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.
We are at the initial stages of Voice AI’s evolution, in an epoch where well-functioning vertical Voice AI solutions will be instrumental in helping companies transform customer support and gain customer loyalty. But to a significant faction of CXOs, the understanding of Voice AI technology, its capabilities, and nuances remain obscure. Our earlier articles have tried to elucidate voice technology and how it can prove instrumental in transforming contact centers. In this article, we further that conversation and move on from discussing the Voice AI ‘product’ to the ‘platform’ and why companies looking to automate their contact centers must consider platform capabilities as a factor that will impact their long-term success.
The platform question holds greater gravitas when the top priorities are ROI, time-to-live, control over performance, and market leadership. In this blog, we deep dive into the core questions: what does a Voice AI platform look like, why does having a capable platform matter, and what are its far-reaching implications?
Today, voice technology has advanced sufficiently to deliver intelligent voice conversations. The wait is finally over, and companies can transform their CX with voice-first Augmented Voice Intelligence platforms.
Even coming to the correct conclusion about a Voice AI vendor capabilities is not easy. But let’s assume the product is good, but before signing up, look into the vendor’s platform capability. It is the next big and most important task because, in the long run, the performance will depend mainly on the platform’s capabilities.
Before we go deep into the topic, let us, distinguish a product from a platform.
A product is essentially an application that solves a specific use case.
The Platform is the underlying structure that provides the core building blocks and the infrastructure for the functioning of one or many products.
In other words, a platform is an enabling environment over which many products run. The architecture of a chat-first voice-capable platform will be very different from that of a voice-first platform because the latter is built and optimized for voice, giving it a distinct performance edge. Here is a glimpse of a purpose-built Augmented Voice Intelligence Platform:
The Platform View of a Vertical Voice AI Company
From the above diagram one thing comes out clearly: that for smooth functioning of a Voice AI solution, its various constituent parts must work in perfect synchronicity. Hence, beyond the product, i.e., the voicebot, various other platform features are needed for an ideal Voice AI solution.
Let’s deep dive to answer the questions: why should companies look for platform capabilities in their potential Voice AI vendor?
At the core of this issue is the increasing realization that voice as a medium of customer support will see an irreversible rise in the coming years, led by Voice AI technology. In the long run, any company that wants a firm hold on its market share or leadership must look into the Platform capability of its Voice AI vendor to enhance the probability of sustainable success and competitive advantage. Here are the five core advantages of a robust Voice AI platform:
Long-Term Success: The performance, strength, and sophistication of the Platform, not the product, determines the success of the company in the long run. Choosing the right Platform will help contact centers mitigate the risk of changing the vendor and starting from scratch mid-course.
Replicating Platform Technology is Challenging: Platforms can not be built overnight. Creating a state-of-the-art platform technology takes vision, resources, capability, and time. Over time the benefits multiply due to network effect and learning curve advantages associated with AI models. This initial advantage creates a remarkable difference as years add on.
Leveraging Modularity: A robust platform always aces modularity as it provides diverse and latest technology options for contact centers to create their solution the way they want. It allows for ease and diversity of integrations. This gives the company flexibility in cherrypicking integrations.
Multiplier Effect: In the extended run, contact centers, Voice AI providers, and other application providers benefit from a robust platform as it harnesses the multiplier effect by leveraging the presence of dozens, hundreds, or even thousands of third-party vendors. So, any company using the platform to deploy a voicebot will have not only a multitude of choices, but they will also benefit from the innovation they bring in, as it can be easily incorporated into their voicebot.
Faster and Agile: A strong Voice AI platform will make it easy for companies to create and upgrade their voicebots. Reduction in time-to-go-live and ease of creating, maintaining, and enhancing the voicebot makes it easy to change and maximize its effectiveness.
Here are some of the capabilities of an evolving Voice AI platform:
A Unified View: It should give a unified view of the entire voicebot, from stats on conversational design to integration to ASR.
Voicebot Creation: It must allow companies to create conversational flows and test and deploy them with minimal help from the Voice AI vendor.
Collaboration: It must allow the users to collaborate and comment at any point of voicebot creation.
Enhancements and Testing: Changes in policy, customer preferences, or offers must reflect changes in conversational design. The users must be able to easily do these upgrades and modifications and test them before deployment.
Campaign Management: The effectiveness of the voicebot depends on the capability of the user to run campaigns with complete control. It must allow them to upload data, run campaigns, and modify them real-time.
A Wide Range of Tools and Integrations: Creating a voicebot with autonomy requires giving a choice of a wide range of tools. A robust platform would provide that to its users along with a great variety of integrations.
A Voice AI vendor can have a great product and a short time to market. But if it is missing a great platform, then, in the long run, its clients will lose their competitive advantages. A CXO can indirectly identify the signs of a weak platform. Here are a few major red flags of a weak platform:
Opaque: The creation of the voicebot will be opaque to the contact center.
No Clear Visibility: The elementary constitution of the voicebot and its functioning will have no visibility.
Lack of Agility: For every minor tweak, the user must catch hold of the engineering team to code and execute the change. This is a waste of time, resources, and money.
Operational Friction: Constant and copious communication between the user and the Voice AI vendor will decelerate the pace of implementation of changes.
Slower and Patchy Delivery/Updates: Delays in deployment, updates, and upgrades
Absence of a Marketplace Advantage: A robust platform grows rapidly, and with its growth comes the network effect, i.e. the presence of third-party solutions that can augment performance in many dimensions.
Lack of Control on Quality: Giving absolute control over the creation and deployment of the voicebot helps the users engage more deeply with their voicebot and mold it with their vision. The outcomes are much better and are sustained for a longer period.
Some great ways to identify these telltale signs is to engage in a free-of-cost pilot or to ask relevant questions during detailed demos.
The essential thing is, a Voice AI vendor must possess a great product that can converse intelligently with consumers or callers. Additionally, this product must be facilitated by a robust underlying platform that enhances its capabilities, adding to the overall experience of creating, deploying, and improving the voicebot.
To learn more about Voice AI solution and what it can do for a contact center, book a consultation now: www.skit.ai
Voice AI is one of the most transformative and consequential technologies for Generation Alpha—the first generation raised with voice assistants and unaccustomed to life without them.
The Internet is dazzling with data and stories on how businesses and consumers
are embracing voice technology; no wonder smart speakers are the fastest-growing consumer technology since smartphones. We are witnessing a voice revolution, as the cutting-edge Voice AI is reinventing the way we shop, and seek customer support. Voice AI will also fuel our undisputed robot-centric future in which the younger generation will converse with smart devices to learn, the elderly will voice-command diagnostic devices, and enterprises will deploy Voice AI agents to answer every customer call.
The Potential Impact:
A Forbes report revealed that major publishers lost as much as $46,000 a day — for a total of $17 million in 2019 due to the failure of common voice assistants to identify the books consumers intended to purchase. The report makes three things very evident:
The voice support stakes are high
Disruption is evident
Voice-first solutions with cutting-edge capabilities are becoming the need of the hour
With the rapid penetration of edge computing, voice will be used to communicate with IoT, smart devices, and other innovative applications. Business leaders must consider – how the voice movement will affect customers’ support expectations, and the way they interact and shop. And how should their businesses, in turn, reinvent themselves?
Voice truly offers a blue ocean of possibilities!
The Rise of Vertical Voice AI Support and Troubleshooting
A significant transformation is currently taking place on the business side. Every customer call is a chance to either strengthen the relationship with the brand or repair it; Voice AI is empowering companies to answer and resolve every query and develop that much-needed bond with consumers.
Voice AI is enabling call center voice automation – that means answering customer queries in a multi-turn, intelligent conversation without human agent intervention.
The impact is significant in terms of cost, productivity, performance, agility, and top and bottom lines. There is an incredible potential for Voice AI support. Here are a few prominent examples of outcomes contact centers have been able to achieve:
70% automation of customer support efforts
40% reduction in average handling time
CSAT scores of over 4.0
50% reduction in operational cost
Better CX with 24/7 intelligent support
Better customer loyalty due to proper support throughout the customer life cycle
Organizations can also analyze call center recordings to look for sentiment and tone, deploy voice-enabled surveys, and more. Voice is therefore a treasure trove of value and competitive advantage.
Voice-First Technology and its Cross-Industry Ripples
By 2023, nearly 80% of consumer apps will be developed with a “voice-first” philosophy, according to Gartner’s AI and ML Development Strategies Study. This marks a significant shift towards placing voice capabilities at the center of every customer interaction.
Every industry, from gaming to tourism has seen the adoption of Voice AI.
Several banks are shifting to Voice AI-powered automation for 24/7 intelligent customer support at a fraction of the cost. Even the debt collection space is seeing a rapid uptick in adoption. Big names such as Capital One, Barkleys, and others have been using Voice AI for support. Various large Indian banks in NBFCs are also leveraging the technology for cost-effective and 24/7 customer support. Many smaller players are also adopting Voice AI and have seen remarkable business outcomes.
CX rules this industry. Millions of customer support calls are made every day. The cost of the support has constantly been rising and consumer durable companies have been scouting for an ideal solution. Many voice AI companies have adopted Voice AI, with huge success. Voice AI has delivered true 24/7 support through intelligent conversations that are cost-effective. With rising use cases such as – inbound call support, feedback and reminder calls, product update calls, and more; Voice AI will see a substantial increase in adoption.
Today, Voice AI is helping adults–in nursing homes and senior living facilities–manage loneliness, isolation, and depression. It is helping patients with Parkinson’s with exercise regimes (Triad Health AI); even ambulances in New England have gone voice-first, eliminating paperwork during emergencies.
The automotive industry is much more voice-first, with all major players from Ford, and BMW to Tesla offering voice assistance. 77 million adults in the U.S. use voice assistants in the car, compared to 45 million adults using in-home smart speakers. With cars increasingly becoming tech-driven, automotive companies will use voice AI more aggressively as the preferred modality of choice.
This is essentially a laundry list; from hospitality to space, voice is all the rage.
The Rise of Smaller, Secure, and Specialized Vertical Voice AI Companies
Google Assistant or Alexa are not the only choices; companies, in addition, prefer small companies with voice tech that supports multi-turn conversations along with a tighter security architecture. Also, when it comes to effectiveness, many Vertical Voice AI vendors specializing in niche use cases outperform tech giants. Debt collection, feedback, rescheduling flights, answering customer FAQs, or sending reminders, new voice AI startups are moving the needle in a big way.
What makes voice appealing:
User Experience and Satisfaction: Nothing comes close to an intelligent and quick conversation that sorts out problems. If a Voice AI-powered agent can work with subtle nuances, and behavior modification to match customer personality, well, customer delight is unparalleled.
It is Faster and Natural: Not only is speaking natural, it is 3-times faster than typing. Many companies, across industries, have been able to reduce the average handling time of support calls by 40%. Virgin Trains, UK, for instance, reduced their average booking time to 2 minutes from 7 minutes with Voice AI.
It’s frictionless: Instead of opening different apps for different needs; with voice, everything is just an utterance away.
It is Your Intelligent and Always-on Mate: New innovations are changing the way products are sold. Talk to a virtual assistant/agent when you drop by your liquor store and Voice AI will help you select wine. British alcohol beverage company, Diageo innovated by investing in voice-led applications and Alexa skills, The Bar. It is created to serve as a user’s personal bartender by recommending cocktail recipes and teaching mixologist techniques. Reimagination is already making its way.
Multi-modal Voice Experience: With voice at its center, the future is multimodal. Consumers can use voice commands while they are shopping via TVs or an Alexa device with a screen.
Here are some big challenges retailers and customers will face with voice:
Data Privacy. When businesses use Alexa or Google Assistant, in essence, they are giving them access to their offering and that is compelling competitive intelligence. Other challenges such as cloning and data can be mitigated with proper regulations in place.
Browsing Difficulty. It is easier to go through a list of search results on a screen, making common product research challenging with voice. But hybrid devices such as smart devices with screens, or navigating shopping with voice on TV can notch up the CX further.
Information Availability: To shop or engage with a brand it is essential to know if it is available in the 3rd party ecosystem. The lack of options/info is a challenge.
Technological Capabilities: Tech is still evolving, and quite a few challenges hamper the experience. Noisy environments, varied accents, pronunciation, languages, and dialects are common challenges that impact conversation quality. On the tech front – barge-in capability, advanced paralinguistic capabilities, processing speeds, and a lot more are required to have enjoyable, human-like conversations.
But even with these given challenges, the strides of voice tech are giant and brisk.
Given the ubiquitous nature of voice tech applications, organizations must think of creating a voice interface to cover all of their customer touchpoints. Be voice-ready on smart speakers, voice assistants, websites, apps, customer support, and even in-store experiences. Create a voice that is always present to help your customer; it will help your company be present in new avenues to serve, personalize, and leverage data.
Every company must have a voice!
To learn more about Voice AI and the significance of Voice in coming years book a consultation: www.skit.ai
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
Management guru Peter Druker’s most important quote resonates completely with voicebot performance: “If you can’t measure it you can’t improve it.”
Aren’t CXOs constantly debating the expenditure on technology and its RoI? While a razor-sharp focus on the end results is well warranted, the choice of metric is very important, too. Businesses can succeed only when technology goals are linked to the business goals, and they finally crystallize as positive outcomes.
Contact centers are one of the most dynamic types of organizations that have been on a relentless hunt for automation solutions. They measure outputs with awe-inspiring precision and optimize their process to be more effective and cost-efficient.
Often, and fallaciously so, contact centers use containment rate as the most important metric when measuring the voicebot performance. In this article, we will demystify the limitations and dangers of using containment rate as an absolute measure of voicebot performance.
What is Containment Rate?
The containment rate is the percentage of users who interact with an automated service and leave without speaking to a live human agent.
When a customer ends a customer service interaction without the need to speak to a human agent, the call is said to be contained. While that may be great news in terms of resource optimization and better usage of human agent bandwidth, what does it really reveal about the customer’s experience? The containment rate does not reveal whether the customer’s query was resolved or if the customer was satisfied. Nor does it reveal anything about the effectiveness of your voicebot or even the IVR.
Why Containment Rate Goes Against the Principle of CX
If your goal as a company is to prevent your customers from reaching a human agent for support, then the containment rate is the best metric. But is that strategy reflective of your vision?
Ideally, in a world with no resource constraints, there would be a human agent ready to answer every customer’s call. But the cost factor proves to be prohibitive, resulting in the need to find a cost-effective and scalable means to improve CX. The technology deployed may range from mundane IVR to state-of-the-art Voice AI. But if the focus is just on increasing the containment rate, it will end up damaging CX.
Every call is an opportunity to forge a long-lasting relationship that can help a company improve its top and bottom line, over time.
What are Voice AI Agents or voicebots deployed for? It is to serve the customers better, provide zero wait-time and 24/7 support, and not prevent them from reaching human agents. The general idea is to promote self-service, yes, but if a customer wants to interact with the company, closing that door is not an ideal way to achieve customer satisfaction.
Hence, the containment rate must be seen in the context of other metrics while deciding if the performance of a voicebot is improving or not. Here are the situations where containment rates can be a misguided yardstick:
Increasing Containment Rates: If seen in isolation, this can seem like an improvement. But customers may be ending the calls because the Automated Speech Recognition (ASR) engine is not recognizing their voice or words. It can also be that the conversation flows are not optimized, leading to customer frustration. There are several other situations where customer queries are not resolved and causing them to hang up. Here, the containment rate may rise, but at the cost of CX.
Decreasing Containment Rates – Scenario 1: Calls can be classified into two categories: Completely successful calls, or partially successful calls. Many times, a voicebot is able to answer customer queries, and collect information, but for further complex questions or disputes, customers may ask for a human agent. Containment rates may decrease in these cases, but CX will improve. This is because the voicebot eliminated any waiting time for customers, it answered basic questions. The collected data and conversation helped the human agent quickly resolve customer queries; all culminating in improved CX. If we look only at the containment rate, we might assume that the voicebot has performed poorly and can result in bad business decisions.
Decreasing Containment Rate – Scenario 2: Every Voice AI Agent is trained for certain use cases and that is what makes them more effective than any other horizontal AI solution. In a case where the Voice AI Agent is handling all the calls but is trained for limited use cases, the containment rates may vary depending upon the volume of in-scope and out-of-scope calls. Hence, the generic or overall containment rate would be a wrong measure of voicebot performance.
The 10 Most Ideal Voicebot Performance Metrics
All the discussion here surrounds inbound calls. Here are the metrics people must use to measure voicebot performance.
Yet again, it must be emphasized that no metric must be studied in a vacuum. Only when put together, the true picture will emerge. But here are some performance metrics that make the most sense:
Business-related metrics: KPIs that focus on business impact and Voice AI objectives.
It is defined as the percentage of calls answered within a predefined amount of time. It can be measured over 30 minutes, 1 hour, 1 day, or 1 week. Also, it can be measured for each agent, team, department, or company as a whole.
A 90/30 Service Level objective means that the goal is to answer 90% of calls in 30 seconds or less.
Service Level is intimately tied to customer service quality and the overall performance of a call center. Thus, instead of containment rate, Service Level is a better measure of measuring performance and can facilitate key decisions better. Deployment of a voicebot must immediately jump up the service levels and thus create business benefits.
First Call Resolution Rate (FCRR)
A call is marked resolved when the voicebot grasps the users’ query and has done everything right to assist them, even if it means connecting them with a human agent and the issue getting resolved in the first call itself. FCRR is an important metric as it helps to understand whether the voicebot is performing correctly for the use cases it is designed for and how well it is escalating the call.
Though a relatively marginal case for inbound calls, high FCRR will impact the cost of customer acquisition (CAC) and retention for obvious reasons. Instant call pickup, intelligent conversation, answering a customer query, and any follow-on questions can reduce the time lapse between customer query and purchase.
Also, higher FCRR goes a long way in increasing and maintaining customer retention. Higher FCRR is also necessary to navigate higher Costs per Call.
In-Scope Call Success Rate
Though contact centers can measure the overall success rate, a better metric would be the Inscope success rate. At any given moment, a voicebot may be trained for a limited set of use cases. For example, a Voice AI Agent might be equipped to handle PNR queries or schedule maintenance visits, but when a call goes beyond this scope, it should pass on the call to a human agent. Hence, true success can only be measured if only in-scope calls are considered to calculate the success rate.
Average Handle Time (AHT) – In-scope Agent Transfer AHT and End-to-end Automation AHT
To understand better, let’s compare the AHT in the two scenarios where a Voicebot must create value.
AHT Comparison for End-to-end Automation – For a specific set of use cases the voicebot is designed to answer every query without the need for a human agent. The average call handling time AHT 1, as shown in the graph above, can be compared with a similar use case answered by a human agent.
It must be noted here that typically the cost per call per minute of a voicebot is quite lower, 1/7th (though inherently subjective), of the same cost of engaging a human agent. Hence, even if the voicebot takes the same amount of time to resolve the query, business gains are 7 folds.
AHT Comparison for Escalated Calls: Interestingly, AHT can be compared even when the call is forwarded to a human agent by the voicebot. This is because the voicebot captures essential data such as – it verifies the identity of the callers, captures their intent, and forwards the call to the human agent so that he/she can pick up the conversation from the last point.
If the AHT of an escalated call is lower than the call answered by a human agent, then it means that even for out-of-scope calls, the voicebot is creating value.
If the voicebot is escalating the calls for use cases it is trained for, it needs improvement. If it is escalating calls out-of-scope, then it is functioning perfectly well, and this information can still be used for broader decision-making.
Scenario: Agent Transfer After Resolution Due to Dispute or Second Query Many times atypical conditions arise when the customer just wants to speak with an agent, ex. when an insurance claim is rejected, the customer invariably wanted to speak with a human agent to vent out their agitation. Voicebot is not at all responsible when the call escalates to a live agent in such cases, and hence such situations must not be considered when assessing the performance of the voicebot, the situation warrants human agent intervention.
Such deep analysis is only possible when such metrics are considered to evaluate voicebot performance and business gains.
User Experience Metrics: Companies must focus on CX that is useful, engaging, and enjoyable; creating a positive image that leads to product purchases, referrals, repeat purchases, and loyalty.
Finally, the moment of truth, the CSAT score. It is a result of the overall performance of the voicebot. It is a good measure because ultimately, everything is futile if the voicebot doesn’t move the needle on CSAT scores. You can have a high containment rate to boast about, but if your corresponding CSAT scores are falling, your business performance will suffer significantly.
6. Average Wait Time
A company has to take a decision, it can route every call via the Voice AI agent, and this will bring down the average wait time to zero. Wait times have a serious and direct bearing on CX. One single-shot way of engaging the customer without making them wait or having them get further frustrated with IVRs is by deploying the Digital voice agent at every call.
7. Average Resolution Time
Once the customer is through and is speaking with the agent (human or voice AI) the time it takes to resolve the call matters a lot for consumers. This number must be looked at when CX is a priority.
Technical Metrics: Ensure the conversational AI product works and adheres to the requirements for performance or latency.
8. Intent Recognition Rate – Most important voicebot performance metric, and refers to the accuracy with which the voicebot is able to capture the intent of the speaker. This is important because a voicebot can only troubleshoot when it is able to capture the intent accurately.
9. Word Error Rate: The accuracy with which the ASR can recognize the words. Lower does not mean the outcomes will be inferior if intent recognition is high. But, the higher the accuracy the better.
10. Latency: Latency is a delay in response, and unlike chatbots, voicebots need to be pretty quick and agile in their response else they risk losing the customer’s attention and being pigeonholed as ineffective. Typically a Chabot latency is the sum of latencies of = ASR + SLU + FSM + TTS
Typically the total latency of 1-2 seconds is good, though, the lower the better.
Embrace Metrics that Truly Measure Intelligent Conversations
Abandon call containment rate as an absolute reflection of voicebot performance. Yes, it holds value but it is not true to the purpose of creating a voicebot.
Measuring and monitoring the right metrics will help you capture precise voicebot performance and thus enable you to improve it. Only then will it result in cost and CSAT advantages that the voicebot has been deployed for.
To learn more about voice automation and how to measure and improve performance, you can book a demo using the chat tool below.
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.
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.
We have all been in dire straits and dealt with frozen bank accounts and medical or travel emergencies. We can vividly recall the palpitation and frustration felt during those moments, waiting for customer support, navigating IVRs, or a chatbot.
Companies have long wanted to change it, but challenges such as high attrition rates, unscalable teams, inconsistent CX, and cost pressures have curtailed their capability to serve customers.
Consequently, customer frustration is on the rise. A 2019 report said that customers are annoyed by the irrelevant options presented by the IVR. In fact, two out of three Americans (66 percent) say they would choose AI-powered voice-over chat if it were effective at answering their questions.
Riding the wave of recent advancements in NLP and AI, we are graduating from machines automating crude, low-value tasks to a new era where AI-enabled voice customer support would help companies create enormous value, conversing in their preferred language with semantic understanding to resolve their problems.
For Exceptional CX – Technology and Channel Strategy Matters
A Harvard Business Review survey revealed that 73% of business leaders view reliable customer experience as critical to the overall business performance of their company.
Companies now realize that multi-channel or omnichannel strategy has failed to live up to the expectations of improving CX, primarily because different customer segments prefer specific channels to connect. Thus, an optichannel or optimal channel strategy is more prudent as it focuses on the capability to support a customer journey via a channel/modality optimal for that problem.
Even today, after years of decline in customers’ preference for voice support to troubleshoot, voice is still over 50% in contact volume. Though companies may pursue an omnichannel strategy, if they are not good at voice support, they must be cognizant of its impact on CX. Optichannel is thus a more prudent strategy as being good at different modalities such as emails and chat will not compensate for the damage done by poor voice support. Companies have to choose wisely, there is no one-size-fits-all solution.
Text and Voice: Don’t Mix and Serve
Acing CX means that the company must be good at serving customers with their preferred channels. Voice is complex, subtle, and requires semantic understanding. Nuances of a voice conversation such as a change in the rate of speech, voice modulations, and more that convey a customer’s feelings are lost if your solution is not built from scratch for voice. Bundling a chatbot with a readily available Automated Speech Recognition (ASR) to add voice capability just kills the beauty of spoken conversations because it can transcribe but not converse.
Shortcuts like these fulfill notionally the goal of being present in every channel but defeat the goal of being good at the relevant channel.
Moving Beyond the Complexity of Digital Transformation with Voice AI
In the last few decades, the world moved from voice to text to chatbots. But as customers still prefer voice over other communication channels, even brands are taking notice. WhatsApp, a chat messaging platform, is building voice-led solutions for businesses. A Deloitte study reveals that by 2030 there will be a proliferation of voice-led technology across the globe and that 30% of sales will be via voice by then.
As companies hustle to achieve digital transformation, the low success rates, and disturbingly lower rates of sustainable DX success are proof of the precarious journey.
Fortunately, there is one way to not only automate contact centers with the most cutting-edge technology but also ensure that it succeeds without a big resource commitment from the organization. Yes, Voice AI is one such solution with stand-alone deployment and stunning success rates.
Companies must consider deploying Augmented Voice Intelligence for contact center automation as a good starting point toward digital transformation. But before that, brands must ponder over the most significant question – What does the shift towards voice entail as we cross the voice automation rubicon? What is its impact on the market and competitive landscape?
Look before you leap!
Only if you feel that your human agents are doing zero-value repetitive tasks, and there could be enhancement of their productivity. Your company is continuously facing resource, cost, and compliance challenges. Perhaps it’s time to contemplate and change.
For more information and free consultation, let’s connect over a quick call; Book Now!
Just over a decade ago, with our first tryst with Siri, little did we imagine its significance and how Voice AI will change customer support forever. Several generations, from baby boomers to millennials to gen Z, are using voice searches on popular platforms such as Google Assistant, Alexa, Siri, and others is a testimony of its potential. Today, we stand at the cusp of Voice-tech revolutionizing customer service.
Since speech is an integral part of being human, we covet meaningful conversation to connect and express. But today, even the thought of being stuck with Interactive Voice Response (IVRs) and chatbots in an emergency/urgent situation gives us the heebie-jeebies, right? And the long wait for a customer service agent to pick up, if at all, forges a lasting negative emotion towards the brand.
Companies have been trying hard to deliver a delightful customer experience; but with existing legacy systems, it is just not possible. The emerging answer to CX woes is Augmented Voice Intelligence that not only understands and responds but is semantically capable of comprehending the context of customer queries or problems.
For brands, customer experience can make or break their reputation. A Harvard Business Review survey revealed that 73% of business leaders view reliable customer experience as being critical to their company’s overall business performance.
The Conversational AI space has been experiencing explosive growth, and within it Augmented Voice Intelligencesits at the frontier, with the incredible potential of disrupting the way companies interact with their customers.
Why Voice-first Solutions Will Take it All!
Written language differs significantly from spoken one. Spoken content has more information, hidden in the form of pauses and pitch modulations, Chatbots bundled with ASR can transcribe, but not converse. As organizations pour millions into automated voice support, they would want their virtual agents to understand the semantics, such as sarcasm, and not take “oh, you did a good job’ at face value. Those subtle nuances of human conversations get annihilated when we strap a readily available Automated Speech Recognition (ASR) over a chatbot.
Though chat has distinct use cases it excels at, a simple conversion of text to voice and vice-versa does not meet even the table stakes of a voice conversation.
Nearly 9 in 10 people preferred speaking to someone over the phone rather than navigating a pre-set menu, showed research from Clutch. That is why the future belongs to Augmented Voice Intelligence!
Companies cannot simply use generic voice engines, as they are built for contextless conversations. Simply because a customer interacts with a company with a very specific context, and expects it to troubleshoot as skilled human support would do.
Voice-tech solutions that are built for voice, from the ground up, will be the ones delivering successful conversations. This boils down to conversing with customers within a specific context enables automated voice support to solve their problems, even complex ones, in a frictionless manner. It requires training in domain-specific knowledge at the speech recognition layer and creating different design guidelines for every vertical and for specific use cases within those verticals.
It is an uphill task, but what’s the prize for all the effort? The biggest prize indeed: Conversations that your customers will love!
The Conversational AI space has been experiencing explosive growth, and within it Augmented Voice Intelligencesits at the frontier, with the incredible potential of disrupting the way companies interact with their customers.
Augmented Voice Intelligence focuses on empowering an enterprise’s workforce by combining the power of human voice and AI. A Digital Voice Agent can easily resolve tier 1 customer service issues and automate cognitively routine work while human agents can focus on more complex customer problems.
Human/machine collaboration is the future of intelligent work. The intent is not to replace the human workforce, but to enhance their productivity by taking away the mundane workload.
The opportunities for the Voice AI ecosystem are only getting started. Data from research platform Allied Market Research showed that the conversational AI space has the potential to touch $32.62 billion by 2030, registering 20% YoY growth between 2021-30.
For brands, customer experience can make or break their reputation. A Harvard Business Review survey revealed that 73% of business leaders view reliable customer experience as being critical to their company’s overall business performance.
End-to-End Customer Support
The main applications of Voice AI or AI-enabled Intelligent Voice Agents can be subsumed into four categories:
Resolving Tier-1 Issues: All calls can be routed through the Voice AI agent, and it will be able to answer a large chunk of calls completely, without any human assistance.
Pre-Call Assistance: As the call gets forwarded to the human agent, Voice AI can fetch all the relevant information for the agent to engage in the most meaningful way.
On-Call Assistance: TheDigital Voice Agent listens to the conversation and provides instant data and help to the human agent, augmenting the agent’s capability to serve manifolds.
Post-Call Assistance: Call summary is essential for feedback, and the agent needs to fill it out. An AI-enabled Digital Voice Agent can perform such post-call activities with semantic understanding; the agent simply has to look and approve.
Think of a contact center with a seamlessly scalable team available 24*7, with agents who have customer data at their fingertips, where the quality of calls never drops and no one gets frustrated. Where personalization, relevant up-, and cross-selling are table stakes and call data analytics and feedback are available on the fly.
Sounds like utopia, right?! But this is well within the grasp of businesses, with the right voice technology solution. Now imagine the competitive edge your company can derive from the successful adoption of augmented voice intelligence.
This is the defining moment for custom-centric companies, as their voice strategy will have ripples far into their future.
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Voice has forever been the preferred means of communication, and today the global shift towards voice is becoming more conspicuous. It has become increasingly popular across generations and geographies. There are 135.6 million people in the US using voice search features, and as of 2021, nearly one in three (32 percent) US consumers own smart speakers, according to Statista. Consumers are using them for shopping, searches, and much more. Studies have found that today, even voice ads are an engaging multitude of users. Over half of all online US shoppers and 40% of the US population use voice assistants to explore products (Narvar, 2018).
The rise is visible across the globe. In India, for instance, the number of people using voice queries daily on Google is nearly twice the global average. With higher consumer adoption of voice-led searches, its incorporation in CX strategy is now a business imperative.
By 2030, there will be a proliferation of voice-led technology across the globe, and 30% of sales will be via voice, a Deloitte study revealed. These are disruptive times, and as MIT research seconds, the risk of not investing in technological capabilities during downturns is nothing less than existential.
In the new normal, competition has intensified over the capability of companies to deliver CX. Until now, IVRs and chatbots did help in improving CX in a limited way, but an enormous value gap and the chasm of unaddressed challenges remain. The traditional bottlenecks are still constraining the ability of organizations to serve customers. Scalability of the support team and cost pressure are the top two debilitating challenges. Given the plateaued capabilities of present legacy systems, companies have begun to pin their hopes on new technologies such as augmented voice intelligence that can help them break the status quo.
Mounting Challenges of Customer Support
In the new normal, disruption has resulted in the rise of customer support expectations. Here are a few focal pain points:
High Attrition Rates: Even the best contact centers struggle to retain.
Unscalable Teams: It is near impossible to match the ebbs and flows of call volumes with support team size.
Faltering CX: IVR only resolves rudimentary tasks, rerouting customers to nightmarish waiting lines for human agents to solve their problems.
Cost Pressure: Infra, training, retraining, and retention efforts cost a fortune.
Consequently, customer frustration is on the rise. Nearly 9 in 10 people preferred speaking to someone over the phone rather than navigating a pre-set menu (IVR), showed research from Clutch.
Assessing the Tech Solutions Available Today
Technology has always had the answer to most business challenges. Here are the tech solutions available today:
IVRs: They had been game-changers when they came. But most IVR implementations are created with the objective of reducing call volumes or preventing callers from getting to an agent. They do not differentiate between customers or their intent, leading to time-consuming and frustrating systems. Also, confusing navigation and terminology with poor integration capability with other channels is a big miss at value creation. IVRs still create value, though in a limited way, and maybe apt for companies where customer experience is not a priority.
Chatbots: For companies looking for a cost-efficient solution whose products or services have a Non-linear User Journey a chatbot can be an effective means. They have been here for a while and owe their popularity to-
Increasing demand for self-service
Are easier to train
Ability to give 24/7 customer assistance at low costs
Can engage audio-visual media
But they too have their shortcomings – they miss out on two core pillars of customer experience, i.e., emotions and ease of use. It is impossible to convey emotions over text for ordinary folks. Also, it is taxing to type repeatedly, especially if the customers are not tech-savvy, too young or old, or in atypical situations.
Voicebots: A meaningful conversation can light up the darkest day! And in customer support, it is even more critical as consumers call their providers with the hope of speedy resolution.
Today, tech advancements have made Voice AI Agents capable of executing biometric authentication and looking up all the relevant information when a user calls from their registered mobile. With data handy, the intelligent voice agent then uses it to quickly solve customer problems with only a few sentences exchanged with the customer. It is the holy grail of customer support, and now with augmented voice intelligence, it is possible.
Changing itineraries, travel plans, canceling or booking tickets, registering complaints, or changing mutual fund portfolio allocation are tasks that can be accomplished with no waiting lines or tedious conversations. There is nothing more satisfying than voice conversations because it’s natural, intuitive, and gratifying.
Augmented Voice Intelligence Vs. Google Assistant, Siri, and Alexa
Alexa, Siri, or Google Assistant are the gold standards of voice automation, but they are built for generic conversations, answering any type of query from almost any language. Revolutionary that they may be, they are not suitable for customer support because the expeditious resolution of customer problems requires a solid foundation of context.
An Intelligent Voice Agent, powered by AI, is trained for thousands of hours on specific customer problems. They understand the vocabulary, the decision process, and what solution to propose. Most importantly, unlike the most popular search engines designed to provide one answer, intelligent voice agents are capable of multiple rounds of questions and answers. For customer-centric companies, Voice AI is a suitable solution.
Listen to Voice AI Agent In Action
Voice-first Solutions Will Transform Contact Center Automation
Written language is significantly different from the spoken one. Chatbots bundled with Automated Speech Recognition (ASR) can transcribe but not converse. When it comes to voice, only pure voice solutions, built from ground up for voice, will be able to deliver tangible business outcomes.
As organizations pour millions into automated voice support, they would want their virtual agents to understand the semantics, such as sarcasm, and not take “oh, you did a good job’ at face value. Those subtle nuances of human conversations get annihilated when we strap a readily available ASR over a chatbot. A simple conversion of text to voice and vice-versa does not meet even the table stakes of a voice conversation.
The attrition among call center employees is the highest. Seamless collaboration of human and machine intelligence is the future of work. Voice AI is perfectly poised to augment human agents and multiply their capabilities.
How? As intelligent beings, we prefer to do meaningful tasks that create value. By taking away a chunk of repetitive and low-value tasks an intelligent voice agent helps human agents focus on significant and complex tasks. Also, it provides information in response to the contents of the conversation, assisting them to perform remarkably better and feel engaged with their work.
Take Your First Step
Brands have to ask themselves – What does the shift towards augmented voice intelligence entail for their market? How can they use voice as a growth engine? Here are a few outcomes organizations have achieved by deploying Augmented Voice Intelligence:
Up to 70% automation of customer support efforts
50% reduction in operational costs
Over 4.5 customer satisfaction scores
Up to 40% reduction in average handle time
Enabled analytics-driven informed decisions
If the answer to the questions below is a “Yes”, you should seriously consider incorporating augmented voice intelligence:
Are your human agents involved in zero-value repetitive tasks?
Are you facing resource, cost, and compliance challenges continually?
Do your talented agents feel they could perform manifolds more with proper tech support?
Is customer experience at the core of your business?
Never before has investment in Voice AI made more sense. The advancements in NLP and AI have enabled companies to move from crude automation of non-value tasks to the epoch of Augmented Voice Intelligence, assisting companies to create value by automating customer support and enhancing CX with multi-language support with semantic understanding.
The voice strategy of customer-centric companies will have ripples far into their future. After all, vox dolor, vox Dei, i.e., the voice of the consumer, is the voice of God.
For more information and free consultation, let’s connect over a quick call; Book Now!