Ben Mones
Founder & CEO Fama Follow

Welcome to the Use Case Podcast, episode 221. Today we have Ben from Fama about the use case or business case for why his customers use Fama.

Fama creates technology-enabled, AI-driven candidate insights.

Give the show a listen and please let me know what you think.

Thanks, William

Clinch A Modern Tailored Experience

Show length: 28 minutes

Enjoy the podcast?

Be sure to check out all our episodes and subscribe through your favorite platform. Of course, comments are always welcome. Thanks for tuning in to this episode of the Use Case Podcast!

Music:
Welcome to RecruitingDaily’s Use Case podcast, a show dedicated to the storytelling that happens or should happen when practitioners purchase technology. Each episode is designed to inspire new ways and ideas to make your business better. As we speak with the brightest minds in recruitment and HR tech, that’s what we do. Here’s your host, William Tincup.

William Tincup:
[inaudible 00:00:03] William Tincup, and you are listening to The Use Case podcast. Today, we have Ben on from Fama. We’ll be learning about the business case, the use case, for why his prospects and customers use Fama. And that’s F-A-M-A, for those listening at home. So Ben, would you do us a favor, and introduce yourself and Fama?

Ben Mones:
Sorry, you cut out there.

William Tincup:
Oh yeah. Sure.

Ben Mones:
Yeah.

William Tincup:
Could you introduce yourself and Fama?

Ben Mones:
Yup. Hey there, thanks for grabbing me on. Ben Mones, CEO, founder of Fama. We’re the world’s largest social media screening company.

William Tincup:
And so, the business case for folks that use Fama, how do you start that? How do you start the conversation? What is the problem that the technology resolves?

Ben Mones:
For sure. I think we like to start at the point of evaluating the screening mix that HR professionals, talent screening professionals, are using today. The tools that make up their arsenal. So, when I position Fama, introducing it to somebody for the first time, I explain it as the modern background check. So, instead of looking at things like, was this person a low level, non-violent offender, typically what makes up a background check. For your low level, non-violent offender a few years ago, we’re much more focused on what we think the modern customer, modern employee cares about today. So, those are things like intolerance, threats, harassment, the sorts of things that if you’re people are evidencing that thing, and from your customers, it’s going to alienate them, have them not come back, not want to purchase from you.

Ben Mones:
And two on the other side of it with the labor environment we’re in right now and how hard it is to keep good people we’re basically saying, “Hey, we want to enable you to leverage screening technology, to help keep your culture great to remove toxicity from the workforce.” Where we know that people who are working in toxic work environments, ripe with things like intolerance harassment, that thing. Productivity goes down, good. People are more likely to leave. So when we position Fama, we’re basically saying, “Let’s look at the tools you’re using today to screen talent.

Ben Mones:
Let’s think about how we can use those tools to extend your brand in the eyes of your customers, and also build a great culture and show the people coming into your org or sort of extending the values of your organization in the eyes of your clients and your employees rather than detracting from it.” So we’re not trying to say this is the new background check. I do think background screening, as it stands today is always going to be a thing if you will. But you know, we’re coming out and saying, “Hey, look, there’s a sort of evolution in the market and the screening mix should have all along with it.”

William Tincup:
So in terms of the things that we look at, so the hows then the why I guess has been explained.

Ben Mones:
Yeah.

William Tincup:
I guess in social listening, What are we paying attention to?

Ben Mones:
I think a lot of in our industry especially anytime a company like ours is compiling public data about people and using that in credit granting, benefits, hiring. There’s a lot of misconceptions, I think, in a healthy way about what goes into that. So I always start with the bottom when they ask about the how I explain what it’s not. So this is not a score. This is not a thumbs up or a thumbs down. This is not a yes or a no, or a recommendation on a candidate or a whole person in any sense. But instead, what we enable clients to do is to bring and productize insights is the term we like to use from the publicly available web and bring that into their talent screening funnel.

Ben Mones:
So what that means is that customers can come in and say, “Hey, I want to know about any reference to using those same kind of behaviors we stuck with intolerance, threats, harassment. I maybe want to know, but any reference to illegal drugs I’m hiring in California. I don’t care about cannabis.” But these are the sorts of things that should they exist. And the candidates digital identity, the sorts of things that bring into our org, I, as the hiring manager, talent screening professional would want to know about that. And what Fama does is we handle the heavy lifting of finding a person’s complete publicly available web presence. This is all consent based, just like any other background check. So as soon as the candidate signs a consent form, what we do is we go out find that complete publicly available web presence, using a combination of both people and automation in the same workflow. And then we filter through that content using natural language processing and image recognition to escalate anything that the client had defined as job relevant.

Ben Mones:
So this gets around, I think a lot of the concerns that people historically had about doing this themselves, where you go on a person’s Facebook profile or something, you see a protected class, for example, or something that shouldn’t be included in the hiring decision. We blind clients to that by only escalating for user review, the hits, if you will. And in background screening prolongs, we have like a adjudication matrix built into the software itself. So clients can essentially define what gets escalated for human review, what gets auto cleared.

Ben Mones:
So really clients reviewing 3% of reports where there is a racist tweet, a Google article, we’ve got products now for the executive suite that goes into offline news litigation, et cetera. So we’ve really expanded well beyond just social media today to start looking at a range of other data sources then yeah. Clients look at as important to hiring these days. So.

William Tincup:
You also are now, or in the future, do you also look at once the hire is done and their employees monitoring because… Okay. So they didn’t have a racist tweet. You know, we use that as an extreme, they didn’t have a racist tweet before we hired them.

Ben Mones:
Sure.

William Tincup:
However, after we hired them complete nonsense comes out of their Twitter account or something like that. Is there again and either now or in the future, do you see that as something that plays out?

Ben Mones:
I’d say for today, there’s talk around monitoring we do offer it, but it’s for very specific use cases today called like security clearance use cases or people access have access to very sensitive information or manufacturing systems. I’ve put it less than 5% of our business today is some sort of monitoring product. I think that there is a movement in the background screening industry right now to evangelize the future of monitoring because for the street it’s a recurring revenue stream. It’s not this. One time revenue that folks are running.

Ben Mones:
So if you look at some of the S ones from when the big players went public last year, they all look at the monitoring market as expanding significantly over the next five years or so. So I’m doubtful, frankly, that monitoring will expand to the degree that the insiders in the industry are forecasting, but it’s a product we offer today. I do think that background screening itself is that last and final where the person comes into your organization to determine, “Hey, this person is it, or are they not” I think monitoring is really going to be driven by the market in terms of overall acceptance. And I know how the back screening industry is going to keep pushing it because it’s a very attractive revenue stream for the both of them.

William Tincup:
Right, right. It’s in their best interest.

Ben Mones:
Yeah.

William Tincup:
Yeah, there is benefits to the company. So I get it, I get it.

Ben Mones:
Yes.

William Tincup:
Give us some examples without names, give us some examples of things that you’ve helped Fama has helped your clients avoid just by you. Now you know and then you can with that knowledge, you can make a better hiring decision. What are things that they’ve avoided? And give us some examples of those things.

Ben Mones:
Yeah, sure. So we’re the type of company that ideally you never find out the pain that we helped you avoid, right? So it’s an insurance policy risk policy here. So with Fama every single day with the volumes that we’re transacting on today, companies, whether it’s in the healthcare, financial services, tech, media and entertainment, retail, staffing, we’ve now seen adoption across industries where every single day we have folks that are identifying things. Like you said, intolerance, racist, tweets, that thing, litigation involving harassment around the candidate. Right. That kind of thing. So what we’re doing is helping preclude and avoid any potential brand damage for these clients also at the same time, any negative impact on their culture. So without getting too deep into the detail, we’ve seen a range of use cases.

Ben Mones:
There’s this typical, I want to know about intolerance, right? That’s the very low, low probability call it one and a half, 2% of all reports that are coming back, but high impact sorts of things that customers want to know about. And I’d also point out too, it’s not always a binary hire, no hire decision when these sorts of hits come back. Oftentimes what an employer is going to do is just a course correction like, “Hey you said that that joke, maybe it was a joke. You said it four or five times over the past few years, that’s not cool at our company. That’s not what we stand for. It’s not the sort of thing that’s going to make you a great fit here. Just let’s make sure we’re on the shared same frame of reference on what’s in, and what’s out at a company like ours.”

Ben Mones:
So I’d say that’s one just macro, that’s happening every day now. When you and I first met back in 2016, we were running I don’t know a few hundred reports per month. And at this point we’re looking in the tens or twenties of thousands at this point per month. So we’re just seeing every day that use case pop up. Some more interesting stuff, as we’ve done some really exciting work with some of the folks who were distributing the vaccine during the COVID pandemic. So some of the big government and private organizations that were responsible for vaccine distribution, what we helped them do was identify anybody in their employee population that was promoting anti-vax content online.

Ben Mones:
So there, we ended up actually identifying one of our customers about 1% of all the 25,000 people that they were hiring were promoting anti-vax ideology online and signing up to give the vaccine. So keeping those folks from giving the job and potentially inserting their own agenda into the scenario was a pain point that many folks never had to deal with because we caught it before it became a problem.

William Tincup:
That one seems rather, I mean, rather objective.

Ben Mones:
Yeah. Yeah.

William Tincup:
You can clear cut, say. When you’ve said intolerance and racist…

Ben Mones:
Yep.

William Tincup:
Those are very nuanced. Now they can be extreme. They can be very easy to pick out. Okay. N word, got it. That is, okay, there’s done. However, one person’s intolerance is not necessarily another person’s intolerance. It’s not like a universal intolerance. Right?

Ben Mones:
Sure.

William Tincup:
How do you coach your clients through, I just read this yesterday. It’s a local school here, University of Texas at Arlington. Their student council President was forced to resign because on Discord, she made a joke about, “Well, we should just bomb all those countries.” And again, when we out of context, yeah you probably say, okay. Well you know that’s something this is fair.

Ben Mones:
Sure.

William Tincup:
But with context, especially as a sarcastic person like myself, I could actually make that funny. I know I could make that funny, so.

Ben Mones:
Right.

William Tincup:
How do you coach people through that? First of all, I’m one of those people, I’m a railroad. I can make anything funny, like take-

Ben Mones:
I agree. I agree.

William Tincup:
… the worst things of life. And I think I could make it funny. So I’m on that spectrum and not everyone in HR and recruiting is on that spectrum. So I get that. So how do you coach people through what is, and what isn’t intolerance? What is, and what isn’t racism in? I don’t know if that’s syntax analysis or contextual, how do you coach them through that?

Ben Mones:
It’s two fronts. I would say one it’s the technical development, which I’ll speak to here of our technology and aligning our AI around the most universally agreeable definition around what intolerance is and isn’t, but-

William Tincup:
Right.

Ben Mones:
The second piece of that is the processes that we help our clients sort of set up inside of their organization around adjudicating this data when it comes back. So I’ll start on the tech front. So when we built Fama there are two ways to go about the NLP and the image recognition thing. It can either be a generalist, just like Google and say, “Hey, look here’s an image, there’s a dog in it. There’s a street sign in the background. There’s a road, we think that’s 75% a human in the frame.” So you can go generalist, or you can go very, very specific in terms of category modeling, which is what we do.

Ben Mones:
So we focused on being very good at rating and identifying what intolerance was in text and in image and natural language processing makes up syntax analysis, a part of it’s keyword analysis, it’s punctuation, it’s emojis. It’s really taking a human labeled input and then training a machine to replicate the work of that human and to do it consistently. So, because we’ve been at this now for seven years, we’ve gotten to a point where we aren’t just letting a machine go off on its own. We are constantly, and I mean, on a weekly basis, retraining our algorithm on a set of standards that we as a company have identified, not just internally, but from a DEI committee, we’ve set up to say, this is what the universally agreeable definition of intolerance is, and for fun. And we share that definition out to our clients.

Ben Mones:
Here’s what’s going to be flagged, here’s what’s not going to be flagged. So there’s work that we do as a service provider to essentially say this is our definition of intolerance. This is our definition of threats, harassment. Here’s what’s in, here’s what’s out in terms of how we think about it. For example, a threat someone’s saying, read someone saying, “My team is going to kill it this weekend.” Is very different than someone saying, “I’m going to kill my boss this weekend.” Right. Those are two very, very different statements. And they might seem different in text.

William Tincup:
Unless they say I’m going to kill my boss at tennis.

Ben Mones:
Yeah, yeah.

William Tincup:
Or shoot him.

Ben Mones:
Or I’m going to kill my, kill my boss in a freestyle rap battle.

William Tincup:
Exactly.

Ben Mones:
At, at midnight under the streetlights be there.

William Tincup:
Yeah.

Ben Mones:
So, so in any event-

William Tincup:
Context.

Ben Mones:
You can train a machine to tell the difference on that thing, but to your point still, there are companies I’m telling you same industry, same geography, even geographically down to the same block in the same big city that look at the same hit differently.

William Tincup:
Right. Right.

Ben Mones:
So what we train our clients on is just like background screening today, where it’s a crim hit or a drug hit, or a verification hit is going to mean different things to different employers based on their risk tolerance. Right. Some companies are going to be very stringent about that six year old criminal conviction. Others are going to be like, you know what? It was nonviolent. We really need people we’re bringing you in. Right. So ultimately it’s really on the company to decide.

Ben Mones:
And when we train our clients on adjudication, we encourage them to look at a few different elements of the report. So the first being the frequency, how many hits are we seeing? Is this just a one off thing? Is this something that has happened time and time again? Or is this just a one off joke this person made a few years ago, right. And just taking a step back, it’s whenever you get a background check hit back, and you’re going to take action on this third party, you have to go through the pre adverse, adverse notification process. And I’m sure all your listeners know about that being tuned into this space and all that. But what that basically means is that, the company has to share a copy of the report.

Ben Mones:
They have to give the candidate an opportunity to contest the results. And it opens up the platform for a discussion about what’s happening. So when that hit comes back, clients are often, “Okay, well, what do we do with this information?” And so what that means is, we look at the recency of it, we look at how frequent was it posted? So recency is more when was this? Was this a few years ago? Was it just last month? Was this something when this person was in a more junior stage of their career, can we look at it as a development thing? That sort of thing. So it’s the recency, the frequency, and then as you outlined, it gets into the tone of it. We, we look at the sort of Supreme court definition of pornography when you know it when you see it. Right. And that’s how our clients have-

William Tincup:
I think it was just the excuse for them to look at pornography, by the way, just as a mental note, I think that there was… Because I remember that bit. And he was, “We’re going to take six months and really define.” I’m like, “Yeah, yeah.” Yeah, I want to define that too. Especially if I get paid to define it.

Ben Mones:
Suddenly in the next few industries, porn makes the internet.

William Tincup:
Yeah. Yeah, yeah.

Ben Mones:
That’s what? That’s-

William Tincup:
Exactly.

Ben Mones:
… an extra 15 or 20 years.

William Tincup:
Thanks for the definition. Appreciate your strong sermon.

Ben Mones:
Yeah. Yeah.

William Tincup:
Yeah.

Ben Mones:
Appreciate the definition. Now let’s go make the internet. So, maybe something good happened out of that. But in any event, it’s something where the customer needs to have a set of policies and adjudication framework to deal with the hits that come back consistently. And it’s not a sentence stone thing. It’s something that is not imitable, you can edit it, you can go back, you can change your policy and companies do that. After 90 days, 120 days on the platform where they start saying, “Hey look! Can we adjudicate this?” Maybe we don’t care as much about cannabis hits for example, or maybe we don’t care as much about sexual references, persons making online, that thing. So it’d been interesting an exercise for me to just find the different ends of the spectrum where… I’ll tell you. We just wrapped up our series B financing, by the way, a quick shout out to Silverton Partners.

Ben Mones:
Thank you. $10 million series B, which we’re super fired up about, but on the fundraising term. And I met people who were, “What is this PC BS that you guys are doing?” I don’t get this at all. Intolerance? Come on, who cares about intolerance? Right. So obviously a very different opinion than one that I have, but there are folks that we met along the way that were just philosophically had a different view. So I think you’ll see that in the marketplace, but I do think there’s an overall trend right now for companies wanting to root out the intolerance, harassment, threat, illegal drug use that thing when they’re hiring.

William Tincup:
All right. Two things that I want to cover you through before we go. One is where in the workflow, where in the funnel do you think that Fama is used the best?

Ben Mones:
Today it’s being run predominantly right alongside a background check. So typically right at the conditional offer of employment today. So that’s where we see the most use for Fama as your final check, your safety net, auditing and validating the fact that you did everything right to get to this point. And now we’re just waiting for the results in the background check to make sure that we did our work on the character and fit front.

Ben Mones:
So typically it’s right at conditional offer of employment. I do see some companies bringing it slightly early in the funnel, just because our report turnaround times. And the level of insight that you get is such that allows you to construct what they call sort of a sequential screening process where they’ll do different types of checks and then not have everything all at once. So some companies are starting to do that. I call that the pro advanced way to go about it, but the majority of clients are just doing it a conditional offer employment.

William Tincup:
Your favorite part of the Fama demo. It’s like a holy view-

Ben Mones:
Yeah. Yeah.

William Tincup:
… your favorite child. Well, it’s your favorite child.

Ben Mones:
Well, I do have two kids now. I did have twin boys on the sum of five years so.

William Tincup:
So of course you have a favorite. Yep. All right. So tell us a little bit about your favorite. No, I’m just kidding. Totally kidding.

Ben Mones:
No, the favorite part of the demo for me isn’t to feature a button or anything like that, but the look on the customer’s face, because a lot of times are going in and people have been doing this manually. They’ve been burned by something, right. They’ve been caught on their heels. Many times when clients reach out, there’s a reason, right? They miss something or their leadership team is saying, “Hey, we got to get ahead of this. We’re worried about brand risk as an organization.”

Ben Mones:
So oftentimes it’s the look of awe on the customer space when they see what we can do. And also when people say, “That was simple, oh, that’s really straightforward.” Because to me, that’s yeah, that means we’ve got the product right. We got the UI right. We got the UX right. So like I said, been in the trenches on this for almost a decade now at this point. And still seeing the way that customers react when they see the simplicity. And I would say elegance of the solution itself. It’s that reaction that keeps me coming back for more so.

William Tincup:
I lied. One more question is buying questions that people, if they’ve not been down the social screening path before, what should they ask? What should they ask people like Fama? What should they be asking you?

Ben Mones:
I think you should be in any type of hiring software that you’re using I think compliance is a key piece of it, right? Ensuring the provider that you’re working with can help you deliver an FCR, a compliance solution. Because if not you’re going to get burned and you get into troubles. That’s one key piece, I would say that any customer should be asking a third party provider for. And yeah, the second piece I would just say is the ability to scale grow and become the future of screening.

Ben Mones:
I mean, I think this is the sort of thing where we believe that the adoption is going to continue to grow like it has over the past year. And you want a company that can scale with you, grow with you and help you deliver obviously comprehensive high quality solution. That’s just base. I think any company buying any software should want comprehensive in quality, but specifically for us, I think it’s the ability to scale and the ability to deliver a compliance solution, protect you, protect the candidates privacy and get to the data you need and get on with your day. So that’s kind of how we think about it.

William Tincup:
Drops mic, walks off stage done deal. Good thing.

Ben Mones:
Wait, cue the smoke machine, cue the smoke machine. The simulated ring, simulated ring, we’re doing the music video.

William Tincup:
And we need some pyro techniques. Hey seriously. Thank you so much for coming on the podcast.

Ben Mones:
You got it, man. Thanks a lot for having me on and hope you invite me back.

William Tincup:
Absolutely. And thanks. And congratulations on the series B and thanks everyone. Listening to The Use Case Podcast.

The Use Case Podcast

Authors
William Tincup

William is the President & Editor-at-Large of RecruitingDaily. At the intersection of HR and technology, he’s a writer, speaker, advisor, consultant, investor, storyteller & teacher. He's been writing about HR and Recruiting related issues for longer than he cares to disclose. William serves on the Board of Advisors / Board of Directors for 20+ HR technology startups. William is a graduate of the University of Alabama at Birmingham with a BA in Art History. He also earned an MA in American Indian Studies from the University of Arizona and an MBA from Case Western Reserve University.


Discussion

Please log in to post comments.

Login