Let’s begin by addressing the elephant in the room—the collection rates have dramatically fallen in the last decade. The State of Debt Collection 2020 Report reveals that in 2010, U.S. businesses placed $150 billion in debt with collection agencies, of which they could collect just USD 40 billion. On delinquent debt, the collection rates have declined to 20% (industry average), a decrease from 30% as recorded a few decades ago.
Anyone from the debt collection space would be cognizant that the industry has been under pressure from all fronts—inflationary pressures, agent attrition further fuelled by the great resignation and increasingly stringent regulations after Reg. F, and economic downturn.
Never before was the need for automation direr than it is in 2022!
What is Voice Automation for Debt Collection Companies?
Before we go into the transformative role Voice AI can play in the debt collection industry, let’s understand voice automation.
Voice Automation –Refers to the automation of voice calls, decoupled from the assistance of a human agent. This means the capability to answer customer queries with the machine, striking intelligent, multi-turn conversations.
Consider this scenario where an AI-enabled Digital Voice Agent interacts with a customer and facilitates an on-call payment.
The demo is a perfect example of how an intelligent Voice Agent can help consumers willing to pay and facilitate a quick payment with remarkable ease.
Outbound Call Automation: A Digital Voice Agent can call consumers and establish the right party contact, remind them about the due date, capture their dispositions, raise dispute requests, accept and schedule a payment on call, or help them negotiate, and arrange a payment plan for a better recovery.
Automating Tier-1 Inbound Consumer Queries: The Voice AI agent can answer tier-1 calls, which are as much as 70% of total inbound calls, without the need for a human agent. Also, even when a Voice AI agent calls customers, it can answer all basic questions and handle tier-1 queries discussed in the outbound section above.
Hitherto, only IVRs have played a limited role in increasing the containment rate with the self-service option. IVR’s effectiveness can be debated, especially when reports have revealed that it plays a role in decreasing customer experience. The problem with IVR technology is that they have reached the culmination of what it can do for debt collection agencies. It is time to move beyond IVRs, especially when tech advancements have brought us to the sweet spot of cost-effective incorporation of AI-enabled solutions such as Voice AI.
Addressing the Elephant in the Room: Core Debt Collection Challenges
Debt collection companies face these core problems:
Dormant Files: Every debt collection agency sits on a pile of inactive accounts, as high as two-thirds of their portfolio, that they can not process because of its economic infeasibility. This is a sour point, and they are looking for tech solutions that can help them address this pain point.
Non-Revenue Generating Calls:
Wrong Party: Proportions of wrong party contacts vary depending upon many factors, such as the age of debt, but it can be as high as 70-80%. All the calls made by human agents that turn out to be wrong contact numbers are pure costs with no return.
Dispute: The next big chunk of the volume of calls is usually when a consumer fails to recognize the debt or disagrees with the outstanding amount. The regulations require debt collectors to raise the dispute request to investigate the debt further and provide relevant information to the consumers before any collection activities. Those calls where debt is disputed by the consumer or asked for more details of the debt eventually turn out to be a pure cost activity.
Cease-and-Desist: Be it inbound or outbound, there is always a set of consumers who ask agencies to stop all collection communication with or without any good reason. There is no real scope of value creation by a human agent in this case as well.
Attorney Representation: Often, the consumers ask to contact their attorney and not to approach them directly. All agents do in this case is update the system to not reach out to these sets of consumers as required by regulations.
Call Back Requests: More often than not, the consumers ask the agent to call some other time, in some cases beyond the working hours of the agency.
Right-Party Contact (RPC) Cycle: Traditionally, a human agent will call consumers to establish if the contact number is correct. Any debt collection agency has so many files to process that they can only call a fraction of them within a time frame, and take long to cover all consumers, if at all. The shorter the cycle, the larger would be the scope to improve recovery.
Propensity Based File Segmentation: Ideally, a debt collection agency would like to segment their portfolio into different buckets based on the consumer propensity to pay. But sadly, with a large number of files, it is challenging to do this within a limited time frame, if at all.
Agent Bandwidth Optimization: Agents are the most precious organizational resource and their time/bandwidth optimization is an utmost priority for them. But in absence of RPC and disposition capture, it is near impossible to optimize their time and effort.
Service Level Maximization: The number of calls a debt collector addresses per agent per hour is vital for enhancing operational performance.
Compliance: The regulations have become increasingly stringent; this has two implications:
The penalties and fines are levied at instances of breach of regulations. They are typically bearable expenses, though they affect profitability.
Lawsuits filed by consumers: They do real damage as they consume time as well as cost, and are typically much higher than government fines and penalties.
With the coming of Reg. F, a new conversation has begun on the compliance of new-age technologies. Being AI-enabled and capable of striking an intelligent multi-turn conversation, Voice AI finds itself better placed to meet compliance. (read more about it in this Voice AI compliance white paper by Mike Frost and Skit.ai).
Voice AI is based on AI/ML, Automatic Speech Recognition (ASR), Spoken Language Understanding (SLU), Text-to-Speech (TTS) technologies, and more. A confluence of such great technologies enables Voice AI to understand the spoken word and respond to it most intelligently. Here is the gist of how a Voice AI Agent can create value for debt collection agencies:
Segregating Right and Wrong Party Contacts:
With the great capability for executing thousands of concurrent calls, Voice AI can call and establish the right or wrong parties in a matter of minutes, for a significant portion of files. No technology has been able to accomplish this except Voice AI.
Value Creation: At a fraction of the cost, a debt collection company can identify if the contact is right or wrong without involving their human agents. Time and cost advantages can help them improve performance in a big way.
Enabling File Segmentation by Capturing Disposition:
Classifying customers into 4-5 different segments solves a lot of problems for the collection agency. A Voice AI agent can call thousands of customers and, based on dispositions, can segment millions of accounts into various buckets such as consumers who disputed the debt, consumers with cease-and-desist requests, consumers with attorney representation, consumers who agreed to a payment plan, etc.
Based on this segmentation, accounts can be allocated to respective specialists and departments for further processing.
Value Creation: Only after capturing the disposition for the entire portfolio, the company will be able to draft an optimal strategy and optimize the time spent by their agents.
Since the coming of Reg. F, the compliance has become difficult to keep and the corresponding implication of its breach is getting higher. With large portfolios, it is difficult for agents to execute their follow-ups with perfection.
Mandatory rules such as the 7/7/7 rule, along with Mini Miranda, use of decorous language, and more, make it difficult for the human agent to always stick to the script especially when a majority of calls are repetitive and low-value.
Value Creation: Voice AI agent, once trained for compliance will always stick to the script, and use the right language. It will also stick to the schedules of follow-ups increasing the probability of conversion as well as saving the company thousands of dollars in fines and lawsuits. This also increases the speed of the company processing its portfolios.
Value Out of Non-Revenue Generating Calls:
Voice AI, at a fraction of the cost – 1/6th, can process these calls (mentioned in the above section) and help human agents avoid these and focus on value-creating calls.
Voice AI, with its consummate coverage of debt portfolio, can help debt collection companies have a more precise understanding of their consumers and devise better strategies. Below is a graph that depicts VaR and the ideal file segmentation and corresponding strategy.
Strategizing with Voice AI
Age of Debt and Voice AI: A debt collector will typically have a mixed portfolio with debt lying in various age brackets. Typically the older the debt, the lower the probability of recovery, and hence Voice AI is more suited to engage with these accounts.
It must be noted here that the segmentation is only possible after the Voice AI Agent covers the entire portfolio to uncover consumers’ propensity to pay.
Capturing Propensity to Pay: Once the Voice AI Agent has captured the disposition of the consumer, a debt collector can then segment or classify it and assign it according to the disposition.
Strategizing for Value at Risk: Since Voice AI costs one-sixth of a human agent, and is as effective for simpler conversations, it is ideal for Voice AI agents to address these accounts and follow up meticulously.
High Willingness to Pay (WTP) – High Value: When the willingness to pay is high, the voice AI agent can call promptly and facilitate on-call payments or remind them to pay. Debt collectors have been able to achieve a high degree of success in this category.
High and Low Willingness to Pay (WTP) – Low Value: This segment of the portfolio is prohibitively costly for human agents to process because of its low value, making it ideal for the voice AI agent to process it and help prop up recovery rates.
Low Willingness to Pay (WTP) – High Value: High value and low willingness to pay makes this segment of consumers ideal for human expertise. Human agents can deploy their cognitive skills to convince and help them pay.
Optimizing Campaigns:Armed with new insights on consumer behavior, debt collectors can refine and optimize their campaign strategy. An ideal mix of Voice AI, human agents, and SMS/emails, can make a difference.
Impressive Contact Center Outcomes with Voice AI
No, the capability of Voice AI is not just based on conviction and hope, there are solid stats to second every value proposition.
It must be noted that the higher volume that Voice AI Agent handles, the greater the scope of value creation. This is necessary if a debt collector wants to strategize based on consumer disposition.
Here are a few outcomes that the debt collectors as well as other contact centers have achieved with Voice AI:
Up to 38% improvement in service levels
Nearly 50% decrease in operational costs
Up to 70% automation of your consumer support efforts
Reduction of 40% in average handle time
There are multiple challenges from diverse fronts plaguing the debt collection companies. They can break the status quo and make the necessary changes on many fronts such as cost, performance, recovery rates, compliance, and speed.
Voice AI technology has been successful in value creation for debt collection companies. However, it takes an expert vendor and meticulous execution to achieve desired results.
To further understand the nuance of Voice AI and the scope of transformative value it can create for your business please – Book a Quick Appointment.
Artificial Intelligence (AI) has disrupted almost every industry in one or the other way, and ARM industry is no exception. However, due to stringent regulatory restrictions in the industry, leaders are being cautious about implementing one.
This paper provides a compliance review of the Voice technologies, especially AI powered virtual/Digital Voice Agents. The intention is to briefly introduce the technology followed by statutory framework to analyze the technology for compliance.
I have attempted to provide the relevant cases to establish my point of view from legal perspective. Also included in the paper is the list of things one should consider before implementing such solution.
It’s imperative that ARM leaders should try to adopt such technologies, though cautiously, in order to stay in the business in this era of labor arbitrage, inflation, and a generational shift in communication preferences.
This whitepaper is written in collaboration with Skit.ai. Skit.ai is an Augmented Voice Intelligence Platform that helps businesses modernize their contact centers and customer experience by automating and improving voice communications at scale. Skit.ai is a vertical voice AI company, which means they bring deep domain expertise and business knowledge along with advanced technical know-how.
Skit.ai is the winner of CCW Excellence Award for Disruptive Technology of the Year 2022. Skit.ai was also named as a Cool Vendor in Gartner Cool Vendors in Conversational and NLT Widen Use Cases, Domain Knowledge and Dialect Support in the year 2021.
Disclaimer: The information in this whitepaper is not intended to be legal advice and may not be used as legal advice. Legal advice must be tailored to the specific circumstances of each case. Every effort has been made to assure that this information is up to date as of the date of publication. It is not intended to be a full and exhaustive explanation of the law in any area, nor should it be used to replace the advice of your own legal counsel.
Introduction of Technology and Background
As a 20-year veteran of the ARM industry, I have firsthand experience as a debt collection agency shareholder and general counsel, I am the named inventor of three patent or patent-pending products that are or will be available in this ARM industry, and I currently provide legal representation of various debt collection agencies for defense litigation, defense of regulatory investigations and preparedness efforts for compliance. In these multiple capacities, I often have and do continually find myself evaluating new and emerging technologies. The evaluation of these emerging technologies is often premised upon a regulatory or statutory challenge that is impeding the needs of the industry.
In this whitepaper, I will address an emerging technology that is fairly new to the ARM industry, Digital Virtual Agent (DVA) technology. DVA technology is not an entirely new concept for ARM as we have utilized Interactive Voice Response (IVR) technology for several years. Both DVA and IVR technologies have regulatory challenges under the Telephone Consumer Protection Act (TCPA), specifically the restrictions on prerecorded messages and artificial voice calls that are placed to cellular telephones. The TCPA statutory construction is predicated on extremely dated technology. Technology that at the time of the statutory construction of the TCPA was primarily focused on landline telephones, pagers, and per minute charges for long distance calls or per minute cellular telephone plans. While the statutory language is predicated on expired technology that in and of itself does not alleviate the requirement for compliance. Instead, it creates the requirement of necessary workarounds to ensure compliance with the statute.
47 U.S.C. § 227 (b)(1)(A) states, in relevant part, as follows: (1) PROHIBITIONS. It shall be unlawful for any person within the United States, or any person outside the United States if the recipient is within the United States – (A) to make a call (other than a call made for emergency purposes or made with the prior express consent of the called party) using and automatic telephone dialing system or an artificial voice or prerecorded voice – (iii) to any telephone number assigned to a paging service, cellular telephone service, specialized mobile radio service, or other radio common carrier service, or any service for which the called party is charged for the call.
The purpose of the TCPA at its inception was to avoid tying up emergency lines or saturating new and growing wireless networks. At that time, there were only about seven million cellular subscribers. Cellular telephone plans were expensive costing around $1 per minute of use. In seeking to curb “robocalls,” and the extreme costs associated with those calls to cellular telephones, Congress was attempting to regulate certain broadly placed calls that made use of a specific type of equipment that was prevalent in the 1990’s, with no connection or relationship between the calling party and the recipient. The recipient, if the call was answered, were charged significant fees for just answering the calls. Fast forward several years and the Courts interpreted these rules very broadly to include text messaging. The Courts’ interpretation brought into question communications, both calls and text messages, for prescriptions notifications, security alerts, collection calls, appointment reminders and the like. The Courts allowed the TCPA guiderails to stretch to businesses with existing business relationships which created class action liability in the tens to hundreds of millions of dollars in liability. In many situations, consumers not only desired these calls but were not negatively impacted by the restrictions as they failed to be informed of appointment or past due obligations.
Fast forward again to 2021 where the Supreme Court of the United States (SCOTUS) via Facebook, Inc. v. Duguid, 592 U.S. ___, 141 S. Ct. 1163, 209 L.Ed.2d 272 (2021)resolved a split amongst the circuit courts and rejected the expansive definition of an ATDS, provided primarily by the U.S. Court of Appeals for the Ninth Circuit. The Ninth Circuit rulings essentially considered every cellular telephone in America to have the capacity to become an ATDS. While there is still potential liability regarding calls without express prior consent or without human intervention, the courts have seen fewer cases than prior to the Facebook decision. What Facebook did not assist with is the use of prerecorded messages or calls that utilize artificial voice. Instead, the SCOTUS utilized a textualist review of the statute to determine that in order to qualify as an ATDS under the TCPA that a dialing system must have “capacity to randomly or sequentially store or dial phone numbers.” This completely changed the direction of several courts which were taking individual approaches to consider what constituted “capacity” and often focused specifically on the term “store” to create an expansive definition of an ATDS.
The Federal Communications Commission (FCC) is the agency empowered to issue rules and regulations regarding the TCPA. The TCPA prohibits calls to a cellular telephone using and “automatic telephone dialing system” or an “artificial or prerecorded voice” without first obtaining express consent from the called party. In the early 1990s when the TCPA was enacted, these restrictions were a response to a rise in consumer complaints regarding telemarketing calls placed by systems that utilized sequential number generation for outbound telephone calls that play pre-recorded messages.
Congress enacted the legislation and empowered the FCC to enforce it. The FCC through a handful of declaratory rulings in 2003, 2008 and 2015 expanded the definition of an ATDS under the TCPA to include all predicative dialers and essentially anything that had the capacity to predictively dial or dial from a list of stored telephone numbers.
In ACA International, Inc. v. FCC, 885 F.3d 687 (D.C. Cir. 2018), the D. C. Circuit court reviewed challenges to the FCC’s declaratory orders, namely:
Its definition of an ATDS;
The reasonableness of the one-call “safe harbor” for calls placed to reassigned numbers;
Revocation of consent; and
The FCC’s exemption for certain healthcare-related calls.
The D.C. Circuit court set aside the FCC’s interpretation of ATDS and the FCC’s treatment of reassigned numbers as a whole and upheld the FCC’s 2015 ruling that a called party may revoke consent at any time and through any reasonable means as well as the narrow exemption for certain healthcare-related debt. Thankfully, the Facebook decision years later provided additional clarity. However, that clarity has been again determined by federal district courts throughout the country with mixed results.
Courts have continued to reject what has been commonly referred to as the “Footnote 7” argument – referring to Footnote 7 in the Facebook decision, where SCOTUS suggested in dicta that randomly or sequentially selecting numbers from a predetermined list might qualify as an ATDS – where Courts are focused on the generation of the numbers and not the selection of the number. See generally, Laccinole v. Navient Solutions, LLC, 2022 WL 656167 (D. R.I. Mar. 4, 2022); Montanez v. Future Vision Brain Bank, LLC, 2021 WL 1697928 (D. Colo. Apr. 29, 2021); McEwen v. Nat’l Rifle Ass’n of Am., 2021 WL 5999274 (D. Me. Apr. 14, 2021); Carl v. First National Bank of Omaha, 2021 WL 2444162 (D. Me. June 15, 2021); Barton v. Temescal Wellness, LLC, 2021 WL 2143553 (D. Mass. May 26, 2021).
So, where are we today? We are still in a world where we need to consider capacity, storage of phones and other variables in how the equipment used may or may not be defined as an ATDS under the TCPA.
Interactive Voice Response (IVR)
IVR is an automated phone system technology that allows incoming callers to access information via a voice response system of prerecorded voice prompts and touch-tones without having to speak to an agent. It also provides menu options via touch-tone keypad selection or speech recognition to have a call routed to specific departments or specialists. IVRs provide communications with consumers through speech synthesis based on a series of voice prompts that are pre-programmed by the caller. IVR technology provides an efficient means for consumers to self-service an account, make a payment, identify that they are the correct or incorrect party called, request information, or identify information about their account in order to be routed to the proper call center agent.
IVR technology is useful when built to provide pre-determined, optional responses by consumers, like Press 1 to reach the receptionist, Press 2 to reach a manager, Press 3 to be removed from further call attempts from this company. It allows an outbound call to provide a series of options to a consumer to select from to route a call or provide consumers the ability to respond to a predetermined question and also allows companies to provide pre-recorded disclosures based on federal, state, or local laws, rules, or ordinances. IVR systems have provided for increased customer satisfaction rating and have improved contact center operations and key performance indicators. During peak times of high call volumes, an effective IVR system can reduce consumer wait times by utilizing self-services tasks to answer routine questions. IVR technology is also available any time of the day or night, depending on the consumers preference and work schedules it makes information readily available for consumers at times they otherwise would not be available.
Unlike the IVR technology, DVA technology is not prerecorded or scripted messaging. It is highly conversational technology that has the ability to learn from each interaction. DVA is a software agent that can perform tasks or services for an individual based on commands or questions. The term “voicebot” is sometimes used in place of DVA. Voicebot or DVAs are able to interpret human speech and respond based on machine learning assessments and information that is accessible by the technology. DVAs have become very widely used and accepted by consumers. Many homes now utilize DVA styled technology through products like Google Assistant, Apple Siri, and Amazon’s Alexa. These products are able to verbally accept and respond to questions presented by humans. DVA’s are similarly being used in business applications as some consumers prefer to correspond with DVA rather than humans.
The perceived values of DVA technology over human-to-human communication are:
Speed: Almost everyone has experienced long wait time while calling up a call or contact center mainly due to limilited support staff. On the other hand, unlike humans, machines can be scaled up almost instantly in case of surge in call volumes and can serve every caller without zero wait time. Moreover, machines can perform actions much faster than humans, for instance machine can look up for information from the database or send documents or raising downstream tickets faster than humans.
Convenience: Most DVA or voicebot technology is available for consumer use 24 hours a day, seven days a week. This allows consumers to communicate at a time and place that is convenient for consumers – which is also a requirement under federal statute for certain ARM industry activities. Additionally, machines can communicate with humans without violating laws and judging customers in their financial crisis.
The TCPA is the most significant compliance consideration for outbound dialing, including DVA technology. As previously discussed, the TCPA prohibits calls to cellular telephones using an ATDS or an “artificial or prerecorded voice,” without the prior express consent of the called party. 47 U.S.C. § 227(b)(1)(A)(iii). The TCPA also prohibits “using an artificial or prerecorded voice to deliver a message” to residential landlines. 47 U.S.C. § 227(b)(1)(B). However, commercial calls that do not constitute telemarketing or advertisements are exempt from the residential landline restrictions pursuant to FCC classification. 47 U.S.C. § 227(b)(2)(B); Rules and Regulations Implementing the Telephone Consumer Protection Act of 1991, CC Docket No. 92-90, Report and Order, 7 FCC Rcd. 8752, 8773 (1992). Thus, calls where there is an existing business relationship or where the call is not for telemarketing or advertisement purposes, then the TCPA restrictions are limited to calls to cellular telephones.
As previously discussed, Facebook provides a framework in which to consider risks related to outbound telephone calls. The DVA itself does not have the capacity to randomly or sequentially store or dial phone numbers and therefore does not constitute an ATDS. However, a DVA is not the system or mechanism generating the outbound call on its own. Thus, compliance considerations still require a review and of dialing technology to ensure the systems and infrastructure is not considered an ATDS or that the agency’sies policy has a solid consent defense, which we will discuss later. The other important analysis is that of artificial or prerecorded voice.
The TCPA does not provide a definition of artificial or prerecorded voice. One Court has utilized a dictionary definition of “prerecorded” meaning “recorded in advance.” See Bakov v. Consolidated World Travel, Inc., 2019 WL 6699188 (N.D. Ill., Dec. 9, 2019). Other Courts have reviewed pre-recorded considering the plain language and meaning but failed to provide a definition. See Lardner v. Diversified Consultants, Inc., 17 F.Supp.3d 1215 (S.D. Fla. 2014); Braver v. NorthStar Alarm Servs., LLC, 2019 WL 3028651 (W.D. Oka. July 16, 2019). The definition of artificial has received less attention from the plaintiff’s bar than prerecorded messages or ATDS allegations. Thus, we turn to the legislative intent and FCC interpretations. In 1993, just a few years after the enactment of the TCPA, the FCC commented on the purpose of prerecorded messages and defended the TCPA’s constitutionality. See Moser v. F.C.C., 1993 WL 13101270 (9th Cir. 1993). The FCC further identified that pre-recorded announcements are different from human interchange noting that machines cannot ascertain the propriety or proceeding with a message and that live calls include a dialogue rather than an announcement. Id. at *20.
Pursuant to the legislative intent of Congress in drafting the TCPA and solving the problems associated with IVR outbound dialing in the early 1990’s and the fact that machine learning and artificial intelligence-based DVA technology developed post-enactment of the TCPA, Congress intent was not to ban “live” calls to consumers. Instead, Congressional intent shows that the TCPA was enacted to discontinue the use of artificial or pre-recorded voice systems that were considered a nuisance or invasion of privacy by forcing consumers through a decision tree-based script which often led consumers in never-ending systemic circles. DVA technology is uniquely distinguished from the IVR counterparts as it utilizes machine learning and artificial intelligence that allows the system to make decisions based on voice recognition and continually learn from ongoing interactions.
Artificial Intelligence (AI) is essentially human-like learning and communication behaviors by a machine or system. AI is classified in two categories, functionality, and capability. Functionally AI has no memory and does not have the ability to learn from past actions. Capability, by adding memory and past information, AI can make better decisions. Items like GPS location apps are good examples for AI.
Machine learning is when software is able to successfully predict and react to unfolding scenarios based on previous outcomes. The systems develop patterns, predict, and learn based on disposition data. It can make adjustments to prior outputs without being programmed to do so, therefore is truly more interactive.
Understanding the technological differences between an outbound IVR and DVA are significantly important to the assessment of risk in the use of this new technology in the ARM space. As previously mentioned, there are significant differences in these two types of technologies. The main difference in evaluating risk is what constitutes a pre-recorded message and what constitutes an artificial voice. Let’s begin with pre-recorded messages. Congressional intent on a pre-recorded message was simple – to avoid calls to a consumer’s cellular telephone and leaving a pre-recorded message on a consumer’s voice mail. The DVA does not utilize pre-recorded messages for voice mail messaging, nor does it play a series of pre-recorded scripts to provide consumers with options to select one of several predetermined paths to additional questions. DVA technology corresponds with a consumer based on that consumer’s statements, questions, or responses. It then utilizes real-time machine learning to determine how to respond to the consumer’s inquiry, no different than a human agent in a call center. Systems, like people, will sometimes be unable to provide an answer to a specific question and may transfer the call to another person or system to respond accordingly in an attempt to provide the requested service to the consumer. The ability of the DVA system to interact with a human in real-time and correlate responses to questions posed by a consumer and not pre-disposed by the company, is a major differentiation in the technology and the applicability of statutory constraints provided in the TPCA.
In the event your risk analysis, in-part due to the limited judicial interpretation of the use of DVA technology, does not meet your risk tolerance levels, don’t stop there. Take a look at other compliance considerations, like prior express consent, human intervention or peer-to-peer solutions that may assist in the analysis to find a compliance strategy to comply with the TCPA. Prior express consent is a viable and solid defense to an alleged violation of the TCPA for the use of outbound DVA or IVR technology.
While pre-recorded messaging and artificial voice are differentiated from ATDS analysis in the TCPA, prior express consent (PEC) is an absolute defense to all three arguments. The phrase “prior express consent” is not defined under the TCPA or FCC regulations. However, in 1992, the FCC addressed the issue of PEC in the context of calling wireless number by stating:
Persons who knowingly release their phone numbers to a caller have in effect given their invitation or permission to be called at the number which they have given, absent instructions to the contrary. However, if a caller’s number is “captured” by a caller ID or an ANI device without notice to the residential telephone subscriber, the caller cannot be considered to have given an invitation or permission to receive autodialer or prerecorded voice message calls.
A process analysis is necessary to ensure that the prior express consent is documented properly, saved, and accessible in the event your company is subject to a TCPA lawsuit or regulatory review. A few considerations for analyzing your prior express consent policy:
Prior express consent can be obtained either directly from the consumer by the agency or passed through to the agency from the creditor. Furthermore, the 9th Circuit Court of Appeals states in summation that the TCPA requires “that prior express consent must have been given either orally or in writing.” Loyhayem v. Fraser Financial and Insurance Services, Inc., No. 2:20-cv-00894-MWF-JEM (9th Cir. 2021). While pass-through consent has been determined by various courts to pass muster under the TCPA, direct consent is obviously better for several reasons.
First, pass-through consent is obtained at the time of service. Depending on the type of service provided a consumer could argue that the consent was obtained under duress or that the required provisions made the agreement a contract of adhesion, meaning the consumer had no choice but to accept the terms without condition. Depending on the type of service obtained those arguments may have merit.
Second, the language in the underlying consumer agreements must contain the proper consents (e.g., calls initiated through an automated telephone dialing system; calls initiated with a pre-recorded or artificial voice). Agencies may be able to influence the creditors consent language in the underlying consumer agreement, but they do not control language modifications over the life of the creditor-consumer relationship which often change through electronic updates to consumer agreements.
Third, underlying consumer agreements are stored and maintained by the creditor. As a third-party provider of collection or care services, the agency is dependent not only on the underlying consumer consent language but also the manner in which the creditor stores, maintains, and reproduces the documentation to prove the consumer provided prior express consent. Fourth, considerations of time between the contractual agreement and the outbound attempt are important as reassigned numbers have created liability for outbound calls. See Soppet v. Enhanced Recovery Co, LLC, 679 F.3d 637 (7th Cir. 2012).
The Consumer Financial Protection Bureau (CFPB) addressed this concern around time in Regulation F, 12 CFR Part 1006 (November 31, 2020). Under Regulation F, it identified concerns regarding reassigned phone numbers in their recommendations regarding text message communications suggesting that agencies consider the use of the Federal Trade Commissions (FTC) reassigned number database scrub anytime more than 60 days has elapsed since the last contact with a consumer. See Regulation F, Section 1006.6(d)(5). While Reg F provides this recommendation and offer for a safe harbor to agencies that follow the recommendation, it is not a rule or requirement but instead an optional compliance consideration that affords a safe harbor or bona fide error defense under the FDCPA. Scrub processes for reassigned phone numbers likely will provide another layer of defense and compliance to an outbound DVA or IVR based call. Finally, consumers should be afforded a simple and clear way to revoke consent or opt-out of future IVR or DVA based call attempts. One way to provide the consumer an opt-out option is to provide it in the IVR or DVA, on a consumer facing website, or via toll free phone number. Agencies should have systemic processes that are regularly audited to consumer revocations where consent is the only or primary defense.
Around 2008-2010, the ARM industry experienced a rash of TCPA litigation claims premised on the use of an ATDS for outbound calls. Technology was developed to overcome these restrictions that required human-intervention prior to an outbound dial regardless of the type of dialing systems that was utilized by the calling party. [Insert MCA Patent reference]. This technology was designed to allow for continued efficiencies in call center routing, reporting and compliance which was built into dialing systems over the prior years.
The ARM industry commonly has and continues to lean on dialing system infrastructure to maintain a rules-based process to ensure compliance with various state and federal regulations that restrict the time and number of calls to consumers in a given period of time. Human intervention is conceptually very simple – it requires a human to click a button or dial the ten key number prior to call initiation from the dialing system. The first case to address this technology was Strauss v. CBE Grp., Inc., 2016 U.S. Dist. LEXIS 45085 (S.D. Fla. Mar. 28, 2016) ruling that human intervention, such as through the click of a button, the system does not qualify as an autodialer under the TCPA. This instrumental rule blazed the litigation trail and provided a path to the 10+ additional federal court rulings throughout the country. This additional compliance consideration provides protection against the allegation of the illegal use of an ATDS. However, it does not provide any real protection for (or at least has not been addressed by the Courts) in regard to pre-recorded or artificial voice allegations.
Peer-to-Peer (P2P) technology is very similar to human-intervention technology and is primarily used today in outbound text messaging campaigns. P2P is similar to human-intervention prior to an outbound phone call with a few differentiations. First, P2P was built for outbound text messaging but could be deployed on outbound phone call attempts as well – although I have not seen the technology utilized in this manner, yet.
Human-intervention for outbound dialing is customarily provided by a human in a call center environment and oftentimes is generated off-shore. The human intervenes in the dialing system to generate the outbound dial by pushing a button (key on a keyboard, computer mouse, or similar device). P2P processes are built into the texting process and its application based. The application sends a message to employees or contractors with a message to log into the P2P system. The employee or contractor then presses a button on their cellular device, iPad, computer, or other electronic device to initiate the text to be sent to the carrier or aggregator for delivery to the consumer.
The efficiency of P2P is better than human-intervention and has also been reviewed by the FCC, wherein the FCC opined that a P2P process is not an ATDS. See FCC Declaratory Ruling, In the Matter of Rules and Regulations Implementing the Telephone Consumer Protection Act of 1991, P2P Alliance Petition for Clarification, GC Docket No. 02-278, DA 20-670 (June 25, 2020). P2P provides a very solid defense to an allegation of that an ATDS was illegally used to generate the outbound call or text message but like human intervention has not been vetted by the Courts as it relates to artificial or prerecording voice allegations.
So, why even discuss P2P for IVR or DVA technology if it does not protect against the TCPA concerns regarding artificial or prerecorded voice? Consent. P2P technology provides ARM companies an affordable and effective means in obtaining direct consumer consent prior to the use of DVA or IVR technologies. Companies today have the ability to send documents to consumers via text messages through P2P platforms that can be signed electronically and returned to the sender for consent capture. Once consent is obtained (either direct consent or pass-through consent), then the outbound DVA and IVR options to communicate with consumers become extremely viable and significantly defensible. Consent is a must for a pre-recorded message defense and human intervention/P2P is a must for defense against an ATDS allegation.
As previously addressed, there are several different compliance considerations to evaluate and determine what to deploy as internal business strategies and to document in policies and procedures. The type of systems used drives the risk analysis. Individual risk tolerance will determine which compliance considerations to implement or maybe how to develop multiple layers of protection utilizing some, all or more options than those compliance considerations discussed in this article. What I believe to be true is doing nothing and not utilizing these technologies is not a good long-term plan or option.
As an industry and in society in general, we continue to experience a shift in communication modalities in society. We are also facing labor arbitrage, inflation, and a generational shift in communication preferences. At the end of the day, finding a preferred communication method is key to right party contacts and a right party contact is the key to success in the ARM industry. Thus, ARM companies must consider generational shifts, labor arbitrage and current financial impacts.
The current workforce and debtor community is comprised primarily of Millennials and Generation Z. These generations communicate primarily by electronic means and prefer to speak to a computer or artificial voice rather than a human call center agent.
Furthermore, we are experiencing inflationary pressures and worker shortages, due its large part to the retirement of the baby boomers, which continues to drive hourly rates to unprecedented, and, at some point in the near future, to unmanageable levels at current fee rates.
Over the years, the ARM industry solved or attempted to solve the labor concerns with near-shore or off-shore solutions that again utilize human’s doing similar work but at lower labor rates and lower overall costs. While labor concerns continue to exist and likely always will, the more impactful change is the shift in consumer communication preferences. You can staff call centers all day long, but if people will not pick up the phone and communicate with a live representative then the model has to change.
The technological advancements and shift in communications preferences make the utilization of this technology paramount to the continued success of any ARM business into the future.
The world and Indian economic growth find themselves precariously placed in 2022, with bleak economic data raising concerns. People are reeling under the increasing cost of living, and rising defaults on loans are beginning to be a worrying trend. The rise in default rates was seen in every segment, without exception, with Loan Against Property (LAP) having the highest default rate at 4.14% in November 2021; loans due past 90 days in the two-wheeler segment are also high at 3.64%, up 140 basis points, while consumer durable loan delinquencies are the third highest. Delinquencies in the credit card segment have eased sharply by 77 basis points to 2.22% (data from credit monitoring agency Transunion Cibil). Also, the spike in fund disbursement will increase the asset size of NBFCs, while the GNPA rate will also increase significantly to 6-8%.
On account of inflationary pressures, and a slowdown in the growth of fresh credit, the situation is becoming challenging for companies in the debt collection space. To maintain profitability, NBFCs are faced with the dual challenge of improving their performance, while improving cost-efficiency at the same time. This calls for a different approach, leveraging technology such as Voice AI to automate a significant portion of their outbound customer reach outs.
In this blog, we shall explore the role of Voice AI as the ‘agent of change’ in the growing debt collection space, and why the shift to Voice AI is one of the most profitable moves NBFCs and debt collection agencies can make in 2022.
Voice AI Is Redefining the Future of Debt Collection
Customer experiences are critical to the brand and business performance agree 73 percent of the business leaders, suggests a study by the Harvard Business Review. The global proliferation of voice-led technologies and voice-assisted interfaces built on AI-based NLP across industries have set massive expectations in the way customers prefer digital interactions and engagements. IVRs have proven to decrease CX, and bulk robocalls have proved ineffective. This is of significance in debt recovery, because as companies lose time, the probability of recovery dwindles.
On the other hand, AI-enabled voice agents are capable of engaging in meaningful conversation that runs beyond generic reminders by gathering insights and feedback that may facilitate on-call payment, rescheduling, and dispute resolution.
Money talks are uncomfortable, Voice AI exactly helps debt collection agencies achieve that, allowing human/machine partnership, the future of intelligent work.
Human-Machine Partnership: Voice AI platform built specifically for the debt collections industry also helps automate voice conversations while enabling context transfer capabilities from across modalities (text, chat, email, and speech), empowering the agents to operate without burnouts whenever call volumes peak. Automation of cognitively routine work also allows more time for contact center agents to prioritize their bandwidth and use it for solving complex challenges without the need to upscale the team.
All in all, integrating Voice AI can help create three ideal scenarios—NBFCs can improve their Collection Efficiency Ratio while reducing the cost and even improving customer experience!
Skit.ai’s Augmented Voice Intelligence in Action
Challenges Facing Indian Debt Collections Companies (NBFCs)
These are challenging times for NBFCs trying to improve their recovery rate. As CXOs look forward to improving the performance of the debt collection agencies here are the core problems they are trying to solve:
Intensifying competition is putting pressure on profitability
Low Collection Efficiency Ratio
High Cost of Collections
Slower campaigns and limited customer coverage
Before we deep dive into how Voice AI can solve all the major challenges, let’s first look at the definition of Collection Efficiency Ratio.
Understanding the Performance of a Debt Collection Agency or an NBFC
The entire performance of a collection agency can be expressed to a large extent by these metrics:
Collection Efficiency Ratio
The collection efficiency ratio is a measure of how well the collection department collects debt. It’s essentially a way to determine the effectiveness of the collections team.
The collection efficiency ratio is calculated as a percentage that depicts the proportion of debt collection achieved out of the total portfolio. The higher the percentage, the better the debt collection performance of the company.
How to Calculate the Collection Efficiency Ratio
The total collectible amount for month X – This includes the overdue at the start of the month as well as all the due dates throughout the remainder of the month.
Remaining recovery amount for month X – This is the amount remaining on a specific day that the team failed to collect.
A higher percentage depicts greater success in the collection of debt, ie., better debt recovery.
How Important is Collections Efficiency Ratio for NBFCs?
The collection efficiency ratio gives an overall monetary recovery status. Irrespective of the number of accounts recovered, at the end of the day, the Rupee value counts.
It is also a good measure because it gives a clear picture of value at risk (VaR) which is the most important thing to monitor for a debt collection agency.
Age at List (AAL)
Time is important when it comes to debt collection. If your account is 7 months old, its recovery rate drops to 50%. After 12 months, it drops to only 25%.
Therefore, Age-at-List is one of the most important KPIs in the collection. This is the average number of days your account has been in expired status. AAL provides a general overview of the collection cycle. This is an excellent comparison indicator between collection agencies and the industry.
Successful agencies are aiming for a low AAL. A high AAL indicates that the agency needs to be more effective in debt collection. However, AAL tends to fluctuate. Therefore, you need to review the data for about a year to gain valuable insights.
The Digital Voice Agent can be trained to pursue B0 and B1 buckets and will be very effective with its precise regime to convert the default accounts. This will lower the age of debt and improve the performance of the company.
RPC rate (Right Party Contacts)
The RPC rate is the first of the more specific metrics in this list.
This KPI measures the ratio of all outgoing calls to a valid phone number for the person (or “right person”) for whom the collection was requested. For collectors, the higher the score, the better the success rate of finding the debtor.
Of course, the first step in collecting claims is to find and contact the right person. If your company has a lower RPC rate than its competitors in other industries, you need to think carefully about what’s wrong and how to improve them.
Percentage of Outbound Calls Resulting in Promise to Pay (PTP)
The PTP rate is just as important as the RPC rate when measuring efficiency and is the next logical step to a successful collection. It measures the percentage of all calls that end with the debtor’s promise of payment. That is if the RPC rate measures the success rate of dialing the appropriate person, this metric measures the success rate of those RPC calls. This is another percentage that you want to get as close to 100 as possible.
Voice AI agents can help companies with lower PTP figures buy prompt calls for which the best agents can train the voicebot whose perfect timing and schedules will help improve the PTP stats.
Profit per Account (PPA)
Finally, PPA measures how much profit each account in your collection makes on average. In short, this KPI measures the impact each account has on revenue.
This metric is calculated by dividing the company’s gross profit (calculated by subtracting total operating expenses from total revenue) for a particular period by the total number of overdue accounts managed for that period.
A Voice AI Agent can help reduce the operational cost to the tune of 50%, along with a faster sales cycle, improving this performance metric.
Improving these numbers is a big challenge and we will now go into detail about how Voice AI can help debt collection agencies and NBFCs transform their performance.
Transform Your Collections Efficiency Ratio with Conversational Voice AI
The effort of a collection agency is to collect as much as possible and as fast as possible from every account, i.e. a higher recovery amount with a shorter collection cycle will improve the majority of performance indicators mentioned above.
Voice AI Core Benefits for Debt Collection Agencies and NBFCs:
Voice Automation: Voice AI will help your company by automating 70% of the calls, primarily tier-I calls, and by automating payment reminders and collection calls at B0 & B1 buckets. This would cut down the time & effort of human agents and they can focus on RTP cases. This would reduce the burden on human agents and improve the use of their time on meaningful and complex problems.
Augmenting Agent Productivity: Since the human agents focus just on RTP cases that require more empathy and intelligence, their efficiency and productivity take a big leap. This has an impact on CX as well as recovery rates as agents are not wasting their time on trivial tasks.
Cost-Efficiency: Be it collection calls or running outbound campaigns for reminders or notifications, etc., the Voice AI Agent can do everything at a fraction of the cost. This has long-term and big benefits for the company.
Quality and Compliance: The Voice AI Agent never fails to follow proper protocols and thus, avoids any potential legal challenges. Also, its delivery is always the same and hence its service quality does not deviate with mood, as with human agents.
9 reasons why NBFCs and Debt Collections Agencies Should Not Miss Out on Voice AI
Allowing human agents to focus on RTP (Refuse to pay) accounts. Thus increasing the profitability by converting high-risk accounts.
Automate simpler calls like reminders & FAQ – Proactively reminding debtors at the right time and helping them with FAQ related to their loan/upcoming payment. plays a far bigger role in collections and Voice AI does it perfectly.
Improve contact-ability & customer coverage – Voice AI is capable of contacting millions of customers in a matter of weeks. Thus the company can reach out to every customer for payment reminders, follow-up on DPD cases, and assist with queries related to the loan.
Shorten collection cycle – Faster reach outs and quicker conversion with Voice AI Agent helps shorten the collection process.
Persistency in follow-ups and call-back requests – Human agent may err in follow-ups but the Voice AI agent follows up as well as calls back at the requested time without fail. This is a big help and improves collections.
Capability to handle spikes in volume – Traditionally the call center teams are unscalable over short periods, but with Voice AI, this is not the case as it can handle any spike in call volumes.
Here are some other unique capabilities of conversation Voice AI for debt recovery:
Feeds data to the CRM tool and provides analytics for further action
Persuades customers to pay at the earliest, offering payment plans and options
Helps agent plan post-call follow-up campaigns with Voice AI Agent
These unique capabilities prove indispensable and give the debt collection agency or the NBFCs a big edge over their competitors.
How a Digital Voice Agent Adds Value to Collections Efforts
The Digital voice agents are highly effective at B0 & B1 collection buckets with no human assistance. The later bucket requires a bit more contextual conversation and dunning from the collection agent.
The digital voice agent gets a custom design flow to interact with customers at Bucket Zero and Bucket 1 for debt collection. At bucket Zero, the Voice AI gives out a “The last day of payment” reminder, requesting the debtor to maintain the payment amount balance in their account for auto-debit. The Voice AI also assists in converting manual payment to auto-debit.
At bucket one (1-30 days), the debtors are expected to pay off the due within the grace period so that their CIBIL is not impacted and does not affect their eligibility for future loans. The Voice AI communicates the same to the customer and assists them with on-call payment. The Voice AI can make calls, follow-ups, and take call-back requests concurrently at any time during the week and to which the human agent has limited capacity.
For situations when the customer is refusing to pay or is unable to maintain sufficient balance, the digital voice agent dispositions them accurately and notifies them of a call back from the human agent.
Voice AI Outcomes
It will be interesting to note that the Voice AI agent helps in improving every performance metric.
Collection Efficiency Ratio – Higher, overall collections help improve the collection efficiency
Age at List (AAL) – faster collections help in keeping the debt age towards the lower side
RPC rate (Right Party Contacts) – Voice AI calls and identifies the Right Party Contact so that human agents do not have to waste time. This is a radical improvement, without spending much money and time
Percentage of Outbound Calls Resulting in Promise to Pay (PTP) – Voice AI agent calls at the right time and to the right person when they prefer to interact, thus increasing the probability of recovery
Profit per account (PPA) – since with Voice AI agent, the costs as much lower, it has a direct impact on this metric
Here is what a debt collection agency or an NBFC can expect from Voice AI agents such as Skit’s Digital Voice Agent.
49% of the total collection value recovery per campaign
Debt recovery from 78% of delinquent accounts without any human assistance
Lower the cost of collection by 40% by addressing the collection challenges like unreachability, unresponsiveness, callback request, and collection after business hours
Achieve 90% of collections in the first 3 days
Increase customer coverage by 30%
Speed up the collection campaign TAT by 70%
80% contact-ability rate
84% engagement rate with customers
68% disposition capture rate on CRM allowing your agents to focus on accounts in the B2 bucket onwards for personalized interaction for recovery
The data mentioned above has been taken from project implementations, and will certainly vary for each company. Thus, it is indicative at best, of the results that can be achieved and the potential of the Voice AI agent.
For any questions on the application, operations, outcomes, and pricing of a voice AI agent in the debt collection space, feel free to contact us – Book A Demo.
For more information on debt collection space and the role of voice AI, please visit the page.
You’ve been exploring Voice AI as a possible solution to automate your debt collection agency’s operations; you’re considering adopting an Augmented Voice Intelligence solution to scale outbound and inbound calls for collections. Congratulations—you’re in the right place.
A Voice AI solution can significantly reduce your collection costs and improve the success rate and duration of your collection campaigns. However, not all Voice AI vendors are the same. How do you choose the right vendor for your agency?
Given our extensive experience with the collections space and our tech expertise, we’ve put together a list of topics to consider when meeting with providers and choosing the best one to move forward with, from the understanding of business operations to technical capabilities.
If you can’t count on your Voice AI vendor to fully understand the collections space, you will end up being significantly more involved with every step of the process, which will ultimately take longer, cost you more money, and lead to a disappointing return on investment.
Compliance with Debt Collection Regulations
The very first thing to look for in a Voice AI solution that handles outbound collection calls is the company’s level of understanding of the existing laws and regulations related to collections in the U.S.
A well-trained Digital Voice Agent can comply with the regulations with a consistency and precision that can be hardly achieved by human agents. However, it’s crucial to check whether the provider is up to date with the current laws.
The main collections-related regulations in place in the United States are:
Fair Debt Collection Practices Act and Reg F: The FDCPA, most recently updated with Regulation F in 2021, is the most comprehensive U.S. law that restricts, for example, call frequency and calling hours, and mandates the reading of the “Mini-Miranda.”
Telephone Consumer Protection Act: The TCPA ensures that numbers in the Do Not Call registry are never contacted; this can be easily achieved with Voice AI.
Federal Fair Credit Reporting Act: The FCRA protects information collected by consumer reporting agencies.
Payment Card Industry Compliance: PCI regulations ensure that the Voice AI provider takes the appropriate measures to protect stored cardholder data and encrypt the transmission of the data.
Health Insurance Portability and Accountability Act: HIPAA is one of the most well-known privacy laws in the United States.
Read more about meeting debt collection compliance with Voice AI in our blog post.
Provider’s Understanding of the Collections Space
This point goes beyond regulations: How well does the Voice AI provider know and understand the collections space as a whole? Their understanding of the structure and overall operations of a collection agency is likely going to be a helpful factor in the collaboration between the agency and the provider.
The provider should be able to understand the agency’s structure, the challenges related to employee retention and call scalability, as well as best practices for outbound collection calls. This way, you can trust that they will design an optimal conversation flow to facilitate your collection efforts.
Different factors will affect the conversation design. For example:
Nature of debt: There are different types of debt, including credit card, healthcare, student, etc.
Age of debt: A 30-day past due debt is very different from a 180-day past due debt.
Ability to Handle End-to-End Conversations
A Digital Voice Agent needs to be able to handle outbound collection calls from start to finish, without any human intervention—from verifying the user’s identity to completing the transaction.
The Digital Voice Agent will therefore initiate the call, remind the user of the due payment, register the reason of delay, persuade the user to pay right away, collect the payment or offer alternative payment plans, and ultimately feed the data it has gathered during the call to the CRM tool.
One important question to ask providers is: What kind of access will the collections agency have over the Voice AI?
The ideal provider will offer access to a dedicated and user-friendly platform, from which the agency will be able to view and tweak conversation flows.
Additionally, having a good platform will also help with the integration of third-party applications, such as payment gateways, CRM, and other business applications.
Want to learn more about how the technology behind a Digital Voice Agent works? Check out our dedicated blog post.
Once the Voice AI solution goes live, will you be able to easily visualize and analyze its performance and results?
As more and more users speak with the Digital Voice Agent, you gather precious data that you don’t want to waste. Your Voice AI vendor should give you access to a dashboard to monitor the effectiveness and quality of the conversations.
MLOps (Machine Learning Operations)
At the very core of Voice AI lies the capability of the algorithms to continuously learn and improve as more conversations take place.
MLOps stands for Machine Learning Operations and it’s somewhat similar to DevOps. It’s an organizational model and culture designed to help the involved teams manage the operational processes behind machine learning.
AI companies that have a good MLOps system in place are likely to develop a better technology set to improve with time.
After Go-Live: Continued Voice AI Training
Your Digital Voice Agents are ready to go live and start calling your customers to remind them of their due payments. What now?
After the Voice AI platform goes live, the work is far from finished. The Digital Agents must be maintained for further optimization of the technology and the conversational experience, also to ensure they understand out-of-scope intents. The solution must also be monitored, especially at the beginning, for quality assurance purposes.
According to a recent Gartner report, failing to monitor automation tools in post-production is one of the most common mistakes companies make when implementing automation.
Additionally, it’s important to note that Voice AI solutions are typically rolled out in multiple phases: with time, additional capabilities and use cases may be added.
Therefore, your agency will want to work with a Voice AI provider with a clear plan for post go-live training and handling.
In conclusion, watch out for these key questions to ask your Voice AI vendor.
For more information and a free demo, you can schedule a call with one of our collections experts. We’ll be happy to help!
Owing to far-reaching repercussions, compliance management has become an issue of gravitas. It’s a challenge of change. Often, frequent regulatory changes create ambiguity for collection agencies. For instance, Regulation F of the Consumer Financial Protection Bureau (CFPB) came into effect on November 30, 2021, and is the most significant debt collection rulemaking. Any creditor–either the original issuer or a debt buyer–faces challenges in responding to it. And even more tedious is training and retraining agents, reiterative setting up processes and tools to meet regulatory requirements.
When it comes to compliance, the devil is in the details. A human agent under varying stress and performance pressure is prone to make mistakes. But even an innocuous breach of compliance results in hefty fines and penalties. Even without state or local mandates around debt collection practices, federal regulations must be followed to avoid penalties or lawsuits from consumers or enforcers. CFPB levied $1.7 billion in civil penalties and over $14.4 billion in relief for American consumers in the last ten years. Compliance has thus evolved as a significant pain point for debt collections agencies.
We have reached a point where compliance is not just an expense item but also a source of differentiation for collection agencies. Unsurprisingly, most debt collection agencies are looking for tech solutions that can help them be more agile and efficient. Voice AI is one emerging solution with the most disruptive potential and growing use cases.
Too Many Calls, Too Little Communication
One of the prime objectives of compliance is to protect the customer from unfair practices and harassment. CFPB bases much of its enforcement authority on the concept of UDAAP (unfair, deceptive, and abusive acts or practices).
A call at the right time, to the right person, and with the right message can achieve the 3 Cs of debt collection: Cost, Compliance, and Customer Experience. A human agent may struggle to accomplish the triad, making too many or too few calls, but it’s a cakewalk for an intelligent voice agent.
The formal, statutory fees and levies, which are increasingly hefty, represent just the tip of the compliance cost iceberg (around 10%) of total regulatory costs. The broader cost of compliance is much bigger, making it a formidable force.
Here are the common challenges faced by debt collection agencies today:
Ever-Expanding List of Laws: Fair Debt Collection Practices Act (FDCPA), Telephone Consumer Protection Act (TCPA), Federal Fair Credit Reporting Act (FCRA), Payment Card Industry compliance (PCI), and Health Insurance Portability and Accountability Act (HIPAA) are a part of a growing list of regulations, adherence to which is a core driver to the success of debt collection agencies and similar financial institutions.
High Cost of Continual Training and Vigilance Process: A survey of sector firms by the Credit Services Association (CSA) reveals that in staffing terms, the proportion of resources involved (in compliance) seems to trend generally between 15% and 25% of total resources. That is a significant percentage and an opportunity to cut down the cost.
Client Expectation and Audit Requirements: Clients of collections agencies are deeply wary of meeting compliance and exert pressure, even more than regulators, to comply. As per a report by CFPB, collection agencies with large clients face 17 audits in a year. That’s an average of 3 audits every 2 months. The lack of transparency between debt collectors and consumers makes it difficult for agencies to facilitate these audits effectively. It is a formidable challenge to meet such high expectations cost-effectively.
Insufficient Time to Design and Implement Compliance Effectively: A rapid and frequent change in regulation leads to collection agencies running from pillar to post to update their processes. Deploying AI-enabled voice agents can minimize the training and guidance cost.
High Cost of Not Meeting the Compliance Requirements: Failing to meet the compliance requirement has, in the past, led to grave heavy consequences. Encore and Portfolio Recovery Associates, two giants in bad debt collections, were fined $18 million in 2015. They were forced to refund or halt collection of over $160 million in consumer debts. Violating the Do Not Call registry can cost agencies anywhere between $500-$1500 per case, as per TCPA. Moreover, razor-thin margins make the total cost of attorney fees, settlement costs, and the opportunity cost of time too much for agencies to bear.
Voice AI and its Ability to Empower Collection Companies Manage Compliance
More often than not, compliance is a matter of adhering to protocols and procedures. AI-enabled digital voice agents that can religiously follow a given set of instructions prove far superior in adherence to the regulatory framework.
There are numerous instances where small mistakes land collection agencies in trouble. Here are some simple yet powerful examples of how Voice AI can help with compliances:
Honoring Do Not Call Registry and Data Scrubbing: The telephone Consumer Protection Act (TCPA) maintains a register of subscribers who do not want to be called for telemarketing calls and automated dialer calls unless you have consent to do so otherwise. It’s essential to scrub the data before dialing these contacts and check for permission. Solution is to scrub the data against certain database such as Do-not-call registries (external and internal), consumers represented by attorneys and debt settlement companies, deceased consumers, serial litigators, bankrupt consumers, cease-and-desist order consumers. Unlike human agents, who can fumble, digital voice agents perform this with the help of APIs in a fraction of a second.
Calling Within Permissible Hours: FDCPA does not allow collection agencies to contact customers outside of 8:00 a.m. to 9:00 p.m. local time unless the consumer has given explicit consent. Additionally, customers with night jobs may not wish to be contacted during the day. Such personalization in large portfolios prove to be a daunting task for a human agent but an effortless one for a digital voice agent.
Calling Frequency: Regulation F of CFPB limits the frequency of calls under the 7/7/7 rule, restricting the agencies from attempting to establish communication with their consumers for more than 7 times in 7 days. The 7/7/7 rule includes voicemail, unanswered calls, and messages left on the consumer’s phone, and excludes email and text messaging. Furthermore, agencies cannot try to establish contact in the next 7 days after a successful communication. It’s taxing for human agents to consistently follow these rules for the entire customer base while optimizing time and cost at the same time. On the other hand, configuring machines to follow all these rules is possible with a click.
Mini-Miranda is mandatory as per FDCPA in the first communication in any channel. Digital voice agents never fail to comply with such regulatory requirements.
Failure to Discontinue Communication Upon Request: Communicating with consumers in any way (other than litigation) after receiving notice with certain exceptions can lead to lawsuits. Machines follow strict protocols and comply with the request submitted by the consumers.
Communicating with Consumers at Their Place of Employment: It’s illegal to contact the consumer after being advised that this is unacceptable or prohibited by the employer. Human agents under dier conditions fail to honor guidelines. On the other hand, since machines reachout at the right time and frequency have high conversion rate while meeting compliance.
Contacting a consumer represented by an attorney: Agents must not contact the consumers who have chosen not to be contacted by agencies and have signed up attorneys for communication with certain exceptions.
Communicating with a Consumer During Validation Period: Human agents can make a mistake and try to establish communication with the consumer or pursue collection efforts after receiving a request for verification of a debt made within the 30-day validation period. On the other hand, Digital Voice Agents are configured to not engage in any such activities and trigger the automatic collection calls once validation period is over.
Misrepresentation & Threatening Arrest or Legal Action: With variable incentive as a major wage component, it’s quite common for debt collectors to misrepresent as attorney or law enforcement officer. FDCPA prevents such kind of misrepresentation and has punitive enforcement directives. Digital voice agents follow strict protocol and never succumb to such malpractices.
The abusive or Profane Language used during communication related to the debt is prohibited. Digital voice agents never fall back to such practices in order to achieve the results.
Communication with Third Parties: revealing or discussing the nature of debts with third parties (other than the spouse or attorney) is prohibited except to know the location of the debtor without mentioning debt related information. Intelligent Voice Agents can confirm the right party before giving out any information.
Raise a Dispute: Voicebot can also help consumers raise a dispute over a call and tag it in the CRM so that the relevant team can pick it up.
Validation: Upon asking for validation information, the voice bot can immediately send the electronic copy of the validation notice and mark the contact with a relevant tag so that human agents can see the status, and neither the voicebot nor human agents try to communicate to the consumer for the next 30 days.
Raise Tickets: Voicebot can even raise tickets to send the physical copies of the validation notice if explicitly requested by the consumer.
With Distinct Advantages, Voice AI Will Play a Bigger Role in Compliance Management
Apart from numerous other use cases, the utility of Intelligent voice agents in improving the compliance of debt collections agencies is fast emerging and very promising.
Apart from the direct costs of compliance, indirect costs such as fines and penalties take a heavy toll on companies. Today, compliance has become more than an expense but a source of differentiation. Many companies have already begun adopting Voice AI, and its ever-expanding use cases will help them create a distinct competitive advantage.
For more information and free consultation, let’s connect over a quick call; Book Now!
In the new normal, key players in the debt collection industry, from creditors to every downstream collection agency, face significant challenges to improve collections. This is happening mainly for two reasons. First, there are rapidly evolving regulatory and compliance frameworks to which collection agencies must adhere. Second, the mitigation of cost has become an extremely uphill task.
However, there is an additional issue at play: The most common solutions prevalent in today’s market, such as Robocaller and outbound IVR voice blaster, are incapable of conversations, feedback, and insights. Instead, an AI-enabled Voice Agent is capable of meaningful and human-like conversations with customers.
Unlike the most common solution prevalent today, i.e. Robocaller or outbound IVR voice blaster (incapable of conversations, feedback, or insights), an Intelligent Voice Agent is an AI-enabled machine capable of meaningful human-like conversations.
Why is an Intelligent Voice Agent Ideal for Collections?
Intelligent Voice Agent, which is the blend of conversational voice AI and human intelligence, holds me
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.
Research provides plenty of information to support the cause of automating collection calls. Apart from research provides plenty of information to support the cause of automating collection calls. Apart from improved recovery, 1 in 4 US consumers prefers interacting with an Intelligent Voice Assistant when handling awkward financial situations, according to a 2018 consumer sentiment survey by The Harris Poll.
Solving Collection Challenges with an Intelligent Voice Agent
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.
7 Reasons Why Augmented Voice Intelligence Is Transforming Debt Collections
Augmented Voice Intelligence, which is the blend of Conversational AI and human intelligence, creates meaningful conversations with customers to support them throughout their entire collection journey while staying true to compliances and regulations. Let’s delve deeper into the 7 core reasons:
1. Automation AndHuman Bandwidth Prioritization
The beauty of deploying an Augmented Voice Intelligence is that it can call all the customers and it then filters out the complex cases that need human agent intervention. In the present system, agents call the entire list of contacts, be it a simple case or a complex one, not creating desired value in the process.
With a virtual voice agent, all the contacts in the portfolio are called at the right time of the day and within a couple of hours. The entire portfolio is then segmented based on the disposition collected for each debtor. The dispositions captured can be: propensity to pay, refusal to pay, wrong-party contacts, disputed debt, call-back later, validation requests, etc.
For willing debtors, the virtual voice agent can not only collect the payment during the call but can also negotiate and offer alternate payment options. It also reminds them of the next due date.
Additionally, the Digital Voice Agent calls back all the debtors who could not be reached in the first attempt without the need for human agent intervention. This takes a huge burden off them.
For the dispositions in which human intervention is required, the Voice Agent can segment the portfolio so that relevant human agents can be assigned the downstream tasks based on the importance of the disposition for the portfolio and the company.
This automation and prioritization of bandwidth unlock massive value for the collection companies.
2. Improved Portfolio Volume and Customer Coverage
If, let’s say, 66% of the debtors are handled by digital voice agents end-to-end, now collection agencies can take up 3X more portfolios or cover 3X more customers with the same set of human agents. This illustrates how the same support team can manage higher levels of business with even better results.
Collection agencies can take up more portfolios or take bigger ones, as they now have better customer coverage.
3. Lower Cost and Faster Collection Speed
Contact center automation with Conversational Voice AI assistant ensures that service quality and speed remain consistent, which otherwise will be volatile as new human agents with less experience join the team. Also, continuous hiring and training is a great operational hassle.
The Digital Voice Agents can make hundreds of concurrent calls at scale, economically, and in just an hour. Not only that, voice agents, being a machine, are very punctual and reach out to debtors that request a callback or make reattempts right on time when the probability of connecting to contact is highest. All this is done within the prescribed compliance framework.
4. Superior Recovery and Collection Efforts
Better collection and recovery require persistent efforts. When nudged at the right time, a debtor who is willing but unable to pay now might pay a few months down the line. Thus, what matters is how persistently collection agencies can reach out to a certain segment of debtors, ideally disposed to pay.
Understandably, a significant section of debtors will not pick up calls in the first attempt or might request a call-back at a certain time in the future. It is near impossible for human agents to follow up on every single contact, but the intelligent voice agent can do it with perfection.
It’s a piece of cake for a Digital Voice Agent to schedule follow-up calls, honoring the regulatory guidelines, spread over weeks/months, and ensure better recovery rates. With timely and adequate calls going out to customers, and 24/7 support, the right voice-tech solution checks all the boxes to improve collections and recovery.
5. Minimize Errors, Ensure Compliance and Security
A significant amount of agent training and monitoring can be avoided with the deployment of Voice AI agents. High employee turnover, clubbed with significant training costs makes the entire exercise of meeting compliance, extremely costly. While the possibility of potential errors as regulatory regime complications is on the rise, it cannot still be eliminated.
Conversational Voice AI Agents operate with negligible errors and can be easily updated, thus improving compliance significantly. Also, a Voice Collection Agent can be well trained in regulatory frameworks and will therefore ensure strict adherence to consumer data security and protection (encryption and redaction) by sticking to industry best practices.
6. Enhanced Customer Experience
A Voice AI agent can ensure a smooth, courteous, and positive debtor experience, leading to a positive attitude towards the collections process and ultimately a positive brand image.
7. Seamless Support Scaling for Any Call Volume
Business volatility and fluctuations put an economic strain on collection agencies that need to maintain a qualified team of human agents which has to grow and shrink with demand volatility. Scaling becomes further challenging as employee turnover is the highest among industries.
With the deployment of Augmented Voice Intelligence, there is no need for maintaining a large contact center team to deal with large call volumes, as voice automation helps in handling a majority of calls. Thus the problem of team management becomes minimized.
Intelligent Voice Assistants: The Future of Agile Customer Service
At times of disruption, it’s essential to leverage technology to craft a sustainable competitive edge by addressing core business challenges.
Growing evidence hints at the power of Augmented Voice Intelligence to enable cost optimization, and handle a broader customer base while minimizing significantly the operational challenges relating to regulatory compliances, and team management.
With a tad steep learning curve, it’s best to be an early bird. The evidence abounds, with the right tech solution partner, there is a great amount of value creation possible.
Move early, move fast, grow faster!
For more information and free consultation, let’s connect over a quick call – Book Now!