Webinar: Increasing RPCs with Authoritative Phone Intelligence for Collections

Now let me tell you a little bit about today's speakers. Mitchell Young is an executive director of Identity Risk — excuse me — Identity Risk Solutions at Neustar, where he oversees the collection, utilities, tech and internet, call center and data verticals. Mitchell has been at Neustar for more than 15 years helping companies leverage real time identity data and analytic insight to improve operational efficiency and manage risk and compliance. Prior to joining Neustar, Mitchell was a senior director of risk at Target's info which was acquired by Neustar in 2011, where he helped develop several markets. Mitchell has an undergraduate degree from Penn State, and an MBA from New York University. Also with us today is Matt Wolk who is a senior director at Neustar risk team. Matt is a 21-year veteran of call center analysis and operation, specializing in the outsourcing of collections and risk to improve revenue performance for both clients and vendors.

This event is being recorded, and a recording will be made available in the coming days on accountsrecover.net.

Let me take a quick moment and say a few words about Neustar. Neustar is a leading global information service provider driving a connected world forward with responsible identity resolution.

As a company built on a foundation of privacy by design, Neustar is depended upon by the world's largest corporations to help grow, guard, and guide their businesses with the most complete understanding of how to connect people, places, and things. Neustar's unique, accurate, and real-time identity system continuously corroborated through billions of transactions empowers critical decision across its clients enterprise needs. With that, I'm finished with the introduction portion of today's event. Let me introduce Michelle Young to begin today's presentation. Mitchell?

Thank you, Mike. Thanks to the accountsrecovery.net for hosting. We're glad to be here today. I am here with my colleague, Matt Wolk, and we were typically going to split up some of this presentation, and Matt, I think it was some allergies, lost his voice. So he's here with me for any color commentary he might add. But I'll be leading the webinar. So a few housekeeping items as we get started.

The webinar should run 35, 40 minutes long in content, and then we will open it up for any questions. It is structured in two parts. So the first part, we'll talk a little bit about identity data, talk a little bit about the Telco industry and some of the trends that we're seeing and some of the regulatory trends that we see not just for the collections industry but in the telco world, too, where we do a lot of work. And then the second half — and stay tuned, or stay for this part of it — we're going to walk through some data analyses and some actual client performance and impact that Neustar has been able to bring to companies in the collections area. There are about a hundred people signed up and logged in for today, so I think a great topic.

Importance of identity data across industries

For those on, you have a lot of peers also interested in this topic. As we know, it's the lifeblood of the collections industry and effort. So let me dig in. As Mike mentioned in his introduction, I run our identity solutions group within Neustar. And I have the benefit of overseeing several different vertical markets. And I think it's interesting because there are similar challenges facing each of these markets. Not just do we work in collections, but both working with first-party and third-party collectors, but we work in the utilities industry.

We do a lot of work in the banking with large financial services and companies. We do a lot of work with consumer services, health care services, lots of companies in different vertical markets that are all trying to reach their customers, whether that's to give emergency notifications of power going out or fraud alerts for a credit card or a bank account, or it's time to take your medication today, or within the collections industry you have a debt due and a balance owed. For all of these industries, using the phone and reaching out to customers is a core part of their communication effort. And what we see are these prevailing forces that are challenging companies across the board in their efforts in reaching out to companies.

Collections industry

Certainly, regulatory in the collection industry has been one of the biggest drivers over the last month, both CFPB regulations and FCC, at least proposed regulations from both of these. And we'll talk a little bit about those. There's also ROI constraints. Everyone has businesses to run. And reaching out to customers is both part of that business, and there's costs associated. So how you do that efficiently and manage the business is critical across the board. And fraud's another one. And fraud is not one that is necessarily specific to the collections industry, but fraud is a big one that consumers are plagued with.

Utilities and outbound calls

In the utilities area, lots of customers are getting fraudulent calls saying they need to pay a bill today or their power is going to go out. Or there's lots of spoofing that happens. And it impacts collections because consumers are less and less likely to answer the phone. So not only is having current and accurate data important, but also understanding where consumers' heads are and the lack of trust today that exists in the phone channel is just another challenge facing all companies that are trying to reach consumers today.

Shift in quality over quantity

Within the collections industry, for a long time, the goal has been, just give me a quantity of phones, and I'll keep dialing. We've seen a shift towards quality. I think the legacy providers of phone data in this industry have really focused on providing quantity. And we've seen that shift to quality. I think the interesting thing in the collections industry is the industry's been so efficient that quantity of data made a lot of sense. I think where things have been moving in the last few years — the quality of data is becoming paramount for everybody's business.

So across all these industries that we serve, we tend to see, still, 88% of business calls go unanswered on average. And this is across first party, third party, and across all the industries I've been talking about. We still see very low RPC rates. Now, within the collections industry, certainly, third party 3% RPC rates may be a goal to aspire to. But across the board, they're pretty low RPC rates. And it is the confluence of all of the things I've just talked about, regulatory demands, bad data, and the lack of trust that the consumers have that are keeping RPC rates down.

The other thing that we know about bad data is bad data leads to inefficient operations, all of the key metrics that you measure in terms of RPC rates to promises to pay and just dealing with your workforce. We've often talked about the outbound dialing effort as a game of battleship. And if you think about the game of battleship, for people that have played it — it's a classic around for decades — is the collection industry has always been so efficient that they could say, just keep giving me bullets or pegs. The pegs are phone numbers. As long as I get enough of them, I'm bound to hit the ships that I'm looking to reach.

And what we know now is that that strategy, while the industry is efficient enough to execute on that strategy, the unintended consequences of those stray pegs is no longer acceptable. TCPA has made those no longer acceptable. And some of the recent proposed ruling by the FCC is pushing, more and more, to say, hey, you need to get the answer key to the battleship game, right? The recent proposed ruling on limiting calls to seven per week or limiting contacts to seven per week — I'm not going to go into the details of it. But I think the message is the shift is going to continue to quality and continue to accuracy. And if we stick with the analogy of the battleship game, it's basically — no longer is it just buy more pegs is the answer. Now, it's, hey, I want the answer key. If I can get the answer key, I can have unlimited pegs. And those are your phone numbers and your phone calls out.

So from a consumer data perspective, having good data is fundamental to being able to execute with quality and have the answer key to that battleship game. But we know this is a challenge. It's a challenge for first party. It's an even bigger challenge for those in the third-party arena. And this is some of the reason. These are some of the trends that we know of in the phone industry as we're managing — we have a view into all the porting that happens on a daily basis, all of the phone numbers that get disconnected and connected on a daily basis, and people that are moving.

And you can see it's a massive amount of change every year, I think the critical one being 45 million consumers change their phone numbers every year. So very quickly, any time one of these events happen, your records become out of sync and out of date. And it's very hard without seeing these signals on a daily basis, like Neustar does, to be able to update and maintain a current CRM system, or a Contact Records system, for your customers.

Increase in mistaken call blocking

The other overlay on top — it's not just having current data, but even if you have the right data, your consumers may be seeing this when you call. We have seen a huge increase in, across all of the major carriers, spam tagging and call blocking that's happening. And in all the industries that we serve, it's similar. All the companies that need to reach out to customers and use the phone as the channel — they're getting caught up in the unintended consequences of these carrier efforts, where it's not just call spoofers or robocallers that are getting tagged for spam, but it's legitimate businesses following all the regulatory guidelines who happened to do a high volume of dialing that are getting caught up in these spam filters.

And recently, we see that this particular issue is going to get much more challenging for those making outbound calls because the other regulation that you may or may not have seen it, which came out in the middle of May, was another proposed ruling of these anti-robocall tools getting pushed by default rather than a current opt-in model. So what that means is, for certain carriers, you need to opt into spam tagging.

And please know, robocalls is the number one complaint to the FCC every year. So they are pushing the carriers to address the robocall issue. The challenge is legitimate businesses are getting caught up in those efforts. And the suggestion by the FCC to make all of these spam tag capabilities pushed by default rather than opt in is going to quadruple the impact that you're seeing today in the marketplace. So if you've addressed it, great. If you haven't or don't think it's impacting you, it likely will in the coming year.

So given the things we just talked about and the challenge, we still know that the key questions everyone wants to answer is who to contact, what phone number to use, when to contact somebody, and how do I avoid call blocking so my efforts aren't for not. And Neustar, we feel, is in a very unique position to help companies answer these questions. We work with lots of companies in the collection space today. It's from our work within the telecommunications industry and some of the major work we do as a partner to the telcos that gives us insight that can help us answer these questions. And we'll talk a little bit more about those as we move into this next section.

Improving right party contact rates

Ultimately, we're seeing great improvements in right party contact rates using a combination of different solutions. We'll talk a little bit about what those solutions are, and then we'll look through some case study results of impact that others have seen. So right before we dig into the different solutions, I'll give a little bit of an overview of where Neustar gets its insight and why it happens to be unique. We power some massive registries today. We power a lot of work in the telecommunications industry, a lot of work in the ad tech industry.

Neustar is the largest provider of caller ID services

So as companies are moving more to look at digital communications, we have really unique insights there. But for the core of what we're going to talk about today, it happens to relate to our telco business. Neustar is the largest provider of caller ID services in the US. Over 90% of all the calls in the US where a caller ID is involved, which is most, is done through Neustar and through the caller ID database that we manage on behalf of the telco industry.So it's unparalleled coverage across all different types of phone, whether it's VoIP, wireless, landline, public, non-public, and really unique insight into the activity of billions of call transactions every month. So it's not model data. It's coming directly through the individual's phones and calls happening in the telco ecosystem. It's really similar to credit bureaus that get trade reporter data directly about credit information as a great source for credit data. Neustar is very similar, where all of our data comes directly from the telco industry and its authoritative sources on phones and phones that are active or disconnected.

So it's unparalleled coverage across all different types of phone, whether it's VoIP, wireless, landline, public, non-public, and really unique insight into the activity of billions of call transactions every month. So it's not model data. It's coming directly through the individual's phones and calls happening in the telco ecosystem. It's really similar to credit bureaus that get trade reporter data directly about credit information as a great source for credit data. Neustar is very similar, where all of our data comes directly from the telco industry and its authoritative sources on phones and phones that are active or disconnected.

More accurate phone calls with lower risk

So how our solutions work — from an outbound dialing perspective, we have solutions that look at de-risking your efforts and optimizing your efforts. De-risking is really simple. It really has to do, mostly, with TCPA, which, for this industry, we've tackled over the last five years and really helped people understand, does this phone still belong to somebody, and is it wireless or landline? Pretty straightforward.

Where it gets more interesting is understanding, in the blue category, these different rows of optimization, which are, are my customer records accurate, complete, and up to date? What's the best number and time of day to reach a particular person? How do I avoid my calls from being blocked or spam mislabeled, and how do I improve my odds of calls being answered? And we have solutions that address every one of these questions, and we'll talk through some of those. I think they're very straightforward. And because they come from authoritative data, they're very powerful.

So how they work — and these are some simple graphics, but I hope they illustrate the point well — is, very simply, we know, in the clients that we work with today, they have primary phones. They may have multiple phones. But for this illustration, we see a primary person per account number. And our response may say, hey, this particular phone you have is a really high-usage phone. It's wireless. We see it very active. Or we see a phone that's — there's no usage at all. We have ways to say, well, we're not seeing anything around that phone, or a landline phone that may be really low usage. And very simply, those types of behavioral attributes correlate to a dial priority.

Phones that are wireless and high usage have much better contact rates, RPC rates, and ultimately lead to promises to pay. Those phones that have no usage — all they do is spin. They never actually get answered, and they don't yield you any results. So those are phones you can de-prioritize. I think where it becomes a bit more valuable is when we look within a particular account, and someone may have five phones. And the challenge is they don't know very much about these phones. It could have been last in as the first one I use. But there's not a lot of true behavioral insights around any particular phone number.

So what Neustar's able to do is bring actual behavioral insights about a phone for optimal prioritization. So we may take a set of five phone numbers and reorganize them so the best phone number is one you can use first and reduce that time to an RPC and reduce that time to, hopefully, a promise to pay and a resolution. And I think this is aligned with the CFPB proposed ruling of looking for organizations to make fewer calls. And the way to make fewer calls and still have success is to have the right phone numbers for an individual and move to the answer key to the battleship game, rather than just buying all these pegs of phone numbers, which may or may not yield you any meaningful results but are creating a lot of frustration amongst consumers and perceived robocalling.

Power of authoritative phone data

The other thing that authoritative phone data allows us to do is to say, hey, the phone numbers that you happen to have — you actually don't have any good ones now, and we can give you phones that are highly contactable, ones that we know are active, that belong to that user, that haven't been disconnected, that can still yield you results as long as you're dialing within the correct regulatory guidelines, which we know people are.

So those answer some of the questions of, who do I call, what phone number do I use? And now we start thinking about, well, when do I call? And for the most part, people are dialing within normal business hours or during the day time. The thing that we see here that we can show is that we know when it's an optimal time, when it's most likely to be able to reach a consumer during the day, based on call windows that we see where you can likely reach a particular consumer.

So the yellow here is where we see the largest difference between someone's actual effort and the optimal effort we would suggest. So the good news here is it doesn't require a wholesale change to how people are operating today. But it may say, hey, put more effort in different times, or it may be that this 20% of calls should be here, right? The people that you're calling from 12:00 to 2:00 — you're actually more likely to reach them from 4:00 to 6:00. So let's just move the right people to the right call windows, and let's put the right amount of effort during different times. 8:00 to 10:00 is not really an optimal time to reach people. 10:00 to 12:00 is much better. So let's flip around some effort.

The types of intelligence that we can provide is, for a particular phone number, we believe the best time to call in a given day is a particular two-hour window. And it may be different for different days. People may work different shifts. People may work different days. And we can see a correlation to phone patterns and behaviors and usage to when it's most likely that you're going to reach them on the phone.

The other question we can help to answer is, how do I remove spam tagging from my phone? We've done a lot of work with companies, and this is often the type of analysis we see, where lots of phone numbers that are high-volume phone numbers are getting spam tagged across all the major carriers. So even if you have the right phone, even if you know it's active and in use, and you call it during the right time, if potential spam shows up or suspected spam or nuisance likely shows up on the handset, on the phone, it's really unlikely that somebody's going to answer that call.

Removing spam tags

These are the unintended consequences of the carriers trying to do a good thing on behalf of their consumers. These spam tags can get removed. We can work in partnership with the carriers to identify legitimate businesses that shouldn't be caught up in some of the pretty simplistic filters that are happening, but appropriate. They're based on volume. So sometimes people look at one number. One number may have 90% of your outbound dialing. Here, it's 14 top numbers representing 85% of all outbound calls and creating more challenges for you to reach consumers.

So with that — and I went through it quickly, but it's pretty straightforward in terms of helping you answer questions of who to contact, which number to use, how do you really prioritize the number that you have so you can get quicker contacts, quicker RPCs, and reduce the duration of time it takes you to get to your promise to pays, when to contact them so you're more efficient, so you can actually get them to answer, maybe, in the first time that you call or second or third, and then you'd better align with proposed CFPB rules, and then to avoid call blocking, so when you put all that effort into getting the right numbers and dialing at the right time, your call doesn't get blocked and not answered by the consumer.

Value of better phone data intelligence

So that's a capture of what we're seeing in the industry, the challenges around data today and its ever changing-ness, and some of the solutions we have to help companies improve their operations and answer these core questions. I'll shift now to the second part, which is really looking at some performance data across a few anonymized data analyses and clients that we work with. And hopefully this is helpful in understanding the value that others are seeing and the value that it may be able to bring to your organization.

So we focus on a combination of variables that correlate to increased RPC rates. And there are four core of them. The first one is phone type, understanding if a phone's wireless or landline. We see much higher RPC rates with wireless phones than landline phones. The other is verification. Does this phone still belong to this consumer? Certainly, the first two were the attributes that solve the TCPA question, or TCPA guidelines, to make sure to auto dial you had the right phone.

These are still predictive as it relates to contactability and RPC rates. But what's become even more important is just, is the phone still in use? And we can look at usage over two time periods. We look at phone usage over the last 12 months, and then we look at phone usage over the last two months to ensure that the phone is still active and still being used by an individual. This is not model data. It's specific to a particular phone number. We see the combination of these results has tremendous power.

Contactability scoring examples

So we'll walk through a few of the scores. There is a lot of data that I'm going to show through this, but hopefully I'll try to key in on the few points that I think are most relevant. So the way that we've built our contactability score is by leveraging the combination of phone type and verification, phone usage over two and 12 months. But I think the biggest point is where you get a simple contactability score, which is A through K. And green, yellow, red starts to indicate where we see best performance and where we see a lack of performance.

I'm going to move right into the results. I think it'll be more helpful. So from a contactability score perspective, for this particular analysis what we saw is there really wasn't much prioritization put on the phones. All these phones were dialed somewhat equally, even though we could see that they fell in very different score ratings. The percent of the dials was all over the place. Different segments we saw — F styled at quite a high rate, Js at quite a high rate, Cs at a high rate in terms of just number of dials for this particular portfolio.

The RPCs is interesting, is where we always see a trending, right? As and Bs perform the best in terms of percent of RPCs, Cs and Es and all the way down into where Js and Ks are barely giving any RPCs for the effort. And the RPC rate trends similarly. Es are all landline phones. It was a smaller population, so there was a good — the RPC rate wasn't bad for this particular population.

But you can see it trends and distributes appropriately across these contactability scores, where what we can see is about 98% of all the RPCs came from about 70% of the dials — great in terms of time to RPCs and time to promise to pay, reduced duration, great in terms of reducing the effort.

And you may have one account that has a J and an A and an F, and you're dialing phones here and not getting through and finally get through on an A. So we can help focus the efforts. Basically, the As and Bs and Cs start to lean towards the answer key to the battleship game, where Js and Ks are just throwaway pegs. Very rarely are they going to get you to a ship on the other side that you're trying to get to.

I will keep walking through some of this. And then where we can redeploy this effort up to the As and Bs and Cs is where the game really is. And that's what this is meant to show, where if we can help reallocate your dialing, there's significant RPC lifts and significant improvement in operations. So on the left-hand side, this represents the current dialing strategy. And if I'll highlight an area here, 46.9% of dials were on phones that were either an A, B, C, or E. 22% of dials were on phones that were J and K.

So the new strategy is zero dials go to the Js and Ks, and all of that additional dialing effort goes up to phones that are somewhat in the A through I category. They have similar RPC rates, and it increases the overall RPCs for a particular effort from 1,031 to 1,518. This comes through focusing efforts on the best phones and also through additional phones that are appended and provided by Neustar when you can trade a J or a K for an A or a B. And that's where we see overall improvement not just in efficiency but in overall RPCs.

In terms of our appended services, this is an overview of the phones within a particular analysis that we did. And these are a few different analyses that we're sharing. So it's not all the same one, if you were trying to follow along and connect them. So what we saw in a particular portfolio of 98,000 phones is that they distributed it this way, more phones in the I, Js, and Ks than in the As, Bs, and Cs. In terms of the percent of phones, you can see roughly here, majority of phones down in this I,J, and K area.

In terms of RPCs, we still see the majority of RPCs coming through these better phones, rather than through the Is and Js and Ks, right? And RPC rate trends, like we saw in the last analysis, were much higher RPC rates in these phone numbers. So what we're able to do is to take all these phones and now start to append additional phones for improvement.

If we have As, Bs, and Cs, if the original distribution of phones is, as you can see in this column — after we're able to append the phones that we have, accounts that have 11.7% percent of phones as an A — they increase it to 17.1% A, and again, increase in the Bs, increase in the Cs, and try to really put effort up in the As, Bs, and Cs categories. So this is a pretty significant percent change in phones across these different contactability score ratings. The whole goal is to increase the number of counts with highly contactable phones and decrease the accounts with underperforming phone numbers.

In another analysis — and this is just another way to illustrate this — we were able to bring a 26% lift in green phone numbers, those that are As, Bs, and Cs, which yielded more answers and more appointments in this particular example. I'll keep moving through these. And again, it's a lot of data, so I hope the pace is OK. Matt or myself or others on our team — we're happy to walk through this again one on one if it's too much to digest as we walk through it.

Phone behavior intelligence suite

The next set of data is our call window, which is part of our phone behavior intelligence suite, which is to say which window of time do we think is optimal to reach a particular consumer. And what you can see here is, again, we tend to see the 8:00 to 10:00 range where a lot of people are getting started trying to make those early calls. We think that it's not the optimal window, at least in this portfolio as well, and again, less calls at 6:00 to 8:00 as the day was winding down where we think there's a lot of upgain there to happen.

Again, not much change in the middle, except let's make sure that the actual accounts that are being called during a particular window are actually the right ones. So there could be some shifting around of who's dialed from 10:00 to 12:00 versus 4:00 to 6:00 on any given day. And the value of that — what we see is that RPC rates — when you dial in the optimal window, RPC rates are higher. This is meaningful impact. It's not the same impact as the contactability score. We think this is more of fine-tuning for those organizations that have the capability to be able to leverage a call window solution.

So when people dial in the call window, we see improvements on overall RPC rate. If you dial within two or four hours of that call window, we see good performance. Where we start to see a drag on performance is if we think it's 4:00 to 6:00 and you're dialing 8:00 to 10:00. We start to see that drop-off in performance. And especially if there's no call window at all, we see less of a performance. So there's just gain to be had if you can initiate a call during that optimal call window.

And this is a view of a reallocation of that strategy based on call window. So for this client we were working with, they were only dialing 12.6% of their dials during the optimal call window. 19% and 25% were two or three call windows away. There was a huge shift in dialing during the optimal window or within one window away and just shifting things around. And ultimately, the yield was 0.38% increase in RPC rates, or a slight increase in overall RPCs, and for a meaningful result, as this company was looking to fine-tune their operations and minimize the number of dials that they had to make to get to an RPC, which is the two aspects of this that we're trying to improve, both the operational effort of the time it takes to get to a resolution and the number of dials that it takes and increasing RPCs along the way.

SPAM tag solution

And the last piece is the impact we've seen from removing spam tags. So our spam tag solution does two things. It looks at caller ID, where you can actually control what it says on the caller ID when a consumer receives an outbound phone call, and two, removing the spam tag overlay that may exist. So for this particular client, the first week was looking at their caller ID changing.

They were at a 6.1% call answer rate. We weren't looking at RPCs. we Were just looking at overall answer rates for this particular analysis. That gave them a slight lift, up to 6.5%. And then we began to register their phones. That takes a few weeks to kick in and actually work with all the carriers and really make sure phones are clean and spam tags are removed. After that two-week period, we saw an increase to 8% live call answer rates. It was about a 33% lift.

So this particular solution requires very little effort on your side, except for phone numbers to be provided that can be managed by us to remove those spam tags. Doesn't require any operational effort on your side, any programming, any change of resources or anything. Again, as you manage data and you get that answer key to the battleship game together, you also want to make sure that the spam tags aren't preventing you from sending those pegs over and landing on the ship.

So we can shift now to questions. So that was a lot of content I know we walked through in just over 40 minutes. So I hope it was helpful. I hope it maybe raised some light bulbs or some questions for folks. Again, we're happy to do similar analyses for anybody. We have a data analysis team set up that works with clients to do initial lookback tests, which are getting a sense of, do you perform similarly to other clients that we're working with where we think we can bring similar results? And thank you for your time. I'll pause now and open it up. Maybe some questions came through. Jennifer and Mike, you are helping the manage today. And Matt and I are here to answer any questions.

Absolutely. Well, thank you very much, Mitchell. That was a lot of information, but it was incredibly insightful. So thank you very much for taking the time to share it. The questions are starting to definitely roll in now, so let's try and get through as many of these as we can. Are you able to see any data that suggests that the National Do Not Call Registry affects some of the data that you are describing, or is it negligible?

Does the National Do Not Call Registry impact the data?

Well, the National Do Not Call Registry doesn't impact the data that we see. So we have those flags. We're familiar with it. We know which phones are on the Do Not Call Registry and which aren't. But that doesn't impact the behavior that we see. So when phones are making calls, and they're transacting on the telco network, there's nothing from the Do Not Call Registry that would hide any of that or prevent caller ID from getting queried, so yeah.

OK, a question — I'm wondering if you or Neustar has a presence in Canada.

We have a small presence in Canada, but it's somewhat different. So we don't have the same type of some of this behavioral insight in Canada because our caller ID business is really focused in the US, so some phone data but not in a meaningful way as it relates to the solutions that we reviewed today.

Do identity data strategies work for smaller volumes of calls?

OK, a question wondering if the strategies you talked about today work for agencies that make a smaller volume of calls.

Well, sure, the volume of calls doesn't necessarily have a relation to the impact of them. Ultimately, you may not experience spam tagging if you are making a lower volume of calls. So that one aspect of the solution may not be relevant. And we can test for that and see if you're spam tagged or not. But ultimately, we're just talking about accuracy, right? We're talking about data quality and accurate data and behavioral performance data that can impact your organization. So whether you make fewer calls or not should not impact the efficacy of these solutions.

Got it. OK, a question wondering, with respect to the right party contact that are being recorded, are you able to distinguish between an actual live caller who's picking up the phone or certain apps that are out there that act like an RPC?

Hm. I'm not sure that I'm familiar with the apps that act as in RPC. And our solutions don't do anything around call tracking or what you would indicate as a wrong party or a right party or what that answer should be. So we rely on the performance attributes that our clients provide us and correlate that to our data. So ultimately, the data we have is from within the telco world, and it relates to whether phones are connected or disconnected, who owns them, and are they used. And what a consumer may have set up on their end to answer their phones is not part of the intelligence or insight we have.

How can we segment data to maximize our RPC rate?

Got it, OK. I did a webinar recently, and one of the executives was talking about doing an analysis of the ideal time to call, which I know that's part of what you were talking about today. The analysis that this particular agency did was that everybody wanted to be called between, say, 10:00 and noon in the morning. Now, obviously an agency can't call everybody at that time. They don't have the bandwidth to do that. So I'm wondering what advice you would have had for this particular person on how to further maybe segment out their data to identify other times to try and get that RPC rate as high as possible.

Well, that's a great question. And we've seen two things that can help with that, actually. So if you think about phone numbers — and I don't know how they were conducting that — we're looking at actual behavior of a phone number, so when do we think that person's likely with that phone, where we think you can reach them. Now, the good news is high-usage phones tend to be with people all the time.

So from that perspective, if you don't want to focus on what we think is the best window, you could say, you know what? High-usage phones — I'm just going to call them as I have capacity. But what I'm really going to focus on is optimizing the phones that are low usage, because those people may not have them with them all the time. Maybe they work on a line, and they just aren't making phone calls. Or maybe they don't use their phone that much.

So if I can really focus my effort on just reaching the lower usage phones at the optimal window, we think that's really a great way to improve contactability rates and RPC rates. And it's not a huge impact on your operations, right? It's not saying every phone number needs to be within an optimal window. It's saying only the ones that I think are going to be the most challenging to reach, but I believe to belong to the right person, am I going to try to optimize when I dial it. And it's a great way to leverage the insight without trying to say all my dials have to be within 10:00 and 12:00, because no one can staff for that.

Is there a perfect outbound number strategy?

Right, exactly. We've got a few questions that have come in about the outgoing phone number that a company should use when making their calls. Should it be a toll free? Should it be a local number? Do you have any insights into that aspect of the equation?

People are talking about that a lot, and I don't. It's not the area where we've done tremendous testing. We've had these conversations with our clients as people are incorporating our insight. And I think there have been some that love the local numbers. There are some that are shifting away from it back to an 800 number or back to their main numbers. What we're able to do is provide a portal to manage your caller ID if you want, so it's really easy to do A/B testing. It's somewhat complicated, often, to manage your caller ID across a multiple of phone numbers which may come from different carriers.

You may have it outsourced to certain call center companies. We have a portal that allows you to manage your caller ID along with removing spam tags that just give people the ability to do A/B testing so they can really test to say, hey, what works best for your particular population that you're dialing? Some, it may be a local area number. Some, it may be an 800. Or some, it may be a very general caller ID. Some, you may want your company's name because you have an ongoing relationship. So I don't have any guidance on what we think works best, except maybe some reassurance that everyone's dealing with that one right now.

We're all in the same boat together. One of the conclusions that I found really particularly interesting is that it's not just about making the right calls, but it's as much removing bad calls that can help increase right party contact rate. So I'm wondering maybe if you could just spend maybe another minute just talking about that dynamic within a collection agency, that there always has been this dialing for dollars and, like you said, more quantity over quality. But I think the paradigm does seem to be shifting. And I just wondered if you could just that again for a minute or so.

Yeah, I think there's two aspects to it. One, we've seen the evolution over the past seven, eight years since all the TCPA lawsuits came in where, all of a sudden, there were consequences or collateral damage for all of those pegs that went into the open water where there wasn't a ship in the battleship game, right? It used to be there weren't any consequences. TCPA made consequences for those wrong dials to wrong people.

And what we're starting to see with the recent CFPB proposed ruling is just a further shift towards demanding quality rather than quantity and demanding that, if you want to reach the right people, you have a limited effort to do it. So for everybody on the phone, that means good data becomes critical. It wasn't so critical before. I mean, the industry was so efficient, incredibly efficient. And when unintended consequences didn't matter, you could get by on that efficiency. And I think we're seeing the continued shift or evolution towards quality and accuracy really mattering.

Potential impact of STIR SHAKEN

The other side of that is everybody's getting bombarded with so many phone calls, and no one has any trust anymore. So that's a consequence of lots of dialing over the time, too. And a lot of it is robocallers and fraudsters and stuff not originating from this industry. There is this big shift or this big effort coming out. I didn't talk about it today. It's called STIR-SHAKEN, and it's a telecommunications effort that we're working on. We've built the test bed for the telco industry.

But it's basically a certification to say, hey, this call that's coming in is actually a certified call. And over the next few years, you're going to start to hear about attestation and certified phone calls so it can bring some trust back into the world of phone calls. So that's more of something that's to come, something that Neustar is a big player in in partnership with the telco industry. But I think that that's going to help, too. It's more of a long-term play.

Does agency size impact RPC rates?

OK. We had a question before about the size of the agency impacting RPC rates. And I'm just curious. Does the type of debt or size of debt have any impact, or is that separate from impacting an RPC rate?

Yeah, we haven't done that kind of aggregation across the industry to look at trends across size of debt. We see better performance, of course, with first party than third party just because the data itself is much more aged, and there gets a lot of appended data mixed in. Matt, I don't know if you're on, have any thoughts on that. But I don't have any particular insight on that one.

Yeah, I'll try to speak as best I can. We have seen a number of different analysis. And as we all know, portfolios perform at different RPC rates, connect rates, liquidation rates, et cetera. So the performance lift that you're going to see is going to be relative to what you've seen in the past. We've seen lift in RPC rates from 15% all the way up to 75% and 80%. And again, those are two extremely different types of portfolios.

So the portfolio you're dealing with is going to dictate — and to Mitch's point, the age of the portfolio — is going to somewhat dictate where your starting point is. But in any case, providing that better data is always going to yield you a better opportunity to get in touch with that person and to get that right party contact faster, drive liquidation faster, and move up revenue into the liquidation curve. As we all know, scorecard is still king in this world. And as long as it is, performing on those batches and driving those RPCs is going to be the most important thing.

Excellent. Thank you very much, Matt. We did have a couple of questions requesting a copy of the presentation as well as the integration information. I'm sure that, by reaching out to Mitchell or Matthew using the contact information on the screen, they'll be more than happy to provide or talk more about that information or share the presentation with you. I think that's all the questions that we have in the queue. Before we wrap up, Mitchell, just in case, to give people one last chance to ask a question, maybe you want to just summarize your remarks today or any other key takeaways, or maybe talk about something you didn't get a chance to talk about but thought was important, but just to provide any parting words of wisdom.

Key takeaway on data intelligence

Well, thanks again, Mike, and thanks for everyone that hung in there with us. No, I mean, I think we covered a lot of ground. I like to make it as simple as possible, and I've used this analogy a lot. I think we like to say we have as, much as you can get, the answer to the battleship game, where we can give you the answer key in terms of intelligence and accuracy. So with the proposed regulations that are coming and the push to being accurate in everybody's efforts, we can help you win that game. We know, in the games you play, you guys succeed and do a great job. And as the game has shifted a little bit, we think we have the tools that can help you. So thank you.

Awesome. Well, excellent. Mitchell, Matt, thank you so much for joining us today, and thanks for sharing your time and your insight. One last time, I want to thank Neustar again for sponsoring today's webinar. Please go to www.neustar.com to learn more about the company. Thanks to everybody who participated. A recording of this will be posted later today to accountsrecovery.net.

And please stay tuned to accountsrecovery.net for news and more webinars in the very near future. Matt, Mitchell, thank you so much, really appreciate it.

Thanks, Mike.

All right, everybody, thank you very much. Enjoy the rest of your day.