supercharge Debt Collections
It is time to embrace the reality that neither automation nor pure human intelligence can help debt collection agencies to master complex collection campaigns. Skit.ai’s Augmented Voice Intelligence platforms like Skit.ai enable the collaboration between humans and AI-powered machines to respond to the mounting operational stresses in debt collection agencies. These solutions empower live collectors to perform consistently throughout the debt collection process at a better cost, productivity, and recovery rate.
To learn more about how Voice AI can help reimagine debt collection efforts with call automation, schedule a call with one of our experts or use the chat tool below.
For debt collection agencies, debt recovery is a labor-intensive effort that typically relies more on human effort than capital investments. Even with the adoption of newer digital communication tools that promise to scale manual efforts, the ARM industry invariably struggles with one major issue — human resource turnover.
The high attrition that characterizes the collections space makes third-party debt collection agencies vulnerable to several challenges, like loss of domain expertise, risk of non-compliance, lawsuits, and increased cost of hiring and training new talent. In the United States, with nearly one in four citizens having at least one debt in collections, recovery has become an increasingly costly endeavor.
Most Common Reasons for Collection Agent Attrition in the Debt Collection Industry
Here are some of the most common challenges that make it so difficult for agencies to retain collectors:
Too Many Accounts, Too Much Work: Given the growing debt delinquency in the U.S., one can only imagine the amount of verification and debt-related communication work that can drive collectors to overwork.
Collectors’ Commission is Dependent on Recovery: Third-party debt collection agencies are involved when credit card issuers or creditors’ collection representatives cannot recover overdue balances. Collection agencies face thinning profit margins, and human agents’ commissions for debt recovery further burn holes in their pockets. There is no set rule or guarantee on the time the human agents need to recover outstanding loans successfully.
The Great Resignation: While all contact centers face high attrition rates, many people have been rethinking their careers and seeking opportunities in new fields over the last two years. This also applies to the ARM industry, where collection agents face acute stress from chasing after customers over the phone while adhering to a wide array of regulations, making attrition an even bigger challenge.
Empty Promises to Pay: It is common to find consumers dodging debt-related interactions. When confronted directly, they are likely to make promises to pay that may only sometimes be honored, which is another detractor for collectors to stick to their roles.
Debt Shame: Debt collection calls are direct and can sometimes make the debtors uncomfortable delving into the details of their unpaid loans. According to a study by Webio, people can be much more honest when communicating via text messages than in voice interactions for difficult scenarios. In the case of debt collections, textual conversations can reduce stress for both debtor and collector.
Efforts Often Don’t Justify Conversion Rates: When it comes to debt, the devil is in the details. To invest too much attention and time in each customer who needs a detailed overview of their loans and debts is unrealistic. It is extremely costly and leads to operational overkill, another reason for collectors’ resignation.
Debt Collection is Not for Everyone: Employee turnover in any field results from the nature of the job/employer and the employee’s capabilities. Working conditions, perks, quality of work, and benefits will fix the collector’s morale. But employees’ capabilities for the job determine how much they are willing to stick to it.
Rapid Changes in Regulatory Framework: Many regulatory agencies like FTC and rules like Fair Debt Collection Practices Act dictate how collection agencies can approach consumers without violating consumer protection laws. It requires constant staff training and procedural approaches like obtaining debt verification requests, debt validation, forbearance, and foreclosures that rely on unique expertise. When agencies adopt a manual route or use restrictive debtor communication methods, errors and inaccuracies are expected.
The Rising Role of Voice AI in the Debt Collections Industry
These challenges highlight the urgency for digital transformation in collection agencies; in particular, agencies are looking at automation as the primary solution to their attrition crisis.
In our previous articles, we discussed the unique capabilities of Voice AI technology in reducing contact center agent labor costs via call automation. Concurrently, Gartner’s estimates from their survey also suggest that labor expenses represent 95% of contact center costs, and adopting Conversational AI helps cut expenses by $80 billion. The customer-facing side of ARM, particularly the debt collection agencies, can capitalize on this trend to reduce staff shortages, curb labor expenses and make human resources more efficient and effective.
Voice AI’s value-adds are in areas that impact collectors’ productivity and bandwidth which further determine talent retention in this space. Here’s the rundown of its merits that help address agent attrition challenge in the debt collections industry:
End-to-end Call Automation: Voice AI helps automate 70% of calls (inbound and outbound), allowing prompt query resolution. Also, agencies can leverage automation to identify consumers, policy numbers, and other debt-related information. This reduces the effort and time it would take to call and follow up with each debtor manually.
Reduce High Cost of Collection by 1/5th: Digital Voice Agents that plug into contact centers and take over calls by holding human-like conversations can execute calls at less than 1/5th of the actual cost of manual calls. Collection agencies can lower operation costs with intelligent voice agents in lieu of collectors by concurrently calling over thousands of defaulters.
High Scalability: Agencies can scale their debt collection efforts and consumer outreach by leveraging call automation and Digital Voice Agents that can handle and answer tier-1 caller queries by automating up to 70% of calls, reducing dependency on human agents.
Higher Portfolio Coverage Intensity: Collectors can cover many more debt files when they leverage Voice AI’s ability to handle multiple calls simultaneously. With minimal effort, cost and time, agencies expand their scale of reach of debt collection practices with minimal human intervention.
Solve Diverse Use Cases: The recovery process in the collection agencies involves rigorous reviews, checking outstanding balances, sending demand and acknowledgment letters, and arranging for telephone contact. It is humanly impossible to keep track of all details, numbers, and sensitive information about different types of debt and cases at their fingertips. Digital Voice Agents can be optimized to address various debt-related queries and use cases without time, cost, and human effort constraints, reducing work stress and dissatisfaction for debt collectors.
Enhance Human Agent Productivity: Debt collectors can experience higher and faster conversion levels by leveraging Voice AI’s analytics and caller data insights. The pre-call verification, call automation (inbound and outbound), and routing features enable real-time agent augmentation, boosting productivity and performance. Also, the Digital Voice Agents are capable of intelligent call transfers to human agents only for complex cases, allowing the human workforce to focus on efforts that help retrieve debts faster.
Voice AI Calls are Free of Human Biases: Holding debt recovery conversations is a sticky collection practice that most consumers tend to avoid out of pressure, discomfort, shame, and fear of judgment. Voice AI’s call automation capability eliminates direct voice interaction between defaulters and collection agents, making collection calls free of human biases. Also, Digital Voice Agents can hold persuasive, contextually accurate, and proactive conversations and keep interactions direct and objective. This way, collection agents can experience higher work quality without job stress, dissatisfaction, and the chances of misdemeanors while talking to consumers.
Collection agencies rely entirely on outstanding loan payments to survive. Voice AI helps collection agencies strike a balance between meeting their recovery targets and making debt collection efforts more intuitive in a way that doesn’t come at the cost of operational burnouts and resignations. Voice AI eliminates bottlenecks in debt recovery and improves the overall customer experience.
To learn more about how Voice AI can help you solve attrition challenges, schedule a call with one of our experts or use the chat tool below.
What Are Connect Rate and Right-Party Contact (RPC)?
Debt collection agencies invest time and resources in getting in touch with consumers. In theory, all it takes for a collector to speak with a consumer is to hit the call button, but in reality, it’s not that simple; oftentimes, the number is wrong, the consumer does not answer the phone, or the wrong person picks up the phone.
Connect rate and right-party contact rate are two metrics that significantly affect the outbound operations of a contact center.
Connect rate measures the percentage of successful attempts a collector makes in which someone picks up the phone. Right-party contact rate is the percentage of calls in which an agent is able to connect with the target consumer, which could be either the debtor or a relative who has been given permission to handle the debt. Right-party contact (RPC) is the most accurate measure of the effectiveness of an agency’s outbound calling efforts.
☎️ Factors that affect connect and right-party contact rates
❌ Wrong number
⛔️ Busy line
💬 No answer
🙅🏽♀️ Wrong party answers the phone
Why Right-Party Contact Can Be a Challenge for Collection Agencies
Collectors know it very well: reaching consumers can be tricky.
Given the limitations imposed by the TCPA and the FDCPA, collectors can’t call debtors at any given time of the day. While timing is everything, even a well-staffed agency can only contact consumers so many times in order to reach them, as the number of available collectors is limited and you don’t want them to spend too much time trying to reach the same numbers too often.
Right-party contact can be a serious challenge for collection agencies. Collectors (and their managers) want to spend as much time as possible actually speaking to consumers and collecting payments — and as little time as possible trying to reach people on the phone. Calls not resulting in RPC don’t lead to a collection (nor a commission for the collector), and result in an overall waste of resources.
This is where automation and artificial intelligence come into play.
How Voice AI Solves the RPC Issue for ARM Companies
With rising costs, high attrition rates, and a looming recession, ARM companies are looking at digital transformation and automation as valid solutions to their operational challenges.
Contact centers in all industries have been relying on automatic dialing systems (or auto dialer software) for decades. These systems make the dialing process faster and easier, boosting agent productivity; in addition to queueing calls and dialing the target number automatically, they also screen out inactive numbers, busy lines, and answering machines, drastically improving the contact center’s connect rate.
But what about right-party contact?
Once the collector reaches a person on the phone, they must establish whether the person they are speaking to is the right party (the consumer or debtor) or not. The right party could also be a third party (a person authorized to handle the debt or an attorney representing the debtor). This process can take a few minutes.
With a Voice AI solution like Skit.ai, a Digital Voice Agent (DVA) handles the actual call — rather than just the dialing process. Once someone picks up the phone, the DVA can easily confirm right-party contact and engage with the debtor, offering ways to pay off their debt. If needed, the DVA can transfer the call to a live agent, who can assist with more complex queries.
The entire process is faster and cheaper and allows the collection agency to save time and money. Below, you can see a step-by-step summary of how a Digital Voice Agent handles a debt collection call:
Many debt collection companies are evaluating emerging technologies and looking into digital transformation. You can’t blame them: due to a faltering economy, rising costs, and high agent attrition, new processes and solutions are needed.
As a result, within the next three years, one in every ten interactions with call center agents will be voice bots driven, according to the new Gartner report. These findings are directly attributable to the spectacular rise to the advances in conversational artificial intelligence (AI), along with the mounting challenges we detailed above.
The report also estimates that by 2026, Conversational AI could save about $80 billion in labor costs! That is a significant number, indicative of the merits that early adopters will have in terms of cost, CX, and expansion of top and bottom lines. But, starting early is key to competitive advantage.
It is an open secret that high human agent churn is due to the fact that most calls are low-value and tediously repetitive. By handling these calls, Conversational AI will make the agents’ jobs more exciting and fulfilling, allowing them to focus on high-value and complex calls.
Globally, there are approximately 17 million contact center agents, and their cost makes up 95% of contact center costs. By intelligent call automation led by voice-intelligent technology, Voice AI, a big part of unproductive calls can be taken over by Digital Voice Agents, yielding high cost and CX advantages.
The Direct Cost and Efficiency Benefits of Voice AI for Debt Collection Agencies:
The most significant takeaway for the debt collection agency is that the benefits of Voice AI implementation are tangible and quickly realizable. But before we go into stats, here is a simple explanation of what essentially happens in a debt collection agency when they deploy a voicebot.
A voicebot is a conversational Voice AI application that can understand what the customer is saying as it is trained for a specific customer problem. It can strike a meaningful conversation with the customer. This happens because the entire conversation design has been done keeping in mind all the possible difficulties a customer can encounter.
So for every customer query, the voicebot has a ready answer as it pulls out relevant information from the client system and informs the customer, cutting the duration of the conversation remarkably.
Digital Voice Agents (DVA) Vs. IVRs: It is worth mentioning here that DVAs are remarkably different from IVRs; in fact, there is no comparison between the two. DVAs are at the cutting edge of the technological spectrum, while IVRs are legacy technology.
IVR can not converse. It is an unintelligent technology that runs a tedious exchange of inputs and outputs. For something as sensitive as debt collections, it is remarkably unsuitable.
Digital Voice Agent is AI-powered, built on Spoken Language Understanding (SLU) and context-rich conversational designs.
For a debt collections company, the two main categories of calls are Inbound and Outbound. Here is the process of value creation:
Inbound Calls: Many agencies cannot process a significant portion of customer calls. From them, a tiny fraction of customers have called to pay and perhaps need guidance.
Answering Non-revenue Generating Calls
The data from various sources is precise: A majority of calls are so simple that answering them by a human agent does not add any value to the company.
We’ve discussed the value of adopting a Digital Voice Agent for call automation. If you want to learn more, take a look at our Resources page, in which we regularly explore current topics related to the ARM industry.
Understanding the Top and Bottom Line Impact of a Voice AI Solution on a Debt Collection Company
The Final Word
Voice AI has proved its capability in bringing about a transformation of contact centers either with a small team or a big one. As its adoption increases, it will become a technology that can deliver sustainable cost advantages as well as a competitive advantage.
Refer to our Voice AI page for more information about its transformative potential.
What’s common among interactive voice response (IVR) systems, ATMs, knowledge base, mobile applications, virtual assistants or chatbots? They are all self-service options that can help dispense answers and resolve queries at lightning speed! Self-service or self-help tools and options make for an empowered customer support team and a loyal customer base.
Self-service equals simplified customer journeys!
In a mobile-driven digital economy, a brand’s relevance and value is measured in terms of the speed, convenience and the level of autonomy offered to their customers. Digital self-service is the central objective of today’s automated customer support, but tailored for better CX and performance. Since the COVID-19 pandemic, the usage of digitized self-service by customers across demographics accelerated with sudden digital transformation (DX). With newer entrants into the market— more digital native brands, always-on, smartphone users and Gen Z customers, numerous possibilities await businesses using digital self-service in their customer support. As per the recent OnePoll study involving over 10,000 respondents from 11 countries to explore humanity’s shifting relationship with digital tech and experiences:
Nearly 58% percent of participants said they will continue their digital brand interactions more than their pre-pandemic levels.
Most study respondents felt that the digital experience was fast and convenient, making it better or on par with the real-world, face-to-face customer service interactions.
Almost 66% reportedly had a ‘good’ or ‘excellent’ experience using online customer service options.
Diving a little deeper, the research summed up the exact reasons for positive reactions:
Instant issue/query resolution (48%).
These findings form the crux of self-service. In this blog we will begin our exploration on why self-service tools are truly adept in capturing customers’ interest, and meeting productivity and performance goals of brands’ customer support.
Psychology behind Self-service
Self-service is not the same as automation. Sure, digital self-service gives automated responses to repetitive queries in blazing speed. It is not only about allowing customers to resolve things on their own but also empowering them to address them faster. The overall value of the self-service strategy is measured in terms of its impact on CX. The faster, more convenient and more cutting-edge the self-service options, the better would be the CX scores. Moreover, the intuitiveness and simplicity of self-service helps reduce customer effort while solving problems on their own. This lowers the customer effort score (CES), another key metric for frictionless CX!
An intuitive, anytime self-service strategy across the platforms or channels also helps evade a laundry list of options for customer service-related interactions and unnecessary contact with human agents. This is integral for curbing additional contact center operations costs and allocating resources and human efforts in areas that build proactive and customer-centric impressions. No wonder, in the U.S. 88% of customers prefer self-service for dealing with their everyday problems. The number is equal to the global average of customers that expect brands and businesses to include a self-service support portal.
The Most Common Types of Self-service Options
Now, let’s have a look at this run-down of the widely adopted self-service support options.
Knowledge Base and FAQs: Internet-savvy customers leverage business/brands’ digital presence to find their way from the search engine platform to access information in a variety of forms (videos, landing pages, texts, infographics, illustrations, audiobooks, guides, and icons) for problem-solving. Dedicated FAQ pages that are brief and true-to-context is another form of self-service option that guides customers through specific customer service-related scenarios on the company’s website.
Integrated Contact Centers: Customer data is created across multiple channels. Integrated contact centers bind sales, contact center agents or other representatives with unified data sharing, collaboration and improved access to customer data across customer journeys and omni-channels for customer service. The intention is to boost CX and reduce the need to repeat information as customers navigate different customer service departments to solve issues on their own.
Interactive Voice Response (IVR) Systems: IVRs have existed for more than five decades. They are customer-facing phone systems that offer (inbound and outbound) support with pre-recorded messages and self-service menu responses to customers’ text inputs. They are cost-effective, scalable, and automated alternatives to human agents.
Chatbots: Chatbots use text-based or voice interfaces that are integrated to websites or mobile apps’ chat/message window to interact with customers. They are AI-driven and created based on the planned interaction flow chart to respond to customers in a matter of seconds.
Mobile Applications: Mobile apps with intuitive and interactive UX and UI give information to customers via dashboards, push notifications and updates in their moments of need, on their mobile devices.
Voice AI: A Quantum Leap in Self-service
The common forms of self-service options are the building blocks of the new age customer support. But there’s always the expectation for solutions that drive up the cost savings and operational efficiency while also helping brands’ contact centers meet their CX objectives. Imagine, if brands were able to achieve that while also offering self-service support that was voice-led, personalized, empathetic and proactively responds in real-time! For today’s automation and customer-first era, Skit.ai’s purpose-built Voice AI platform redefines self-service for optimizing customer support not only for better CX but for enhanced employee and business experience.
Built to enable conversations that are modeled on human interactions for prompt query resolution and personalized caller experiences, Voice AI is a next level of innovation in self-service. It delivers the best of voice experiences for brands through their contact centers that go beyond the capabilities of generic voice bots.
Voice AI is built to be domain-specific unlike generic voice-first platforms by Amazon and Google. The spoken language understanding (SLU) layer of Voice AI helps capture short, conversational utterances and is capable of deciphering semantic details that helps identify the right intent.
Voice conversations are the most natural forms of human communication and still remain one of the most sought after brand-customer interactions. Live voice conversations are critical to delivering high-quality customer experience. Customers interacting with self service options such as IVRS and messaging chatbots think before inputting a text command and hit send. Voice AI is a technology built to understand the intricacies of spoken language and not limited to text. It can quickly grasp customers’ voice interactions and filter through pauses and repetitions.
The Digital Voice Agents plug into the contact centers for automating cognitively routine work and independently resolving tier 1 customer problems. This would aid the human workforce to focus on more complex customer queries and contact centers to adopt intelligent human-machine collaboration. This way customers can stay in control and brands also get to pick the best self-service strategy for delightful CX.
Now, let’s dig into various features of Voice AI that makes it a better alternative to conventional self-service support:
Natural human-like Interaction: Digital voice agents that can mimic human-like conversations and comprehend interactions at a semantic level. It doesn’t feel like interacting with IVRs. It feels like holding conversations with the brands’ contact center agent.
Problem Recognition: Customers navigating through the self-service option can feel like they are lost in translation because of the complex IVR loops, limited menus or options that do not cater to their requirements. Sometimes chatbots are built with an ASR layer on top of NLP. They are great for transcriptions, not conversations. They deliver the same experience as going through a rigid IVR system. Digital Voice Agents can understand the right sentiment and nuances of human conversations, allowing the customer support to accurately identify and solve customers’ problems.
Always-on, Human Agent-free experience: One of the core value propositions of implementing a digital voice agent is its ability to function 24/7 for the ‘always-on’ customers without the dependency on human agents. This translates to cost savings by automating high-volume, zero-value and repetitive customer queries.
Quick Resolution: Self-service platforms optimized by powerful AI-capabilities and strong data sets based on customers data can be used for competitive advantage. It allows fast resolution, impacting customer satisfaction and CX.
Diversify Customer Service at a Lesser Cost: When more problems that are unique in nature can be handled by voice agents and automated, it helps brands’ customer service be a one-stop-shop for addressing customer queries at a fraction of a cost.
Smarter Human Resource Allocation: Self service options in contact centers make it easier to address trivial problems or anything that is repetitive in nature using Digital Voice Agents. Human agents can be allocated only for complex customer service issues, allowing for better resource planning and empowered customer support teams.
Make Self-service More human: Digital voice agents add a human touch to the overall experience without involving a human. The datasets are designed for SLU and built for domain-specific words which makes it easier to hold contextual conversation with the customers even via self-service options.
Hyper-personalize Customer Support: Brands can guarantee hyper personalization leveraging Voice AI’s extensive language support. It helps break spoken language barriers for enhanced query resolution and overall caller experience.
If you still have questions, refer to the infographic below for a brief comparative analysis between Voice AI and three most popular self-service tools.
Primarily Built for Voice Input
Analytics and insights Capabilities
Elasticity of Customer Service
Hyper-personalized and Contextual dialog Capability
Quick Query Resolution
Envisioning customer service in the age of self-service is all about setting the right priorities. With the hope of keeping up with the trends for relevancy, brands and businesses need not steer away from their cost, profits and resource management goals. That’s the core objective of reimagining customer self-service using Voice AI. Brands across industries can supercharge their CX with befitting self-service strategies to be more result-oriented and insight-driven to add a competitive edge.
Our reflections for the future—customers never settle and self-service alone is not enough! Therefore, we believe Voice AI is the most robust and well-rounded technology to improve customer support capabilities that go beyond conventional contact centers, adding a desired level of autonomy and self-sufficiency in customer service.
Refer to our Voice AI page for more information on actively engaging with your customers and unlocking the power of self-service. Book a demo with one of our experts–www.skit.ai
Let’s face it: third-party debt collection agencies often sit on high-volume portfolios of accounts, as they lack the capabilities and resources to contact all debtors. Ultimately, some agencies give up on reaching all those accounts, focusing solely on the larger ones.
ARM companies usually acquire thousands of new accounts each month, but many of those accounts might be left untouched due to the lack of bandwidth. For each account, collectors need to establish right-party contact (RPC), remind the customer of their outstanding balance, and offer ways to help them pay off their debt. More often than not, customers are not available right away, and the collector has to call them back at a different time. It’s not an easy job!
What if I told you that you could automate this entire process?
Yes, you heard that right. A conversational Voice AI solution can handle your collection calls on your behalf. Think Siri or Alexa, but for collections.
What Is Call Automation?
Contact centers in all industries — from banking to e-commerce and, of course, the ARM (Accounts Receivable Management) industry — are turning to automation as a strategy to overcome the challenges of managing both inbound and outbound calls with customers. While there are a variety of software applications out there, conversational AI technologies are booming right now. These tools are capable of handling conversations with customers without the need for any human intervention.
Gartner predicts that conversational artificial intelligence will reduce agent labor costs in contact centers by $80 billion within the next four years.
Voice AI technologies may sound “new” to you today, but they are set to become the industry standard in the collections and payments space within a few years. Early adopters will likely reap the benefits as they’ll be ahead of the learning curve.
When they hear “call automation,” many people tend to think about IVR (interactive voice response) technology. Think, “To make a payment, press 1…” In recent years, voice automation has significantly evolved with the emergence of conversational Voice AI, which is a more sophisticated technology than IVR.
A Digital Voice Agent (read: voicebot) can handle a human-feeling and effective two-way conversation with a customer, answering questions and providing context-specific information.
When integrated with your collection management software, the Digital Voice Agent can reach your customers, remind them of their outstanding balances, and offer them ways to pay via select payment gateways.
Are you curious to hear what an automated outbound collection sounds like? Here’s a demo of Skit.ai’s Digital Voice Agent calling a debtor to remind them of their due balance and collect the payment:
The Voice AI platform follows these steps:
Triggers the outbound call based on pre-determined criteria
Establishes contact with the customer (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
Is an AI-Powered Collector Compliant?
Compliance is one of the most common pain points for those who manage debt collections. There are so many regulations at both federal and state levels, and it’s common for consumers to file lawsuits against ARM companies, which can amount to major expenses on the agency’s part. Additionally, regulations often change, and collectors sometimes struggle to keep up with the new changes.
It’s actually easier to ensure that an AI-powered collector is fully compliant with local laws and regulations related to collections and phone calls. This is because a Digital Voice Agent:
The U.S. economy has been shrinking, with many experts already pointing out that technically we have already entered a recession, as the economy has now contracted for two consecutive quarters. Fears of a recession have dominated most sectors of the economy over the last few months, and the ARM (Accounts Receivable Management) industry is no different.
The economy is slowing, inflation is high, and the Federal Reserve has been increasing its interest rates, and yet the data suggest that we find ourselves in a more complex and nuanced situation. Unemployment is still very low and the economy has been adding hundreds of thousands of new jobs each month, suggesting that it’s not all doom and gloom.
The latest reports, however, predict there will be a “mild recession” between 2022 and early 2023, with inflation being a major indicator of the direction the economy is headed towards, according to authoritative institutions such as Bank of America and Wells Fargo.
How can debt collection agencies prepare for a recession, and what do we know from previous economic crises that can guide us through the uncertain period ahead of us?
What Happens to Collection Agencies During a Recession?
Times of economic uncertainty are a mixed bag for collection agencies.
During a recession, the consumers who have the ability to be more conservative with their spending habits may choose to be more careful than usual. This might result in less borrowing. However, accounts might start increasing significantly as soon as the economy recovers.
On the other hand, for the people who already owe money, it might be more difficult to pay off their balances with jobs and income in jeopardy—leading to more defaults.
Additionally, the agency itself might need to take measures to cut down on costs. This may result in a reduction in staff, which will directly affect collection rates.
How Did the ARM Industry Fare in Previous Recessions?
Data gathered by the advisory firm Kaulkin Ginsberg shows how the ARM industry reacted to the last two major economic crises in the United States.
During the Internet bubble bursting — also known as the Dotcom crash — the ARM industry experienced a boom, with its revenue increasing from $8.2 billion in 2000 to $9.3 billion in 2001—a 13.4% increase. Between 2002 and 2005, the industry experienced continued growth at a similar rate.
The Great Recession of 2008, however, put the ARM industry to the test. The revenue fell by 14.4% from 2007 to 2009. Debt collection agencies struggled to collect payments, as consumers did not have the ability to pay off their debts. Many lenders scaled back their operations, leading to less accounts for collectors to manage.
And yet, just like in the previous crash, the years following the Great Recession were pretty good for the industry. While growth rates did not resemble the pre-recession boom, the industry still grew at an average rate of 4.16% per year.
5 Steps Collections Agencies Can Take To Prepare for a Recession
Optimize All Processes
To make your organization recession-proof, the first step is to optimize all of your internal processes and workflows. Analyze the existing processes and the customer journey and ask yourself: Can you identify any pain points? Where are resources missing and where are they abounding? Are there any workflows that can be shortened or reshuffled? Are there any tech tools to add to your stack that can help with any of the issues you’ve identified?
Invest in Agent Retention
Agent attrition in collection agencies is very high, and this creates additional expenses, as agencies need to cover recruiting, hiring, and training costs each time an agent leaves their job. Investing in agent retention is a must for agencies preparing for a recession. You want to keep your agents happy and make sure they don’t feel overly stressed or overwhelmed with calls. Consider adopting tech solutions that could take over some of the most repetitive and tedious agent workload.
Prepare for Account Volume Fluctuations
As account volume gets more volatile, agencies may experience more fluctuations in volume of outbound calls, needing more or less resources depending on the time. Agencies should develop a strong plan to address these scenarios; plan ahead even if you might not be experiencing this issue yet.
Offer Plenty of Payment Options
Once a customer is ready to pay, you should make it as easy as possible for them to pay using the method they prefer, including mobile payment apps. Collection agencies have started adopting PayPal and Venmo as payment methods, and the first data suggests that adoption is very successful.
The majority of Americans (79%) use mobile payment apps, according to a survey by NerdWallet. When looking specifically at the younger generations, the numbers go up: 94% of millennials use mobile payment apps.
Invest in Customer Self-Service
The existing data on customer service and customer experience indicates that customers expect companies to offer self-service customer care options. 39% of U.S. consumers find it very important to have access to a fully self-serve customer care option available to resolve their issues, according to a report by Emplify.
Self-service for a collection agency includes the ability to easily make payments and solve smaller issues by using the agency’s website, a mobile application, or an AI-powered Digital Voice Agent. More on that in the next section!
How Debt Collection Agencies Can Rely on Voice AI To Prepare for a Recession
Looking ahead and adopting technological solutions that can help you automate processes and improve the customer and employee experiences is one of the best ways to future-proof your collection agency, especially as we prepare for a likely recession.
Voice AI — AI-powered Digital Voice Agents to perform your outbound calls and collect payments from your customers — is becoming more and more popular and common among collection agencies in the United States.
In a recession, you not only want to save money, but you also want to ensure you maintain a competitive edge over your competitors. Looking into the adoption of artificial intelligence technologies that can automate your operations is key to securing a competitive advantage.
The need for digital transformation (DX) can hardly be overemphasized. The need for DX and automation is becoming more conspicuous in the debt collection space. Globally, companies are expected to spend a whopping $1.8 trillion on DX technologies, and what’s more incredible is that DX spending will sustain the momentum and grow at a whooping CAGR of 16.6% between 2021-2025 (IDC DX spending guide).
While the investment and gung ho surrounding DX are real, typically, companies find it hard to succeed at DX, and further challenging is to sustain that success. Only ⅓ of companies succeed at DX, and a much smaller fraction has been able to sustain that success. This blog focuses on one technology that has proven to have a high business impact, and success rates, while being easy and quick to deploy, i.e., Voice AI.
Debt collection space has not remained insulated from the recent tumultuous years. The industry is amidst epochal changes as challenges mount in 2022. The overall grim economic forecast, inflation, and frequent regulatory changes make it imperative for debt collection companies to transform. In 2010, U.S. businesses placed $150 billion in debt with collection agencies, who could collect just $40 billion of that total. On delinquent debt, the industry averages a 20% collection rate, a decrease from 30% a few decades ago.
Technology is the only potent tool capable of overcoming core challenges and transforming debt collection companies.
Ironically, 7 in 10 U.S. small businesses put off technology decisions and are invested deeply in day-to-day tasks, according to a 2021 study from Xero, a global small business platform. The implications of this are clear–companies will not be able to incorporate technology that is vital to their long-term survival. No wonder the majority of DX efforts result in digital grief. Hence the discussion on a technology that brings about quick and easy transformation is vital. But first, let’s deep-dive into the challenges that are crippling collection agencies.
As CXOs look forward to improving the performance of debt collection agencies, here are the core problems they are trying to solve:
Efforts have been made to solve these problems, emanating out of 8 core challenges:
What Digital Transformation (DX) or Being Digital-first will do?
DX is essential if a company wants to thrive in the long run. But it is a precarious journey, and only when prudent technology incorporation is done, it brings about positive outcomes.
For the same purpose, we delve into the nuances of technology that a debt collections agency can incorporate. Post transformation, debt collection agencies can leverage technology to be more agile, more efficient, and automate most of their processes.
Technologies Enabling Debt Collection Companies
We have classified the technology into two parts – Those that help in communication and customer support. and those that support the business function.
A. Customer Support Technologies
i. Voice-Based Conversation Technologies
We can look at voice-based technologies from a standpoint of their newness. This is important because most debt collection companies have to decide what to upgrade, integrate and replace.
Dialers and Telephony
Voice AI or Voicebots
The larger discussion here would be about legacy systems. Dialer and telephone are very important and can be of great value if they are on the cloud. IVRs are still useful, but are equally frustrating, so a decision to either replace them or upgrade them is a big one. Voice analytics is a new and emerging tech, and debt collections companies will benefit if they leverage it. We will discuss Voice AI in detail, as the potential for value creation is incredible.
ii. Text-Based Conversation Technologies
They have been the oldest ones and have also been a part of legal mandates. These technologies are a significant part of interactions with customers, notifying them at the right time.
Chatbots and Text Messages
Using Email in Debt Collection
Text messages have been a vital part of debt collection as they are mandated by regulations. Chatbots are new and are improving rapidly, but since debt issues are complicated, it is not the favored go-to modality for problem resolution.
B. Technologies Supporting Business Function
These technologies power the business function of debt collection agencies and help them operate at better operational efficiency and agility.
Collections CRM for Debt Recovery
Debt Collection Compliance Software
They are very essential and can help debt collection agencies perform operationally better.
Analysis of Cost Structure
To assess the impact of technology, it will be necessary to analyze its impact on cost and revenue. Typically the cost structure of a debt collections agency is like this:
Even a cursory look at the graph makes it abundantly clear that wages are the most significant element of the cost structure, ranging near 42%. Hence a technology that helps debt collection agencies minimize this cost via automation will have a significant impact on the structure of collections agencies.
Call Automation via Voice AI
Voice AI is the most disruptive technology of our times since it automates the most expensive part of contact center operations – calls and conversations.
It is one-of-its-kind technology that can enable debt collection companies to make complete calls without requiring a human agent. Lately the Voice AI technology-based SaaS platforms have become quite affordable and quick to deploy. Hence are creating large competitive advantages for early adopters.
AI-enabled Voice Agents have been optimized to understand spoken language and strike intelligent conversations. The voice engine picks up not only what the customer is saying but also the semantics of the conversation.
Perhaps it is the most disruptive of all the present technologies as it is empowered to answer customer calls, and can reach them out independent of human agents. They are also excellent at updating customers and adhering to compliance requirements. They are proven to cut costs and improve agent productivity and collections rate.
Solving the Biggest Challenge – Automating Voice Conversations
A major chunk of the cost of a debt collection agency involves human agents’ salaries and similar expenses towards that end. Today, for the first time, companies have the technology to automate voice conversation and make calls possible without the need for human agents for as much as 70% of call volume.
We are in this section to delve deep into this new era of technology that will help companies transform truly.
The rapid rise in call volumes, defaults, demand for remote resolution of disputes, and diminishing CX have resulted in collection agencies scrambling to catch up.
The need for better outbound collections efforts—along with managing increasing volumes of inbound inquiries from customers—is putting pressure to scale contact center teams, an undesirable and herculean task.
Call center turnover (30 – 45%) has always been a challenge and has generally been twice as high as the industry average (13.5 – 18.5%), while collection agencies perform worse, with some reporting as high as 100% employee turnover. The concatenation of these factors—higher call volumes, regulations, and agent turnover—has made companies lookout for technology solutions such as Voice AI-enabled contact center automation.
Let’s compare the challenges collections agencies are facing to how a conversational AI-enabled Intelligent Voice Agent meets every challenge.
Beginning the DX Journey With Voice AI
Of all the technologies, the deepest impact has been seen with the deployment of Voice AI. This is because a major part of what a debt collections company does is conversations and automating them is going to create an unprecedented amount of value.
Once a voicebot or Voice AI agent is deployed, here is what that happens:
Automated campaigns with clear data documentation
Clear capture and documentation of the disposition/intent
No breach of compliance as the virtual agent stays true to script
Handing the same volume of calls with a much smaller human agent team
Improve compliance adherence by Voice AI strict adherence to scripts, timings, and regulatory changes
Immediate cost savings and revenue expansion
7 Reasons to Adopt Voice AI For Debt Collection
Augmented Voice Intelligence or AVI is the blend of Conversational AI and human intelligence. It creates meaningful conversations with customers to support them throughout their entire collection journey while adhering to compliance and regulations. Let’s delve deeper into the 7 core reasons:
Read in detail about these reasons in this Article
Here are a few outcomes contact centers have been able to achieve and are equally applicable to debt collection agencies:
Near 50% reduction in contact center operational cost:
Debt collection companies can work with a small team of human agents and handle the same amount of accounts. This is due to the automation as a majority of calls by Voice AI Agents.
The debt collection companies save on the hassle of recruitment and large wages.
The voicebot would also help companies cut down on agent commissions that typically range between 20-25% of the agent’s fixed compensation and is paid over and above the fixed component. This happens because the voicebot can enable payments without the need for human agents or does end-to-end automation. The higher the proportion of the payments the voicebot enables, the higher will be the saving on agent commissions.
Over 35% automation of customer support efforts:
For a debt collections company, the split–80% (Outbound) and 20% (Inbound) holds true. Let’s look into the proportion of call automation:
Inbound: Though it depends upon the number of uses the voicebot is trained for, at an evolved stage, it can handle as much as 70% of total inbound calls. Escalating only the complex cases to human agents. Also, even if the call is escalated, the voicebot will capture the intent and establish the right party contact before transferring the call to a human agent. This adds value and saves agent time, and this reduces the cost.
Outbound: Typically a voicebot will make multiple rounds of calls for the entire database before it can capture the soft PTP (propensity to pay). Only on the select accounts, the human agent will make the call. In many instances the voicebot does the job, in the same manner, a human agent would and thus creates value by replacing his effort. For instance, it can successfully establish:
Wrong party contact
Capturing disposition to pay
About 40% reduction in Average Handling Time
Overall companies across industries have observed a drop in average handling times. This is because even in most simplistic use cases the voicebot will verify the consumer, identify his/her intent, and summarize the interaction. This helps the human agent close the query faster.
Smoother Recovery with Better CX
Making the right call, to the right person at the right time makes a world of difference in collections space. Voicebot with its meticulous follow-ups, with the right message, can help customers make payments more conveniently. Hence companies see better recovery with better CX.
When going for DX, a piecemeal approach is the best. It is most prudent to start with technology with the biggest impact on the performance of the company and has the highest ROIs. But concurrently it must be easily accommodated into the current process with slight modifications. Voice AI possesses all the qualities, making it an ideal point to begin the DX journey.
AI-enabled Voicebots such as Skit.ai’s Digital Voice Agent thus has helped companies transform their contact centers with positive business outcomes.
For any questions on selecting the right Voice AI vendor and the technology, please schedule a meeting on www.skit.ai
The debt collections industry is a heavily regulated space; for newcomers, the number of laws and regulations in place can be quite overwhelming. Whenever a new technology or tool emerges, therefore, it is natural to wonder whether it is compatible with the existing laws and whether the provider is fully compliant.
As more collection agencies look into adopting a conversational Voice AI solution to automate their outbound calls for collections, it can be confusing to go through the regulations and determine which ones apply and which ones don’t.
In this article, we’ll unpack one important law — the Telephone Consumer Protection Act — and analyze its key provisions from the perspective of a Voice AI provider.
Solicitors can’t call customers at night time (indicatively, between 9:00 p.m. and 8:00 a.m.). However, the specific hours are determined by each state. For example, certain states do not allow calls on Sundays (e.g. Alabama, Louisiana, and Mississippi, among others). During the week, the starting time when calls are allowed varies by state—between 8:00 and 10:00 a.m. Calls need to be interrupted between 6:00 and 9:00 p.m. depending on the state.
National Do Not Call List
The National Do Not Call Registry was created to stop unwanted sales calls; anyone can register their phone number. Good news! This provision only applies to telemarketing calls. Luckily, debt collections do not qualify as telemarketing. However, if the customer explicitly asks not to be called, the collection agency needs to honor the request.
Self-Identification via Voicemail
If the collection agency wants to leave a voice message to the customer, then the collector must identify themselves and the agency and provide their telephone number.
Calling Mobile Phones
Nowadays, fewer people have landlines at home, and virtually everyone owns a cellphone. Still, the TCPA rules that callers can’t call a mobile phone without prior consent when using an automatic dialer, artificial voice, or a pre-recorded message. Therefore, one must obtain direct consumer consent prior to the use of these technologies to contact cellphones.
In the next section, we’ll see why Voice AI is not considered an automatic telephone dialing system (ATDS).
How the TCPA Impacts the Use of Voice AI
A Voice AI solution like Skit.ai’s does not utilize pre-recorded messages nor does it play a series of pre-recorded scripts offering customers the ability to select one of several paths to additional questions. Skit.ai’s Augmented Voice Intelligence platform is intelligent, dynamic, and conversational.
In 2021, the U.S. Supreme Court issued a decision on Facebook, Inc. v. Duguid, a landmark case on the definition of automatic telephone dialing system (ATDS) under the TCPA.
In a unanimous decision written by Justice Sonia Sotomayor, the court ruled that equipment that can store or dial telephone numbers without using a random or sequential number generator does not qualify as an ATDS under the TCPA.
When it comes to Skit.ai’s solution, while it does not randomly or sequentially store or dial phone numbers, prior consent is still required.
First of all, there is the issue of artificial voice. Skit.ai relies on advanced voice cloning technology to train the Voice AI using samples of real human voices.
Secondly, the Digital Voice Agent typically does not generate the outbound call on its own; it’s advisable to ensure that the infrastructure used is in compliance with the TCPA.
Please note that the information in this article is not intended to be legal advice and may not be used as legal advice.
For more information and to request a free demo, you can schedule a call with one of our collections experts.
You’re not sure about Voice AI, you have some doubts, and you need some guidance? Are you wondering what a Voice AI solution can do for your company or agency; which risks are involved; and will this technology help you get ahead of your competition?
This guide seeks to answer all of your questions about Voice AI.
This is a unique ebook designed to enable informed and quick decision-making for debt collection CXOs — a comprehensive step-by-step guide for CXOs in the debt collection space to explore Voice AI technology and understand its core capabilities and the qualities of an ideal vendor. Additionally, we’ve included a section detailing the entire implementation process, from ideation to execution and beyond.
The ebook is divided into three sections:
Section 1: Fundamentals. In order to be able to take the informed decision, one needs to know about the product or services. This section contains the fundamentals of Digital Voice Agents, the tech behind it, and why it is important for the debt collection space.
Section 2: Selection Criteria. This section details the capabilities that a debt collection company must look into when considering Voice AI vendors. Several capabilities and complexities should be considered before making a decision.
Section 3: Implementation Guide. This section is a deep dive into the process of implementing a Voice AI solution, from ideation to execution, every step, in granular detail. This will prove vital in not only ensuring final success but also in time and ease of execution.
Section 1: Fundamentals of Voice AI
From its peak in 2009, consumer debt grew by $2.3 trillion to almost $14 trillion in 2019. In 2010, U.S. businesses placed $150 billion in debt with collection agencies but recovered a fraction, i.e., just $40 billion. The industry averages a 20% collection rate on delinquent debts, decreasing from 30% a few decades ago. Overall, the performance of debt collection companies seems to be facing major challenges.
Rapid changes in regulatory and customer experience expectations are taking place in the collection space and are posing serious challenges to collections agencies.
High number of untouched files: One of the third-party debt collectors has over 1 million files across portfolios, but because of the lack of human resource bandwidth, they are not able to reach out to all of them. Though they might send automated text messages to all of these, they know it’s not enough. They could actively pursue and call only 30-40K prioritized files with an outstanding balance of more than $1,000. The agency is not able to get any collection out of 960,000 files that are completely untouched.
High wrong party contacts: The menace of having a wrong contact number and associated problems is prevalent in the industry and is eating away the margin. Every call placed to a wrong party causes a financial loss for your business. These calls are simply non-value adding for any human agent.
High number of non-revenue-adding calls: Other than wrong-party connect, there are many other calls which do not add much value. For example, requests to dispute a debt, through an inbound call or outbound; another example is second-party contact or speaking with a customer who is busy and wants a call-back later. For an agency, any call that does not resolve in payment in the immediate future does not add much value.
Lack of persistent efforts and follow up: One of the most important things in collections is persistency. One industry expert argued that it requires 16 calls to reach an average consumer.Another industry expert, a large debt buyer, stated that, when searching for a consumer, it places between 50-75 calls per debt before achieving RPC.When trying to establish contact, consumers sometimes ask to get a call-back at a later time. After agreeing to pay, collectors have to remind the consumers on a regular basis. If your agents are not able to follow up persistently, collection rates are bound to go for a toss. And it’s humanly impossible to be able to follow such a strict schedule.
Compliance and script breach: Compliance requirements have become stricter. It’s essential for a collection agent to follow a strict script, be it Mini-Miranda, communication protocols such as 7-7-7, or keeping their cool after a bad day.
High attrition: Attrition in our industry is at an all-time high. One of our customers jokingly said that a McDonald’s worker earns more than a debt collector. Average attrition in some of the cases we’ve seen is around 200%, meaning that the average employee stays at the company for no longer than 6 months. With such high attrition rates, hiring, training, and employee-related costs have become extremely high.
Scaling up/down: At times, when you have a new portfolio or file, the workload increases. However, it’s not wise to hire agents only for such surge periods, so operations leaders end up deciding to work only with the available resources. This approach significantly reduces the sped of collections.
These issues ultimately result in lower collection rates and high collection costs.
Before we dive into how Voice AI solutions can help debt collectors, let’s understand the fundamentals of what a Digital Voice Agent is and how it works.
The Tech Behind a Digital Voice Agent
What is a Digital Voice Agent?
A Digital Voice Agent is an AI-powered conversational robot (commonly known as a voicebot) that has the ability to interact with a user and take a certain sets of actions to meet an end goal. It is very similar, but not the same, as voice assistants like Apple’s Siri, Google Assistant, and Amazon’s Alexa.
How is it different from voice assistants?
Voice assistants are designed to handle one or two turns of conversation to meet generic day-to-day tasks and are not designed to retain context longer than that.
Intelligent Voice Agents, on the other hand, are designed to solve specific problems which require much more than two turns of conversation, just the way humans solve queries by first asking multiple questions to understand the context and all the required information to solve a given problem.
For example, a lost credit card can be blocked by asking a series of standard questions. The first couple of questions are to verify the caller, and the next set of questions are to confirm which credit card should be blocked, and then followed by an action where the customer is issued and sent a new credit card. Typically, this is a 6-7 turn conversation that generic voice assistants are not designed to handle. Specialized voice AI agents are required to be built and trained to handle such tasks.
Digital Voice Agents sit on top of telephony and dialer systems. So apart from these two, fundamentally, there are at least five components (engines) to any voice bot:
ASR (Automatic Speech Recognition): This converts the voice into text transcription. This is alternatively called speech-to-text or STT Engine.
SLU (Spoken Language Understanding): This is the brain of the voice bot. It extracts intents and entities (data points) from the text sentence produced by ASR and then comes up with the best possible action. That action can be performed in terms of voice reply or sending a document or a text message, or transferring the call or raising a ticket etc.
TTS (Text to Speech): The block that translates the text into voice to generate a reply.
Dialogue Manager (Orchestrator): The block that manages the flow of data among the above three blocks and the flow of the conversation.
Integration Proxy: These are integration sockets that connects with CRMs, Payment gateways, Ticketing systems, etc in order for voice agent to be effective and efficient in end-to-end automation.
These processes happen in real time and within milliseconds. This is only one turn of the conversation and the process is repeated for subsequent turns.
All of these processes are performed in the cloud after the voice packets are received from a user. So it doesn’t really matter which device the caller is using—whether it’s a smartphone or a feature phone or a wired telephone. Skit’s Digital Voice Agents leverage all of these layers to seamlessly plug into contact centers and augment the work of human agents.
How are Digital Voice Agents different from chatbots?
Technically, an AI-powered voice bot has two extra engines that a chatbot doesn’t need. Since chatbots do not deal with voice, the two engines related to voice (ASR and TTS) are not required. The text input is fed directly to NLU and the intents and entities are extracted and the response is synthesized in text format and relayed back to the user.
Furthermore, voice queries on call bring with it certain challenges like noisy backgrounds, different accents and dialects of speaking the same language, language disfluencies and unique way of adding filler words and pauses, barge-in by a person while the other one is speaking; all of which directly impact accuracy.
And for the same reason, voice bots are much more difficult to build. Everything has to be real-time within milliseconds and there is little to no room for error, else communication experience is hurt.
What sets voice bots apart is that they’re faster. Voice is the quickest and most natural form of human communication—faster than typing or navigating drop-down menus with a mouse. It continues to be one of the most sought-after by end customers seeking support.
How Is Augmented Voice Intelligence Different from IVR?
What is an IVR?
Interactive Voice Response (IVR) is an automated phone routing system that interacts with callers and gathers information by giving them multiple choices via a menu. The system then performs actions based on the answers of the caller through the telephone keypad, which is also called DTMF (Dual Tone Multi Frequency).
IVRs are used by companies or contact centers to route calls based on the choices made by the caller in order to organize call queues of call centers. Through the caller’s selection, the system can determine if the caller wants to contact the billing department, the technical support team, or simply wants to talk to a human operator.
IVR in its backend is a top-down tree structure in which input from user determines which downstream node the call will flow to. End of the node can be either human agent transfer node or self-serve node. In case of self-serve node, a pre-recorded message is fetched from the database and played, for example, in account balance enquiry node, a pre-recorded message with be played along with a variable value, in this case fund balance.
IVR is also used to provide information like promos, updates, or other important information or instructions. One example is to inform callers that the system will record the call.
Lately, IVR providers have come up with voice response instead of DTMF. For example, to reach the billing department, the caller has to say “billing” instead of pressing a key on the the phone. This works on keyword matching. However, if caller utters a long sentence and doesn’t include the relevant keyword, IVR would not be able to recognize the input.
Typically, an Outbound IVR (Interactive Voice Response) is also used to reach out to a large number of customers in a personalized manner using different interaction channels, such as voice messages. The most common use cases are feedback, promotions, announcements, reminders, etc.
Robocaller or outbound IVR has essentially two components in it: (1) a dialer capability and (2) a text-to-speech engine (Advanced Outbound IVRs) or a recorded voice message (Robocaller). Businesses can upload thousands of contacts to the dialer and configure certain parameters such as number and time of retry attempts, time of call etc. The dialer calls these contacts and plays a voice message which consumers can listen to. At the end of call, the consumer can provide keypad based number input to listen to the message again and perform other tasks.
Limitations of IVR
In the 1990s this technology was a game-changer and led to a significant improvement in efficiency. However, today this system is ineffective and unnecessary, to say the least.
Even the most sophisticated outbound IVRs ail from persistent challenges as enumerated below:
Unidirectional Communication: IVRs are capable of only unidirectional communication with a limited DTMF (keypad-based) feedback mechanism.
Low Engagement: IVRs have extremely low engagement rates owing to their non-conversational unidirectional communication.
Right party contact: Inability to capture conversational inputs and run verification to check for right-party communication. Today, you cannot pass on debt related information to the wrong contact even inadvertently.
Lack of ability to capture important dispositions: Robocallers or outbound IVR can’t capture meaningful dispositions that can be used downstream, such as:
Willingness to pay, and expected date and mode of payment
Refusal to pay and associated reasons
Debt dispute and reasons
Willingness to pay partially and offer payment arrangements.
Ability to capture call-back date and time for busy customers.
Lack of insights for segmentation: Inability to segment the pool of consumers based on disposition to help debt collection companies make meaningful strategic decisions.
Inability to reach out to consumers on their preferred time: Since Robocaller cannot capture disposition for busy consumers, it cannot intelligently call back or arrange call back from human agents.
Payment assistance and goal completion: Cannot help or guide the willing consumer to make the payment during the call.
Human-Agent Dependence: For a large number of calls, human agents are needed to reach to a meaningful end result.
Compliance adherence: Since every call campaign is triggered manually, compliance is in the hands of the operator who is running the campaigns.
Customer Experience: Because this system is extremely impersonal, it miserably fails at contributing to CX.
IVRs, even at their best, do not contribute to CX or major productivity gains, whereas a bad IVR experience can prove very costly. The State of IVR in 2018 noted that 83% of customers would avoid a company after a poor experience with an IVR.
The more pressing problem still remains:
“How to automate the mundane, repetitive and non-value additive tasks human agents are doing”
For a long time, we did not have an answer, or we did not have a commercially viable technology solution, but today we have, and it is Intelligent Voice AI Agent.
Digital Voice agents are AI-powered virtual agents that allow customers to converse intelligently, without having to punch 1,2,3,4 on their screen to hold meaningful contextual conversation. It is able to converse with your consumers just like your human agents.
It is capable of understanding, interpreting, and then analyzing conversational voice input expressed by an individual and responding to them in an everyday language.
A Virtual Voice Agent goes beyond understanding words, and determines what the consumer is saying based on underlying semantics, without relying on specific keywords. Using machine learning, a Virtual Voice Agent is continuously improving itself and the customer experience.
A Comparative Look: Digital Voice Agent vs Outbound IVR
Section 2: Selection Criteria
Debt collection is not a simple industry. It is heavily regulated and involves a whole gamut of laws, which keep on changing. Additionally, it’s affected by the pressure to cut down on costs for the collection agencies.
For the first time, there is a technology that answers most of the challenges faced by debt collections agencies. Still, incorporating this tech presents its own set of risks.
Being experts and experienced in the debt collection space, we at Skit.ai have outlined a guide that helps CXOs understand what capabilities to look for when selecting and evaluating a Voice AI vendor.
Look for these core capabilities as you decide how to transform your debt collection business with Voice AI.
Deep Understanding of Business Operations and Processes
A voice technology company can have an impressive tech stack but may still not be suitable for you if they lack domain or industry expertise. They need to understand the nuance of the business and the consequences of conversations, reach out, and promises.
Why is it important?
A deep knowledge and understanding of business operations and processes in the collections space is essential, because debt collection is a complex, heavily regulated industry. Lack of knowledge is not only risky from a compliance standpoint; it can also hinder the creation of intelligent and intuitive conversation designs.
Designing a DVA is as much an art as it is a scientific and technical process.
The conversation with a consumer will be drastically different for a debt which is 30 days old compared to the one that is 5 years old, consumers might not remember the debt or card after some time. Conversation design will drastically change on various factor such as:
Nature of Debt: Knowledge of intricacies of different types of debt – credit card, healthcare, mortgage, telecom, etc.
Age of Debt: Knowledge of nuances involved with debt with different ages. A 30-day DPD debt is remarkably distinct from 180 DPD debt.
Conversation Design Capabilities: Is the vendor capable of managing the subtle differences and incorporating those in conversation designs.
If these factors are not considered, the end product would be suboptimal and end consumer will drop out of the conversations.
Consequences of lack of expertise in the area
Here are some of the issues you are likely going to run into if your Voice AI provider does not meet the aforementioned standards:
Higher involvement at every step: If they are not familiar with the business challenges and operations, they are going to reach out to you for every issue they encounter and seek help in designing flows.
Poor quality of voice agents: A voice assistant or agent can only be as good as its conversation designs. It takes humongous effort and time to create natural and intuitive flows that already understand the most probable customer queries and follow-up questions. Only an experienced voice solution provider can help you succeed in having a voice agent with a stellar performance.
Longer implementation time: There will be multiple to-and-fros as your vendor will come back to you asking for input every step of the process.
Internal resource time and effort: You expect your Voice AI vendor to do most of the work on its own, but that may not happen if there is a lack of expertise. You will end up dedicating a big team to help them design a functioning voice agent. This will disrupt your organizational functioning on an ongoing basis.
Higher cost: Longer implementation time, higher internal resource involvement, and higher need for testing will ultimately culminate in a higher cost for you, both directly and indirectly.
Ability to Handle End-to-End Automation
You should expect your Digital Voice Agant to have the capability to deliver end-to-end automation. In other words, they must have the capability to handle calls from start to finish without the help or intervention of a human agent.
Why is it important?
These days, AI-powered Digital Voice Agents should be capable of handling conversations end-to-end. It would be limiting to use DVAs only for call routing and to identify right-party contacts and transfer calls to human agents.
On average, 70% of customer requests fall into the tier-I bucket; this means that a Voice AI agent must be able to automate, End-to-End, a majority of calls.
This is the most vital capability of a Voice AI solution as entire value creation, productivity enhancement, and business performance rest on it.
Imagine the kind of value that can be created by taking away more than 70% of frustrating calls your human agents are handling.
Here is a list of a few capabilities that augment End-to-End Automation:
Capability to collect payment on call
Debt dispute handling (end-to-end)
Sending digital validation
Identifying RPC and WPC
Consequences of lack of expertise in the area
What happens if the vendor you are speaking with does not have a high-end-to-end automation capability?
Impact on scalability: We know that maintaining a large human agent team is a painful task. The highest attrition rates, not only make it an operational hassle but also escalate the costs to retain them, and keep them engaged and satisfied. With End-to-End Automation capability, Voice AI technology is minimizing your reliance on human agents. You do not need to recruit more when call volumes surge, nor do you need to have a larger team if you want to deal with a bigger portfolio of delinquent accounts. Let’s compare to make the point crystal clear:
Vendor 1: End-to-End Automation capability of 70%: You need human agents for just 30% of complex calls. This means 24/7 majority of your customers will be able to solve their problems instantly, without IVRs and then to human agents. You need to keep a minimal team, a happy team that will work even better as they are now not dealing with interesting and value-creating calls. This has a lasting positive impact on cost structure, HR costs, and other indirect costs.
Vendor 2: No End-to-End Automation: Though the Voice AI agent will be able to identify the right-party, you will always need human agent for every call as call is transferred from DVA to a human agent. This means you will always need human agents for DVA to realize the value since there is no end-to-end automation.
Platform Approach for Rapid Roll outs and Time-to-Market
A platform approach has its typical advantages. Cloud-based modularity makes enhancements and tweaks very easy.
Why is it important?
A platform gives visibility into the system, and for many elements, the adopting company can have the option to tweak things such as conversation flows to better voice agent performance. Additionally, it is easier to deliver upgrades and enhancements collaboratively and transparently.
For instance, Skit.ai offers access to the Skit studio platform, which gives its clients a comprehensive view into how things are moving along. This makes the entire BTDME — build, test, deploy, monitor, and enhance — journey significantly smoother.
Having a user-friendly platform also helps with the integration of third-party applications such as payment gateways, CRM, and other business applications. In the long run, these capabilities can be the difference between winning and losing.
Consequences of lack of expertise in the area
The lack of a platform converts the Voice AI solution into a black box. You have no idea about its functioning, and you will depend on your vendor for everything. This will not only elongate the enhancement process but will also make it costly.
More often than not, time is everything. Consider the damage a wrong information-based conversational flow can do if not updated in time. The compromise on agility is severely debilitating for any company sensitive to CX and changes in consumer behavior.
Compliance Expertise and Experience
Everyone in the debt collection space is aware of Reg F. and the challenges it posed to debt collection agencies as they work to understand the implications and ensure proper compliance. If your vendor does not have the required knowledge and expertise on compliance and regulations, the consequences can be problematic for your agency.
Why is it important?
Leaving alone the increasing fines and penalties imposed by the regulators way more significant are getting involved in lawsuits and court battles.
Companies must seek a vendor who knows the law in and out. Considering the direction of regulations going stringent by the year, the significance of expertise in this area can not be hyperbolized.
Various tasks such as data scrubbing are difficult for a human agent but a breeze for Voice AI and can prevent a potential lawsuit. Furnishing statutory information such as Mini Miranda or relating to other laws is easy for voice AI agents, but your vendor must have the in-depth expertise to train the voicebot for it.
Consequences of lack of expertise in the area
There are two significant disadvantages if your vendor lacks in this area:
Lost Advantage: One indisputable fact is that Voice AI Agent is better at ensuring compliance. Human agents are prone to err and engage in false promises and indecorous use of language. A state-of-the-art voice AI agent makes compliance adherence bulletproof. But if your vendor is conversant with regulations you not only run the risk of breach of compliance but also you miss out on one of the biggest advantages associated with voice AI agents.
Cost Implications: Running into lawsuits costs companies dearly that are already dealing with thin margins.
Business Performance: Faltering at one regulation, or one lawsuit puts the entire company on a backfoot and triggers introspection which slows down the entire business.
Looking into MLops, capabilities are essential as they have a lasting impact on the performance and competitive edge.
Why is it important?
At the core of Voice AI lies the capability of the algorithms to learn and improve as more and more conversations are fed into it.
The more extensive this capability, the more robust will be the learning gains, and the ability of the system to improve the conversations.
Consequences of lack of expertise in the area
The absence of AI/ML or only feeble attempts at it has severe consequences because as companies who are updating their AI/ML models, regularly feeding more and more data will create superior conversations, and will augment their capability to handle conversations.
This means having a proprietary technology stack and not relying on open source technologies.
Why is it important?
A score of reasons are there for you to look for proprietary technology.
Process Efficiency: If a Voice AI company is using its own tech, they have labored hard to optimize it, as well as the integration they are using. This enhances the overall performance to a great extent and makes a world of a difference.
Constant Improvement: Having ownership of the tech stack helps in rapid improvements and releases.
Safety and Security: For a sensitive industry such as debt collection, safety and security are of grave importance. Having tech ownership enables companies to have greater control over the flow of data.
Control: It is as simple – we can not control what we don’t own.
Consequences of lack of expertise in the area
Lack of tech ownership has many negative consequences. It slows down the entire process. Also, your vendor will not have control over the process because it is using many third-party integrations, and failure at one will cause the failure of the entire process.
In essence, the entire experience is compromised because of inferior performance if the vendor does not have ownership of the core tech stack. Every company uses integrations, they are the best ways to scale capabilities, but it should not be the case for the core tech stack.
Actionable Analytics and Dashboard
A unified view of the entire process and the ability to analyze and have actionable insights.
Why is it important?
Every conversation is a potential treasure trove of value. Companies must not waste such valuable resources and an ideal vendor must possess the capabilities to draw insights from data such as dispositions.
Look for capabilities such as bucketing dispositions into meaningful buckets, forwarding disputes to select departments, and more.
A dashboard to monitor the effectiveness of conversations is an essential feature. Also, analysis of AHT trends and more are a must.
Consequences of lack of expertise in the area
We can not improve that which we can not measure. Not having the capability to run analytics will impact business performance improvements and will lead to competitive losses.
Section 3: Implementation Guide
In this section of our guide, we’ve compiled a list of essentials to help your company properly onboard your chosen vendor and implement their Voice AI solution for debt collection.
Have the vendor sign an NDA (non-disclosure agreement)
In order for the DVA to be effective, you will have to share a lot of information for your vendor to be able to understand the consumer persona. Always sign an NDA before sending any documents or sensitive information.
Form a steering committee and assign Single Point of Contact (SPoC)
Ensure to have a focused approach to incorporate the Voice AI from the very beginning of the process. A steering committee can have a mix of expertise from technology to business, operations, and HR.
Always pilot and follow a lean approach in pilot
This is of serious importance. Lean means that your pilot should be undertaken in such a way that your organization gets disturbed in a minimal manner. Avoid unnecessary integrations that will increase the load and complexity of the pilot and can affect the results in a complex way. Also keeping it lean will minimize your and your team’s involvement so that your sunk cost in terms of time investment is low if the project goes south and doesn’t bear the fruits.
Pilot the biggest segments you handle
Going all out is not the best strategy here. Segment the portfolio you are handling in terms of volume and value. Prioritize 2-3 different segments for the pilot and provide representative call recordings for your vendor to understand the consumer persona. Also help your vendor with call dispositions i.e. different kind of flows your typical calls end up in, for example, percentage of calls that are wrong party, debt dispute, cease communication requests etc. This will help your vendor plan the development strategy.
The Voice AI agent will be as good as the information you feed it. It is essential that you provide to the vendor all the essential information, e.g. if you have 12 types of customers, then provide the audio recording of each type of customer. Failing that will result in poor conversation flows that are designed for only a few types of customers.
Additionally, the number of files shared is also important to help in the training of the voice agent. It is best if you share actual conversations in large volume so that it makes ML models better.
Review the call-flows
After reviewing the call recordings, your vendor should be able to come up with the conversational design, call flows, and scripts. Once your vendor is ready with conversation designs and flows, it is crucial that specialists from your organization review and help them refine the those. This step will have a lasting impact on DVA performance.
Stress-test the DVA before rolling out
A lot of people delegates the UAT (User Acceptance Test) tasks to junior resource or ignore all together. It’s the worst mistake to make especially in the debt collection space where one small mistake can be costly. It’s important to stress-test the DVA built by the vendor before deploying and rolling out for customers.
Pilot on as many consumers as you can
You can pilot on 100 calls per day for a week and decide to go for the full-scale implementation. However, for an AI solution, 100 calls are not a representative enough sample, especially for debt collection applications. In case of outbound, 80% of the call might go unanswered, so you will be left with 20% of the calls to test the bot. If you pilot on 20 calls per day for 5 days, you have piloted only on 100 calls, which might not be a bog enough datapoints to base your decisions on.
At Skit.ai we recommend at least 10,000 calls/day for about 4 weeks.
Calculate ROI for Go/No-Go decisions
You must run an ROI exercise, to understand what quantum of value the Voice AI solution will create for your company before moving any further.
This exercise must be done for one year period, ideally for 2-5 years. The variables involved are simple – call volume, cost of the human agent, cost of deploying voice agent, number of integrations, inbound/outbound, call complexity, and deployment type. Your vendor should be able to provide you with notional value creation/cost savings.
Value creation is not as simple:
Higher levels of voice automation will lead to higher augmentation of human agents – productivity, efficiency, and engagement
More top line as the same set of agents will now handle a larger number of accounts
Better recovery rates as the voice AI agent will be more persistent in collections
Better disposition capture for precise campaigns
Time-bound campaigns and 100% coverage on all accounts
You may choose to factor in direct and indirect benefits out of voice AI deployment.
A lot can go wrong here, so it’s better to be aware of the risks of lack of proper technology architecture planning.
Be clear about the call volumes you expect over the years because you need to assess the supporting tech infrastructure around it. Relevant integration, legacy telephony assessment, CRMs, gateways, and more must be assessed and optimized for minimum human interventions and sufficient to last the planned phase.
It must be duly noted that running a Voice AI solution is a process, a continuous journey filled with improvements and upgrades. In order to sustain and be further along the learning curve, training the Voice AI solution on new data is vital.
Upgrades and Training for Sustainable Competitive Advantage
New use cases, business verticals, customer regulations, and more — we live in a dynamic world, and constant effort to innovate the voice solution are essential for being at the top of the game and beating the competition.
It is essential to assess a voice solution in granular detail before moving forward with it. We hope this guide will help you in your buying journey.
For more information and a free demo, you can schedule a call with one of our collections experts. We’ll be happy to help!