Be an AI Superhero with Instant Fit

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Amy Warren: All right, it looks like a couple people are still starting to join. So we'll give them another few minutes to connect in. It's nice to see everybody. We're excited to talk about being an AI superhero today.All right, so with that said, let's get right into it. So I'm Amy Warren, I'm Head of Marketing here at Fama. And today we have Ben Mones, the founder and CEO of Fama. And for those of you who may not be familiar with Fama, we're one of the largest online screening companies that do online screening today. And we work with over 200 background screening companies, about 95 % of the background screening companies in the world today. So Ben, go ahead.Take it over.

Ben Mones: Awesome. Thanks a lot, Amy. And yeah, Amy's had some video issues today getting started. So apologies. We couldn't see her, live here on camera. But, for those of you that join, thanks a lot for carving out 30 minutes today to, join us and talk a little bit about Pharma Instant Fit. So, this is one of our newest products. As Amy mentioned, you might know us as the company that focuses on helping identify signals of workplace misconduct via online screening. But today we're going to talk a little bit about how we've leveraged some of that core technology to expand what we can offer to our clients, largely through, you know, partnering with some of the best IO psych folks in the world.

So, this is the agenda for today that we're going to walk through, and this is going to be a 30 minute meeting. So we'll try to leave a couple of minutes here at the end for questions. We can run over a bit. So, You guys have some time to stick around after, you know, the call. We can do that and walk through all that. So, we'll talk through just generally, you know, where this fits this product, this solution and the broader candidate life cycle. We'll talk a little bit about the evolving toolkit. you know, that we've seen, different TA practitioners kind of start thinking, how do I make sure I'm hiring, you know, the best people putting the best people in a position to succeed, based on the latest and greatest technology that's out there. We'll go through a history of traits and competencies here. And maybe if we have time, we'll get to the on the instant fit demo, but I'm not sure if we'll get there today. So if we don't, something can always pick up here after the call and we'll be sure to slide in some questions after the fact. But this product, again, I'm going to take you on a journey with me. So encourage you to have an open mind. There's going to be parts of today's conversation. Having done this one a couple of times, you're just not going to believe what I'm about to say. There are certainthings that, you know, you'll probably save yourself no way. What is this guy talking about? Where is this company coming from?

So we'll talk a little bit, you know, in detail about how we do what we're about to talk about, but you know, really, where we sort of started here in Fama in general, you know, there's so much technology out there that helps with talent sourcing, finding candidates, job boards, chat bots that allow you to engage directly with the candidate and the onboarding process. But we know that when it comes to choosing a finalist,it's one of the most difficult parts and human parts of the hiring process. So typically this is when a hiring team or a hiring manager has, you know, three to five candidates for a particular role. And they say, look, you know, John's got the experience. Jane has the, you know, book of business and, and, and Sarah, she has, you know, the attitude, right? We love all three of these candidates. We just can't figure out who's the right fit for the organization. And that's really where you know, we see talent acquisition coming in using their expertise, their decades of pattern recognition, their time in the field, the success stories. Again, that ability to know what good looks like just from simply their own expertise and experience and helping guide hiring managers to that finalist. We believe that this is an opportunity that we can bring technology into the mix and hopefully advance forward, you know, a individual candidates sort of opportunity to join a company based on the insight that TA provides.

So really think about the technology you're about to talk about as being used at the short list. Some companies have thought about maybe using this at a finalist of candidates as well to kind of begin predicting and sort of tying this person into the broader organization. But that's really what we're talking about today. So think candidate screening, three to five people for a role. How can we provide tech to tie an acquisition to help? them inform that decision and guide their hiring manager, their hiring team to put in the best candidate in that position. So I'm using this really as an image today. I don't have too much beyond, you know, what's on the screen here, but really I think the image says a lot where, you know, we are seeing a tremendous amount of generative AI. I'm sure many like you, like me, many of your inboxes are filled with you know, SDRs and salespeople selling you the next gen AI thing or the next AI tool that's out there. So we're seeing that begin to infiltrate the world of talent acquisition too, but largely in the world of passive talent discovery. Think of companies like, you know, seek out, for example, companies like chatter works that end up, you know, really helping you find good talent at the top of the funnel, use gen AI to engage with them, create a kind of recruiter like persona. so we're seeing the toolkit evolve very substantially. And I think.You know what I would encourage you to think about today is that we are living through a moment of going from the typewriter to the MacBook and ask yourself that question.

What does that mean? You know for me and I'm seeing an ever changing town landscape. You know we often talk about the fact that Millennials today and Gen Z together make up about 50 % of the workforce and as a millennial myself something I was surprised about something I didn't know but.as we begin to see the workforce change so substantially, where by 2030, 75 % of that workforce is going to be, and there's a new one, Gen Alpha, Gen Z, and millennials by 2030, how is your toolkit evolving to reflect the changing nature of that labor landscape, right? And that's really, again, as we sort of hone in on the product suite today, you know, what we're going to be talking about is evolving that particular type. This data here comes from a survey that we did in December of 2023, where we know a big piece of hiring managers guiding, for example, their talent acquisition guiding their hiring managers to that final decision.

One thing that companies use and have used historically, our previous research, especially was around 48%, but of companies using some form of assessment. How do I integrate professional trades? competencies that somebody brings to the table into that hiring process. You might be familiar with big five hexaco, Hogan assessment type frameworks, you know, that enable you to identify certain types of traits that have historically been shown to predict performance and certain types of job related settings. you know, a lot of companies do it right. And the data here suggests that this is just a sample of about, you know, 62 clients that, that we surveyed and Yeah, about half of them are using some form of assessments on applicants. Others are not sure. So really this is a popular practice. And, you know, if you do want to throw in your two cents, I don't have the chat window totally open here, but Amy can kind of manage that and jump in. And if you do have any questions or comments of, yeah, I use assessments and I love them or I use assessments and I hate them, whatever it is, I want to hear it all. So, you know, feel free to interrupt us as we get deeper into this, but the short story headline here. Companies are using assessments. They use it to kind of round out, identify whether or not this candidate has some of the traits and competencies that historically and similar types of employment scenarios have been shown through tons of peer reviewed research to be tied to performance. In other words, using this data in simple terms to move the needle on who gets hired, who doesn't.

So let's talk about how this is done today. Historically, right? The old way of doing it is send a candidate an assessment. This is called, you know, a self -assessment. We've seen knowledgeable peer assessments that get sent to maybe another IO psychologist that meets with somebody and interviews them, et cetera. But by and large, what we're talking about here are self -assessments that people are taking as part of an interview process, right? This can come in the form of lengthy questionnaires, written prompts, some fun games that are out there. If any of you guys have used some of the newer tech.from a candidate screening perspective. And there we go. Amy's got the live answering. How many are you using assessments today? Go for it. I'm going to minimize it so I can see things on my screen. Generally though, it's not a great candidate experience. You send a candidate something to say, Hey, now you got to go do this thing. After you've gone through this process with us, if you're in a high volume hiring scenario, if you're in a high stakes hiring scenario, right? Maybe you're fighting for very rare talent, right? Somebody that's got a bunch of job offers on the table. Now you're asking them to do something different.We call it the beginning of candy land where your candidate experience suddenly is going like this. And then you ought to go over a bridge, cross a river and crawl through a tunnel filled with snakes and crocodiles. And what does that mean for a hiring manager? It means you're waiting, right? There's lead time due to technical issues, a lack of candidate engagement. We've seen, you know, in the past through some of our discovery before we launched this product, some companies that were, you know, even finding that their candidates didn't have the proper OS operating system on their phones.couldn't even access the assessment and didn't even know that that was the issue. Right? So there's this waiting period. The assessment kind of goes into a black box. Some assessment softwares, they do have that kind of progress tracking associated with it. But in any event, things are kind of out of your control.

What does that lead to as it leads to candidate drop off? So our perspective here with what we're about to walk through is not to reinvent assessments or to tell you that Here's why you need to start running assessments today where we are focused on this product is for companies to be there are using or have used some form of professional trade or competency analysis as part of a hiring process that there is a way to skip everything I just showed you steps one, two and three. So that's really the value proposition here to generate the same sort of psychometric validated assessment on an individual that ties to historically you know, call it profit producing performance, producing trades that have shown to perform in certain types of job and employment scenarios. You can get that same information without ever talking to the candidate. And this is the part where everyone is like, yeah, right. I don't believe you.

So it's okay if you don't, I'm going to take you on kind of the journey because that's what Fama instant fit is. And we're going to start at the very beginning, right? How is this possible? So that's really the focus, you know, on these next few slides here. So who I'm sure people here have used chat GPT. I'm sure y 'all have tried it out with whether your kids or friends or family, maybe use it on the job. I use it at times when I need some quick support, right? On everything from like how to cook a meal or how to maybe come up with a sort of prompt for some work I'm doing here at Fama. So really what natural language processing is, is the ability fora machine to interpret, manipulate and understand, you know, written text, provided language. In other words, that's created by people to understand the patterns between it, whether it's sentiment analysis, concept clustering, keyword analysis, of course, but the only thing that chat GPT is able to do and not to oversimplify it, but text is a closed loop. It's a closed system, meaning that there are only a certain number of combinations of texts that can mean a certain things. And a machine is able to understand that dynamically on the fly to repackage, recreate texts based on your prompt, based on how other texts has been organized in the past.

So again, this is at its foundation, something called natural language processing. It's been around for 50 years now is at the forefront with chat GPT, but one of the core foundations of how we do what we do here with the Fama instant fit product. Now at the same time, we know for about, you know, two decades or so, Companies have been using NLP to look at a person's language, determine someone's web presence. This might come in the form of writing samples or self assessments or tests that people take, for example. So historically, you know, big five, you might've heard of that's a big one. Disc is another, maybe you've done a Gallup StrengthsFinder, for example, maybe you've built your own, you have it in house, right? These types of assessments are very popular. They've been used, validated across hundreds of published articles and research studies.

So the first pillar. NLP, the second pillar, identifying competencies and traits via NLP. If they could kind of the buildup here across, you know, frameworks such as the big five. So that's tip. So all that stuff, you're probably like, yeah, I've heard of that before I got that. I know it. The third, but big, you know, and most important sort of evolution that really only happened in the last six years or so, seven years was that there was research that was put out by a PhD from a little company called Nvidia, which you might've heard of. They're all over the news lately and we're one of the world's most popular and profitable and largest companies for a moment in time here on the stock market, I think just two weeks ago but there was a doctorate in video that put out a research paper that essentially highlighted that when it comes to the source of NLP analysis, social media content performs just as well as a writing sampler questionnaire. And this was really where we partnered with a company called who Nova who's our IO partner, you know, through all of this work and they've crafted really science around this exact sort of research. Right. And so this is that novel approach that sort of brings the concept of competencies and traits to the forefront and to the next level in a lot of ways. Now, this is a very new approach, but in other words, the headline here is that you can extract the same sort of validated insight from texts that someone writes to you in a writing sample, on a cover letter, in an email, for example, as what they might post on social media and even validate that above 90%.against a self assessment. So in other words, self assessment tied to writing sample tied to social media, that steel thread goes up and down. Right. And so this is a smaller number of peer reviewed papers, but about 10 of them or so with the most recent being published last year.

So this was the big unlock for us. When we partnered with, you know, but we said, Hey, look, there's something here. We aggregate huge amounts of social media data about people. We show our clients a fraction of it, just the risky stuff, just the scary stuff nothing else. So maybe we can use some of that, what we call information exhaust to create some new value and products for our clients. And that's really what Fama Instant Fit is designed to do. So Fama Instant Fit is really a proprietary validated model that allows us to identify personality traits and workplace competencies that are similar to legacy instruments like the big five, but use what they call an ensemble framework. So essentially combining the most predictive, the sorts of traits that are historically tied to performance across a wide range of individual, different assessment frameworks and models, largely grounded in the world of, you know, big five and similar types of assessment frameworks that you might be familiar with. but essentially allowing us to get to about 87 % accuracy, which if you're familiar with the world of assessments and 85 % F one score, something that's pretty high on the scale there. So in other words, being able to put ourselves in a position where we could begin to generate a validated assessment on an individual using their online language alone. Now, the key piece here is that we are able to generate this exact same sort. There's about 26 different traits, six different competencies that we can pull from, some of which have been shown again to be tied to higher performance and certain types of job settings.we can do all of that using 600 words through a person's publicly available web presence. And why this was attractive to us is that we had built all of that technology, right? The ability of your Fama user may be part of us before, but the one thing that we've specialized in where we've honed our craft, what we've, you know, poured now at this point, nearly $30 million into an exciting acquisition we did of our big competitor, all really, you know, it was a company called social intelligence, all really invested.in how do we make the best online screening company at that foundation is the ability for us to find a person's web presence with a high degree of accuracy, the ability to filter through that person's web presence and collect that content.

And third, the ability to then provide insights based on that content, largely in the world of signs of risk and misconduct. That's probably what you know about Fama today, but the new dimension that we're introducing into our suite of products is this ability here you know, called Fama instant 50 ability to get without taking a test, without putting any drop off in place, the exact same sort of validated traits and competencies as another dimension of insight from that person's online record. So from a technology perspective, it made a lot of sense for us because we didn't have to do too much. That was new. We were already using resume data to find a person's web presence. We were already collecting data from sites like, you know, Twitter, Tik TOK, for example. Right. And so the ability for us to then take a TikTok video, transliterate it, grab all the audio, run it through our models, and then determine if there were any Fama flags like intolerance, threats, harassment, any keywords a customer set up. We could take 600 words from that video and then run it through this model and generate a professional competency report.

So again, the value proposition here is not to sell you on this idea of Hey, we want you to start using assessments because here's why we think it's valuable. We want to work with the customers that already have identified that these sorts of assessments are important to them and important part of their process, but might want to find ways to expedite time to close with candidates to reduce drop off in the process and further expand the scope of what's possible here. Now, there is a huge potential with this product, I think, in terms of unlocking the value of our online presence for different types of talent acquisition activities. But today, where we're focused is saying, how can we deliver competencies and traits to our clients in a way that really gives them what they need, the stuff they're already looking for without ever talking to a candidate?

So that's what Fama Instant Fit looks like. This is a quick, you know, just screenshot of the dashboard, but very high level. What this is going to look like is going to be you know, web -based software as a service, same thing that you get with Fama web -based dashboard. This is partitioned. If you are a Fama customer today, this is partitioned for compliance reasons from our existing Fama misconduct reports. And I should share as well within InstantFit, there's nothing negative here. We're not trying to give you a reason to filter people out of your organization. We're trying to find ways to help filter people into your organization. So You won't see anything negative about a candidate. This is really about the positive side of who somebody is, the traits and competencies that they bring to the table. That's going to make them successful in the role that they're stepping into. Now, the key piece here, though, is that we aren't telling you who's going to be a fit. This is not automated decision making. In other words, we're not going to score for you or tell you that John is a 95 and Jane is an 88, right? That's not the way it works. But we believe that our talent acquisition users out in the field, this is through research, this is through intuition, this is through being in the market since 2015.

We believe that talent acquisition has the experience, has the expertise and similar to our core product, we want to design solutions for our customers that bring them to what I call the precipice of action. In other words, how can we provide you with the insight, provide you with the information so that you can supercharge and unlock your own potential as a talent acquisition user so that you can help guide your hiring manager through that decision to whether or not, you know, John or Jane in that example ends up getting hired. So we rely on a couple of concepts here. I'll just show you again, like a couple of the traits that we did pull in. We, picked out a couple of them here for today's presentation, but, and this is all cited.

We can send you guys some of the data behind it. If you're interested, send over the validation study, for example. But, you know, we picked out three traits, aspire, social, stress tolerance. We are providing this information to talent acquisition users who we believe know and understand what, you know, someone who's good at goal setting that has leadership potential, right? And we're providing the validation, the research behind sales and executive roles where these traits have historically been tied to higher performance, right? And this is similar to how many companies use assessments today. A lot of this is not comparing one candidate versus another head to head, but asking ourselves that question. We know that a TA or a hiring manager knows that they wanna focus on communication or customer relations. So for this social attribution here, we know that they're hiring for a customer service client facing, we know what industry they're in. Right. And so beyond providing that information, this is a product that is designed again, to kind of guide you as an end user to that final decision. So we're not going to use this as resume filtering. This is not going to be used to automatically pass somebody through, but instead is designed to give you that clue using technology as a talent acquisition user that,This is a role where I know we need good teamwork, right? I know this person's going to be customer facing. So we know that someone who is high on social through some of these, you know, reporting that Fama is able to do, we know that, or believe that that person has a higher likelihood that they're going to be successful in the role itself.

So again, you know, we, we've got a, all the, the citations behind some of these metrics here on, you know, the, the validation studies, et cetera, but again, what we're trying to design here is not a replacement for any talent acquisition user, but a way for them to unlock their own potential, them to increase the cards that are face up on the table in front of them as opposed to the cards that are faced down. So that's really where, you know, this product comes into play and, you know, it is designed to unlock the potential of the user to help that user again, guide that hiring manager to the right decision because we think our TA users actually know what somebody who has high teamwork or ranks high in communication, customer relations, et cetera, we think that they will be able to make that connection between the product itself. So that's really fun.

You're going to get all these slides, by the way, since you signed up and so you registered. And I will just pause here and say that the product is in its earliest stages right now. So we just announced it earlier this, I think,quarter. I think Amy, that's right. We just announced earlier this quarter. So this thing is very new. We're in private beta access only right now. We would love for you guys to come in and test it out. We're offering, you know, really discounted pricing at the moment, you know, to help, you know, beta customers who want to get started and just test it out in exchange for a few, you know, feedback sessions with our tech team will absolutely make it worth your while from a financial perspective. Yeah, that's Fama instant fit. I've been trying to go through this really quick. Sorry, I spoke so fast and only had 30 minutes, but did want to make sure we left five minutes or so here for any questions or chats that have come in.

Amy Warren: Yeah, one of the questions that's come in to me directly is, can you explain a little bit more about how you're using AI to understand someone's online presence? And is that public or is it private?

Ben Mones: Sure. So it's only publicly available data only, or in other words, in our universe of instant fit, only publicly available online language that we're filtering and processing on your behalf. Right. And so artificial intelligence is essentially the ability to really throughout the fulfillment flow I just described from using natural language processing and the information on a resume to find a likely web presence about a subject. Once we have that web presence confirmed to filter through that information on a customer's behalf to extract all the text, run it through an algorithm, also artificial intelligence. So again, it is the ability of using AI to replace the work of collecting information, but also now of processing large amounts of trade and competency based information here, but it's all publicly available. And I should note too, that if you have a candidate that maybe doesn't have a ton of information online, you can also use a writing sample, maybe an email, transliterated audio, that kind of thing. You get somebody speaking for about four minutes. You can also run an instant fit. So there are two options here. You can either get a transcription of a conversation and email, or just leverage that person's web presence.

Amy Warren: And then another question that we have come in is for people who are watching the webinar, who are already clients, who should they talk to about adding instant fit? to what they're currently doing with their misconduct reports?

Ben Mones: Definitely. I would say reach out to your account manager and they'll get you set up. We can do a call. We'll bring in our product team. These are going through because it's a newer product for us. These are running through a lot through our tech team, our tech organization for customers that do want to test it out. So just because we do need a bunch of feedback right now to make sure this thing is right before general release later this year in the fall timeframe. So yeah, reach out to your account manager. You don't know who that is. You can send us an email at, you know, sales at fama .io or support at fama .io. Yeah, whatever, whatever channel you want to go for the contact form on our website, send us your information right now. Any of those paths work, but your main POC at Fama will get you hooked up with the right workflow here in terminal.

Amy Warren: Great. Well, I think that that wraps up our questions for now. Thanks, Ben. Appreciate the time and going over InstantFit. And for everyone who joined us today. We'll be following up the presentation with an email that'll have access to the recording. It'll also have the links that we shared in the chat. And if you have any questions, just feel free to go to that page, fill out a form, and we'll set up some time to talk with you. So thanks everybody for coming today.