How to Reduce Friction and Leverage AI like Checkr
Daniel Yanisse: ...if we take the racing analogy, to go fast, actually you need to have the best technique and be calculated and race cleanly and well.
Alexis Gay: Oh, I love this. Yes.
Daniel Yanisse: If you're reckless, you're going to crash, right?
Alexis Gay: Oh, I love... I could not have said a better version myself. inaudible. Welcome to The Shake Up. I'm Alexis Gay.
Brianne Kimmel: And I'm Brianne Kimmel. Each week, we explore the business decisions that dare to be different and the leaders who are shaking up their industries. You can follow us on Apple Podcast, Spotify, or wherever you listen to podcasts.
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Alexis Gay: This week on The Shake Up, we're talking AI, reducing friction in your product and a healthy dose of background checks.
Brianne Kimmel: And that's because we're talking with Fast Company's 2021 World Changing Ideas award winner himself, the co- founder and CEO of Checkr, Daniel Yanisse.
Alexis Gay: Yes. We're so excited to talk to Dan. I can't wait. I want to first talk a little bit about background checks as an industry on the rise. We're seeing a lot of growth recently.
Brianne Kimmel: One thing that I learned from doing some research on Checkr was the fact that they actually have a collaborative component to their background check. I think historically, you would send someone's information to an outside party. They would come back with a thumbs up or a thumbs down as far as, are you prepared for this new role? With Checkr, they're actually doing it in a way where the individuals themselves, the people that are actively seeking a new role are able to comment and give context on maybe some of the issues that they've had come up previously.
Alexis Gay: So, it's kind of a more human approach. We love that. There's also some concerns being raised around the rise of technology risks and discrimination that impose a bit of a hindrance on this growing market. The idea that because we're talking about AI, because we're talking about an algorithm, returning information here, there are legitimate concerns that this could result in bias.
Brianne Kimmel: Yeah. This is something that I am concerned about. I think that oftentimes we're scanning resumes programmatically, and we're looking for specific filters or data points to prove that someone's able to do the job, but we don't have someone on the other side that's actually ensuring that we're not skimming or passing over applications of potentially underrepresented groups or people that could step up and take on these roles.
Alexis Gay: Yeah. I can get behind that point for sure. What are some of the other shifts that you're seeing or you think we might see as a result of this increased scrutiny?
Brianne Kimmel: There's a lot of conflicting data. When you look at even the number of jobs that are open today, we are starting to see that there's a mismatch in terms of the things that people want to work on and the things that people want to do, and what sort of careers are in demand in their hometown or in their region. It was interesting. I had a conversation on My First Million podcast.
Alexis Gay: Oh, we love them.
Brianne Kimmel: Yeah. I talked about... For a lot of people, college is a waste of time. It's a waste of money. You just throw yourself to student loan debt. And for a large percentage of Americans, you end up taking on a job after college that is not directly related to what you studied. And so, we had this back and forth dialogue. Actually, Sam is still very much on board with college if you're going to maybe an Ivy League school and one where the network is really valuable, which is... I think that the challenge for modern trades there isn't really a social network or a LinkedIn or a community for people that are studying some of these trades to really upscale and get better at their role. And I hope that Checkr starts to really think about. I know they have this big ambitious goal around creating new jobs. And so, I'd love to understand like, how do we get as many people as possible plugged into this new model where you can have more upward mobility?
Alexis Gay: That's interesting. I mean, that would seem like a bit of a shift away from their core competency of quick, accurate background checks to suddenly turn into more of like a community- based solution, don't you think or no?
Brianne Kimmel: I think they can have some underlying community components or some education because I know they're building direct relationships with employees themselves. And so, I'm curious to see what that looks like. On the employee side, how is Checkr in a position to help you find the right role that could be a good fit or what are the next best steps that you can make to become hireable?
Alexis Gay: I love that idea that they could be very education forward with the" what's next" if you do get rejected from a job for reasons that occur in your background check or something like that, where it's like, " Oh, got rejected? Here's what's next. Here's what you can try. Here's what you should do." That's very cool. That's a great flywheel effect. So, speaking about some of Checkr's core competencies, obviously Checkr is using AI powered background checks to reduce friction, I want to hear a little bit from you, Brianne, about how companies can work to reduce friction in their product and customer experience. But first let's talk a little bit about why reducing friction is so important.
Brianne Kimmel: Yeah. What they've been able to do with the API is make it as easy as possible for companies to implement background checks. I've seen this a lot with other APIs and if you're on the startup side of things, it's very hard to hire engineers. We hear this time and time again. Engineers in the Bay Area are expensive. A lot of companies are rethinking their hiring strategy and they're sourcing engineers globally. That is now even harder to find the right people at a global level. And so, what Checkr is doing is making it as easy as possible for someone to implement background checks as quickly as possible to not slow down their user experience. And they really have two customers. They have employers who need to implement background checks and hire as quickly as possible. They have potential employees and these are active job seekers and people that really rely on this to clear as quickly as possible. So, they're not going without a paycheck or they don't have a gap in employment.
Alexis Gay: I also want to touch on why reducing friction, I think, can be so important from a user experience side. I'd love your thoughts on this as well. My thought is that people get bored. People get lazy, people get frustrated really fast now with technology. And by people, I mean me. I have no tolerance. If I try to put my phone number in and it gets rejected two times, I'm out. And I'll probably never return. There's no hope.
Brianne Kimmel: I know that they'll talk about that as well, where there was a market opportunity that emerged because there was Uber and Lyft and Instacart and all these great new platforms that were enabling the next era of the gig economy. And so, for them, they jumped on this opportunity in a space that was really tactical. Both co- founders are technical founders. And so, they were the right people to build it. Alexis, I want to get your thoughts on... I know that with Checkr, they talk a lot about AI and I know that you have a lot of thoughts and experience really learning about. What are some of the downfalls or what are some of the things to keep in mind when a company is implementing some of this AI especially when it comes to bias or potential discrimination?
Alexis Gay: Oh, yes. Let's zoom out a little bit and talk about bias in AI because it's an important thing that we talk about now. It's only going to become an increasingly large issue as we move towards more and more automated solutions. All the stuff we're talking about. In fact, all the tools and pieces of software we've ever talked about on this show have been designed and created and built by people. And I think that's important to remember when we think about bias and AI because, in my opinion, you have to work to make sure that you are checking for and correcting biases that may appear. And one of the most obvious examples that I found in the last few months was Twitter's photo cropping thing. So, to quickly sum it up, essentially, people realized that when Twitter auto- cropped your photo for you in order for it to fit in their newsfeed, it was biasing towards if there were people in the photo, lighter skinned people to be the focus of the crop in the photo. And people ran this experiment over and over and over and over again. I saw it in my feed countless times. It was interesting to me that a company like Twitter, a big public company could let an algorithm go out the door like that, that contains such bias without correcting for something like that. It just went out the door and then people were using it. And it was the people that discovered it. And then ironically used Twitter itself to bring it to the attention of everybody else which I thought was very interesting, but I guess what I'm saying here is, when are we going to start to see companies really checking themselves on bias and AI to make sure in advance before something goes out the door inaudible not seeing these types of things happen?
Brianne Kimmel: Well, it's one of the things. Investors talk about this a lot. What point do you have a human in the loop? This is something where if you're relying on AI alone, there's going to be mistakes and there's going to be things where you need some sort of checks and balances internally. AI alone can't solve this problem. You need people actually on top of it, owning it, and it's a part of the company's accountability to the user base.
Alexis Gay: Yeah. And I think what you're talking about, and this is something that gets lost a lot in the humans V robots debate, you can have tech facilitated solutions that increase efficiency and increase efficacy that don't necessarily replace or remove jobs that human beings need to do. Some things do need a human touch.
Brianne Kimmel: I think as people, we're very quick to... When we hear automation, we're very quick to assume that means our roles will be replaced. The example that I use a lot in investing is like marketing automation as a category has been around for a very long time, however, we still have marketers. And so, I think we see all this technology where we're seeing these improvements where it's upleveling people at work and improving productivity, but it's not replacing work. If anything, it's removing all the monotonous things that we don't want to work on and freeing us up to do more creative work broadly.
Alexis Gay: Do you think that VCs are at risk-
Brianne Kimmel: Of automation?
Alexis Gay: Yeah. Do you think your job is going to get taken over by a robot?
Brianne Kimmel: I'll give a very honest answer here. What's interesting is that a lot of VCs are moving earlier and earlier stage and many of them are incubating startups. And I think the reason for that is when you're a co- founder of a company, when you play a very active role from the earliest days, your contribution to the company is very clear to I think at some point we'll start to automate maybe large growth rounds and maybe the last round before the IPO. I think a lot of founders don't really care where that last round comes from because quite frankly, they already have product market fit. They're already gearing up for IPO. They already have a great executive team in place. I don't think the growth stage firms add that much value.
Alexis Gay: Brianne, this is kind of shots fired. Did you just say growth stage firms don't really add much value? You know we're recording this, right?
Brianne Kimmel: I know. I'm going to get canceled.
Alexis Gay: Wow. Always with the hot takes. So, that's interesting. I was thinking about it from the reverse perspective. I was thinking, " Are venture capital funds going to go the way of the robo advisor?" Will you be feeding metrics about a prospective company into a piece of software that tells you whether it's a good bet? Maybe.
Brianne Kimmel: I think we'll see that in some way, shape or form. I think we're starting to see that a little bit with platforms like Carta that are collecting all of the cap table information. They're collecting some metrics as they move more and more into reporting. I think we will have a handful of platforms that have access to the right amount of information. And if they are actively investing or if they have their own fund, they'll be in a unique position to write the first check or to be an investor because they have that information.
Alexis Gay: Just to take this away from tech for a second as we're talking about bias and AI, I wanted to bring up a couple points. Over the past several years, studies have shown that facial recognition services, healthcare systems, and even talking digital assistants can be biased against women, people of color, and other marginalized groups. The government is actually getting involved with this. In April of this year, the FTC warned against the sale of AI systems that were racially biased or could prevent individuals from receiving employment, housing, insurance, or other benefits. And then not even a week later, the EU unveiled draft regulations that could punish companies for offering such technology.
Brianne Kimmel: Yeah. This starts to get a little bit concerning for me-
Alexis Gay: Really?
Brianne Kimmel: Yeah. Specifically with the EU, I find that there are a lot of amazing engineers specifically in France that are working on AI. This is one of the largest AI hubs in the world is in France. That's where I get a little bit concerned of like, is the government potentially coming into quickly or not understanding the technology in ways where they're very quick to ban it as opposed to giving parameters and some assistance to tech companies on ways in which they can operate without closing it down? Yeah. That's a big conversation.
Alexis Gay: Totally. So, those are other examples of that tech like being out there in the wild and ways that could be potentially damaging. The other example that I wanted to ask if you saw was also on Twitter, but it was actually Lemonade, the insurance company. Did you see their tweet thread about how they're using data in this revolutionary way, and then everyone got really upset, then they had to take the tweet down?
Brianne Kimmel: Wait. What happened? I missed it.
Alexis Gay: They tweeted out a thread that was kind of somewhat self- congratulatory about their technology that they use. They provided an example of how their AI" carefully analyzes" videos that had asked customers to send in for claims, looking for signs of fraud, which includes nonverbal cues. So, basically, they're patting themselves on the back for saying, " Our AI is going to look at the videos that you're sending in and help determine whether you're telling the truth." And then everyone on Twitter was like, " I'm sorry, you're proud of that? That seems extremely bad." That seems like it could go down a very disturbing path. And it was so bad that Lemonade actually walked it back. And then they said, "TL;DR: We do not use, and we're not trying build AI that uses physical or personal features to deny claims." My point in bringing it up. Yes, companies make mistakes. I don't work at lemonade. I don't know what the intention was behind sharing this data. I'm simply calling it out to say, " Wow, sometimes there's a big difference between what excites tech companies and what users are comfortable with."
Brianne Kimmel: Yeah. This sounds like a situation where they have a very high IQ product team, and internally everyone's very excited about it because it's increasing their efficiencies, however, it's coming at the cost of customers. And so, they need someone in those meetings that's really going to say like, " Hey, let's ask our customers about this. Let's do some scenario planning and figure out, what is the worst case scenario? What could happen here? Rather than quickly patting ourselves on the back because you built some cool tech."
Alexis Gay: Yeah. Brianne, that's really good advice. Your companies are so lucky to have you. That would be very reassuring advice to get.
Brianne Kimmel: Thank you.
Alexis Gay: Okay. After the break, we're going to talk to Daniel. We're going to learn how he's reducing friction and the way companies run background checks. We're going to talk about how he made the transition from engineer to entrepreneur. And we're going to talk about auto racing because I always have said that I am very qualified to host a sports show, wouldn't you agree? I'm talking to you.
Brianne Kimmel: Yeah. I'm excited. I think we need to put on some racing gear and get out there.
Alexis Gay: Let's hit the road, Brianne. I am so excited for today's guest. He's the co- founder and CEO of Checkr. Daniel Yanisse, welcome to The Shake Up.
Daniel Yanisse: Thank you for having me. Excited to be here.
Alexis Gay: Yay. Okay. So, my first question actually has nothing to do with background checks, but does have to do with your background. You grew up in France, right?
Daniel Yanisse: That's right. Born and raised in France.
Alexis Gay: In France. Is it Le Mans?
Daniel Yanisse: Le Mans. That's right.
Alexis Gay: Le Mans.
Daniel Yanisse: Yes.
Alexis Gay: Okay.
Daniel Yanisse: You got it.
Alexis Gay: That's amazing. I hear that it's a city known for racing. Is that right?
Daniel Yanisse: That's right. There's the famous 24 Le Mans race. Has been one of the most legendary endurance races in the world. So, that's where I was born and maybe that's why I also am a racing fan and enjoyed auto sports. Yes.
Alexis Gay: Very cool. When you say you're a racing fan, is that you watch, you race yourself?
Daniel Yanisse: I watch and I race myself with my friend and co- founder Jonathan, actually.
Alexis Gay: Seriously? Oh my God. That's really cool. And also terrifying. I'm very curious to hear a little bit more Checkr and talk a little bit about that. In terms of background checks themselves, traditional background checks, obviously, they have their fair share of issues in terms of the slowness and they can often create a lot of friction and lag in certain processes. They don't tell the whole story about someone's life. For example, my background check would show off zero of my comedic talents. For you, what was it that made you want to redefine the way we use background checks by developing Checkr?
Daniel Yanisse: I think a lot of startups are started by employees or workers who are finding a business problem and then wanting to solve it and build a better solution. So, that's the classic story and that's what happened to Jonathan, my co- founder, and I. Our last job before Checkr, we were both API engineers in a smaller startup doing on- demand deliveries for retailers. And we were building the different parts of the apps and the software. Very similar to onboarding drivers on DoorDash or Uber, and then dispatching them to different jobs. And the background check was one of the main points of friction and efficiencies of hiring and onboarding drivers. So, that's how I kind of fell into that space. Looked at the different solution, found that they were really slow and antiquated and manual solutions. Not really great software in that space.
Alexis Gay: You're saying you saw it firsthand being an engineer working on that problem just how slow and complicated it was.
Daniel Yanisse: That's right. Of course like any startup story, we had absolutely no experience in that space. We didn't even know-
Alexis Gay: Really?
Daniel Yanisse: ...exactly what's in a background check. No, we really started from nothing. Of course, we discovered actually a lot more issues with the background checks than the slowness and the efficiency, especially around what you said. The background check doesn't tell the full story about someone. And so, it can lead to... if it's done poorly, to discrimination or fairness issues, blocking people from opportunities. And so, this is a big part of what we're focused at Checkr. Building fairer background checks.
Brianne Kimmel: And do you remember the moment when you decided this was the problem that you really wanted to work on?
Daniel Yanisse: Yeah. Yeah, I remember. So, that was in 2013. At that time, I was tinkering with different other startups, ideas. With Jonathan, we were hacking on the weekends and evenings different apps and different products, but I remember when we just chose the background check space, we started to get a lot of conviction and validation and even excitement from some of our network at the time.
Alexis Gay: So, Daniel, it's interesting. I hear a lot of startup founders have some kind of personal experience that flips this light on in their head that, " Oh, this is the thing that I have to solve," but it kind of sounds like you and your co- founder were tinkering and hacking and exploring. Did you always know that that was something that was motivating you to start something or to start something with Jonathan?
Daniel Yanisse: Yes. So, that's connected to my parents and me growing up.
Alexis Gay: Oh, really?
Daniel Yanisse: Yeah. My dad as an immigrant parents always wanted me and my sister to do the best possible and to have the best opportunities. And he told me like, " You should always try to be there. Try to become the CEO, to become the leader."
Alexis Gay: Oh, really?
Daniel Yanisse: Yeah. So, I think that really influenced me.
Alexis Gay: That's weird. My parents never once said, " You should really try to become a comedian, Alexis." Not even one time if you can believe it. Not even after I said, " Here's, what's happening." Today's episode is sponsored by those fine folks over at HubSpot. Managing conversations with prospects and customers and creating remarkable experience can be tough. HubSpot wants to change that. That's why they created a CRM platform that makes it easy to align across teams.
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Alexis Gay: The result, all your customer people can align around the same goals. Consistently great customer journeys that drive growth and lifetime loyalty. Learn more about how you can scale your company without scaling complexity at hubspot. com. I want to dig into a little bit more about background checks specifically. So, you've got your idea, you know this is what you want to do, you know you've got the right co- founder. Background checks, there's a lot of friction involved and there's a lot of contributors to that friction too, right? Government paperwork, outdated systems. Which stood out to you as the biggest problem area that you thought you could solve?
Daniel Yanisse: Yeah. So, we solved the number one friction we had is use of background checks in our last job. At that startup that that was called Deliv, doing deliveries. We couldn't find an API to request background checks and retrieve the results-
Alexis Gay: Sure.
Daniel Yanisse: ... ina seamless way because we actually were trying to have the background check step being in the app for the drivers. So that a driver can just click" sign up". " I want to get this job. Here is my information. And I want to check a few boxes to agree to the background check." And so that he can kick- start the process automatically. That's what we couldn't solve. And then I had early friends in my network who were early employees at DoorDash and other companies. And we also went through Y Combinator. So, we met other founders.
Alexis Gay: Oh, you did? When was that?
Daniel Yanisse: So, that was at the very beginning. So, we started working on Checkr in February of 2014. We incorporated the company in March. We quit our previous job to work on it full time in May and we got in Y Combinator in June of 2014.
Alexis Gay: So, pretty early on in the company's life cycle.
Daniel Yanisse: But Y Combinator definitely helped us find early customers because it was also the beginning of DoorDash, Instacart who, of course, are massive companies today. Those were some of our very early customers. And they had the same pain points we had at Deliv. They also wanted an API to streamline that step in their worker- driver onboarding.
Alexis Gay: Cool. Why are background checks such a pain? Assuming you could get them into an API, which obviously you've now done successfully, why are background checks such a difficult process in general?
Daniel Yanisse: There's a lot. We can only see the tip of the iceberg, but under the surface, there's a lot of complexity. In the US, the criminal records, the information from the courthouses is very fragmented because we have thousands of courthouses in the US at the municipal county, state, and federal level. So, there still are a lot of things on paper.
Brianne Kimmel: Behind the scenes at Checkr, are you putting pressure on cities and states and at the federal level to bring a lot of this information online or... Because it feels like that would be a bottleneck for the business is you need access to as much information as possible.
Daniel Yanisse: Yes, that's right. We are starting not to put pressure, but to try to partner and to help those small governments. Many times, they're understaffed. It's hard. They have thousands of cases. They don't have large budgets, so they have bottlenecks on their side. So, we're just trying to start investing into government relations and trying to see if we can fund technology or help them move to more efficient processes and really leverage technology to make their life easier, which will in result, help entire economy, right?
Alexis Gay: Yes.
Daniel Yanisse: Because it allows businesses to hire their constituents of that specific county faster to get jobs and employment, which is important.
Alexis Gay: Wow, Daniel. A lot of founders like to say that they're really just at the end of the day making the world a better place, but if you pulled that off, you really would be making at least the US a better place.
Daniel Yanisse: Yeah. I mean, we're trying. There's a lot of work to do. To me, where we can really make the world a better place, it's really about fair chance hearing and helping... Like you mentioned, there's one in three Americans who have a criminal record. That's a huge statistics, right?
Alexis Gay: Yeah.
Daniel Yanisse: And you have 2. 5 million people in prison at any point in time, which is also a huge statistics. The US has the highest incarceration rate in the world. So, that's where I think we can make the biggest change is to help the tens of millions of people with criminal record improve their story on their background and allow them to get better job and work opportunities who are the foundation of having a better, normal life with a family and growth. Yeah.
Alexis Gay: I've seen background checks characterized by some as problematic. Is that something that you've come up against?
Daniel Yanisse: Yeah, definitely. I agree that they can be problematic if used in the wrong way, and if they're used as a tool to block people from job opportunities. And the wrong way of using them is to take a binary approach and basically say, " If you have nothing, I move forward with you as a candidate.
Alexis Gay: Sure. Sure.
Daniel Yanisse: But if there's a bunch of flags, I'm going to just save time and throw away that resume out of the pile." That's how, unfortunately, most employers we talk to were using background checks and I don't think we should blame them for that because it's very busy and hard to hire people. And if you are given a very complex list of criminal records and you don't know how to interpret them, you don't really understand the laws and regulations, it's very hard for a small business or busy HR team to have a balanced approach. So, that became our mission at Checkr. We said, "Background checks are universal. 90- plus percent of businesses use them. They do provide value in terms of trust and safety for platforms, but if they're used wrongly and with the current states, it can also lead to bias, unfairness, potential discrimination." So, we said, " We're going to take something that's valuable to customers and make it more transparent, more fair, more of a balanced tool to add information, but not disqualify anyone automatically."
Brianne Kimmel: So, let's talk about that a little bit. Places like The Body Shop, they've moved towards what's referred to as more of an open hiring, first come first serve basis, which removes a lot of the need for background checks. Do you think something like that approach is the " right direction" that things should ultimately head?
Daniel Yanisse: I mean, I think open hiring definitely is as good intent. It's about not rejecting anyone based on their background. I'm not sure it's the best approach. Humans are inherently biased. So, we have to all accept that we are biased and just not doing a background check does not remove that bias, unfortunately. And I think that the best and fair way to help improve trust and safety and quality of inaudible is to do a background check. We will be transparent on the results with you. So, you get an opportunity to see the verifications and to influence it, which we do at Checkr in our products. We actually let the consumers and the job applicants write their own personal story next to their background so that they can share the full story. Because in the end, we work with a lot of people who have criminal records and who have some crimes they've done in the past and mistakes. And it's a very uncomfortable thing. It's hard for people too. " When is the right time to share my background and to share my story? How is it going to be perceived by my colleagues, by my employer?" So, we believe that the healthiest and best process is to make it an open conversation earlier on. It creates a lot more trust in the relationship.
Brianne Kimmel: This is a really important time in the labor market. There are over 9. 2 million job openings this May alone, and specifically for many restaurants, small businesses, hourly employers are really desperately trying to hire. Have you seen a shift in a company's willingness to accept candidates that maybe have a criminal record or that have inputted some of these additional context on why they have had a record or something come up over time?
Daniel Yanisse: Yes. 100%. It is the biggest opportunity ever right now. And so, today is really the most motivation, I would say, for employers to be more open in the background check criteria and how they deal and treat with criminal records. We are working with many customers and employers to make those changes. Overall, yes. There is a lot more willingness today to be more open and to consider hiring people with criminal records. I think a stat was 70 to 80% of employees and businesses are open to it, which is really nice improvement over the last few years. I think the number one bottleneck remains, businesses want to do it, but they don't know how to do it because it's not easy. How do you have that conversation with workers and with candidates early on? How do you have a good decisioning and process in terms of what type of crimes can be a disqualifier and which ones are not, and how do you evaluate those? And then, how do you make your... Once you hire the person, how do you actually make it safe and confidential for them, but also comfortable and safe in terms of the perception from all of the other workers in the company? It's a balance because you don't want to say, " Welcome, Joe. Joe has been in prison and has had a murder charge when he was 18 and now has had a great life." That can be not good for the employee who wants some confidentiality and have the time to tell the story on their own terms. And it can also potentially be scary for the wrong reasons for the other colleagues.
Brianne Kimmel: Totally.
Daniel Yanisse: Definitely not an easy thing to put in place, but at Checkr, we've iterated on it and now we're publishing a lot of guides and playbooks for HR teams and legal teams on how to actually implement fair chance hiring in their business.
Alexis Gay: That's great. So, you can really start to lead the way for companies that are interested in exploring that path. In terms of trade- offs, I'm very curious to hear a little bit about the trade- off that... it sounds like you had to make in terms of speed and a frictionless experience versus maybe accuracy or completeness. And I know you're a racing fan, so I know you're a fan of speed, but how did you think about that balance between" let's get this done as fast as possible" versus" let's make sure we have the full, most accurate picture for each candidate"?
Daniel Yanisse: Yes. I'm a fan of speed, but I'm also a fan of quality and excellence because if we take the racing analogy, to go fast, actually you need to have the best technique and be calculated and race cleanly and well.
Alexis Gay: Oh, I love this. Yes.
Daniel Yanisse: If you're reckless, you're going to crash, right.
Alexis Gay: Oh, I love... I could not have said a better version myself. It was gorgeous. Have you ever had to make a hard decision as it relates to that trade- off?
Daniel Yanisse: I mean, every day I would say it's a tension. It's the tension between speed and action and balancing risk and quality and being thoughtful, but there's good ways to deal with it, right? There are many decisions where speed is fine because they are reversible. So, if we made the wrong decision, we can quickly pivot and go from A to B, but there are some decisions that have high stakes and are maybe not reversible. When it comes to background checks, definitely the background check is a very important and sensitive information and reports. Someone's job and income and employment is dependent on that. So, we really take it very seriously and it's a huge responsibility we have as a background check company.
Alexis Gay: Something that Brianne and I have been really excited to ask you about is what you're talking about right now, which is, the impact that your machine learning, the algorithm, the AI can have on the decisions that are ultimately made on behalf of these employers. And so, let's talk a little bit about bias in AI. It's something that I've certainly seen a lot of headlines on, and there are a lot of ways in which I think AI can be really helpful and can help create opportunities, but something we've seen a lot in the last, I think, 12 to 18 months, especially, is the ways in which there can be bias written into the code of some of these algorithms. And so, I'm curious, how have you approached that topic internally at Checkr? Is it something you talk about?
Daniel Yanisse: That's definitely something we talk about and we have debates. AI is a very large space and there's hundreds and hundreds of ways of using AI to solve different problems. As of today, we don't use AI to make predictions. And so, we don't use AI to recommend if people will be hired or not. If we were to do that, there's a high risk of bias because the AI can learn that based on the wrong data points, potentially someone's identity, age, income, race, background might be better fit for a job or not, which can accelerate and reinforce biases and continue the unique qualities, for example, that are happening.
Alexis Gay: So, do you avoid not having AI involved in that recommendation process by not making recommendations at all or do you have a human team that makes recommendations to the companies that use the service?
Daniel Yanisse: Yeah. As of right now, we don't make recommendations at all. It's totally up to the company. So, that helps a lot. I mean, it's a very... Doing an employment decision is a very important decision. And right now, we don't involve AI into making recommendations for that. What we do use AI for is to improve accuracy. So, we use AI to make sure that we're not confusing one John Smith with another John Smith with the same date of birth because that's a common name. So, the AI can be very, very sophisticated and detect like, " Hey, I found that one of the addresses in the past was not the same one. So, it looks like this is a different John Smith." That's something that maybe a human would've overlooked. So, that's one example. Another example is I shared that the criminal records in the US don't have a standard. They're called differently in every single jurisdiction.
Alexis Gay: Oh my God.
Daniel Yanisse: So, you have thousands of ways of saying" DUI" or thousands of ways of saying" sexual assault" everywhere. So, we use AI. AI is very good at learning, so we can label millions of criminal records and then we can use AI to automatically identify the type of crime it is which also increase accuracy.
Brianne Kimmel: One thing that has really struck me is, as a team, you're setting really big lofty goals. How did you come up with this calculus and what conversation happened internally that led to this goal of three million jobs?
Daniel Yanisse: Yeah. So, that is our mission goal. So, our mission at Checkr is to build a fair future by designing technology to create opportunities for people. And by helping our customers put in place more open background check rules, we give them the software to actually be able to decide, " Hey, I am open to hiring people with marijuana violations or marijuana convictions," or DUIs if they're not driving on the job. That's not relevant. So, by helping our customers iterating on their rules, that actually allows thousands and thousands of workers who have those criminal records to be accepted and to move forward in the process. And since it's in the software, we can track every single one of them, every positive impact, every positive decision. And so, that's how we keep ourselves accountable for actually creating opportunities for people and helping them get jobs even if they have something in the background. We work with some of the largest employers in the world which is really exciting. And so, for them, making a few changes on their hiring criteria can impact tens of thousands or hundreds of thousands of jobs. And last year with the help of our customers, we were able to help 1. 5 million people be accepted and move forward in their job application and have zero impact from the background check. And so, this year, our goal is actually three million. It's a stretch goal. We always set stretch goals to force ourselves to be more innovative and creative, but that is our mission goal for this year. And it's extremely motivating for all of us, and for our customers who are joining that journey.
Alexis Gay: You mentioned that three million is a stretch goal. And I want to ask you a little bit about that because that's a big number. That's a lot of people. When you see that, you mentioned it was motivating. Do you ever wake up and just think like, " Oh, we can't do it. There's no way we're going to be able to do it."
Daniel Yanisse: No. That's not my style.
Alexis Gay: Never?
Daniel Yanisse: Never. I mean, I'm an optimist and I think everything is possible if we really work hard for it. Of course, we want to be realistic and look at-
Alexis Gay: Sure.
Daniel Yanisse: ...what is possible, but... No. I mean, I think in a startup you have to think big and be bold and be really ambitious. And I know we can. I mean, we at Checkr, we do over 30 million background checks a year. So, three million is about 10% of our volume. We are on track to do 2.5 million. We don't know exactly how we're going to do three million, and that's actually a great problem for our teams and ourselves to solve. Yeah.
Alexis Gay: Well, you have like five more months, right? You have almost half a year to figure that out to get another 500, 000 on the roadmap. Is that something that you all talk about internally a lot? Like where are these last half a million going to come from?
Daniel Yanisse: Yes. Our mission impact and the number of people we help is one of our seven company KPIs. So, really one of our top metrics and we review those on a monthly basis.
Brianne Kimmel: For the three million, I mean, you've mentioned Uber and a lot of the gig economy customers. What are some other examples of customers that are factored into this three million that you'd love to work with?
Daniel Yanisse: We have over 20, 000 customers across all industries from small businesses, tech, non- tech, and very large companies. We are actually working with a lot of great customers on fair chance. It's across the boards. There are benefits for all the industries. Of course, you mentioned all of the restaurants and all of the hospitality who needs to hire millions of people, but I think in tech, we can do much better at creating opportunities for underserved communities and really improving diversity in tech.
Alexis Gay: Totally. Brianne, that was a great question. That was like asking Daniel like shoot your shot at your perfect customer.
Brianne Kimmel: I know how to contact Checkr if you are looking for background checks.
Alexis Gay: You got to put it out into the universe, right? Anything's possible. We just learned that we're optimists here.
Brianne Kimmel: So, I'm going to put one more thing out into the universe. When you hit the three million job applications and you hit that goal, can we all go racing? I would love to go racing. I think this-
Alexis Gay: Oh my God. I'm down.
Daniel Yanisse: Yeah.
Alexis Gay: I'm scared, but I'm down.
Daniel Yanisse: We can do some... Go- karting is a lot of fun and it's good.
Alexis Gay: That I can do. Do you get helmets? Do you get a helmet on the go- kart?
Daniel Yanisse: Yeah.
Alexis Gay: Okay. I have one asset. It is my brain. It needs to be protected. That's amazing. I'm curious... This is our last question for you here. Checkr is obviously a very successful company. And in growing this business... As a leader, what do you think you've learned most about yourself in the process?
Daniel Yanisse: Yeah. It's been an incredible learning experience for me personally. I learned a lot. I think in the early days... Before starting Checkr, I was an individual contributor. I was an engineer. I've never managed people. I've never worked on the other business functions like customer facing or sales. So, it's been a very humbling journey. I think first I had to better understand myself, my personality, my strength, my weaknesses, be more vulnerable as well of all of the things I have to improve as a leader and change some of my traits. I really had to move from being an engineer to being a manager and a business person, business leader. And now I feel like my role at this scale is more... I'm more external facing. It's more like being a cheerleader and a teacher at the same time, which is a very different job than what I started with, but I love it because it's always stretching you and challenging, which is good. I think that that's how you improve as a person in your work life, but also in your personal life. I think it's also being helpful on my personal life to strive to become a better person, better friend, better family member, et cetera.
Brianne Kimmel: Is that something that you also look for when you're hiring now as well? Is that part of the Checkr culture?
Daniel Yanisse: Yeah, very much. So, one of our core values is humility. And that, I think, is very important. And every time we compromise it and we hire people who are not very humble and it's hard for them to be vulnerable or have some ego. It really does not align with our company. And it does not reflect that growth mindset and that humility. So, it's also hard because as the CEO you also want to be confident and bold and opinionated and passionate, which I think I am, but at the same time, I think if you want to be a modern CEO, you have to be humble. You have to care about people first. You have to be vulnerable. I think the old generation of CEOs are very top- down and you can see like Steve Jobs or even Jeff Bezos and others, and mostly leading by fear and by telling people what to do. I don't think that's the right model for the future.
Alexis Gay: No, it feels like a very old model.
Daniel Yanisse: Yeah.
Alexis Gay: Okay. You know what? I lied to you. I said that that was the last question. I actually have one last question, which is, who wins more races? You or your co- founder?
Daniel Yanisse: It's my co- founder. It's Jonathan.
Alexis Gay: Really?
Daniel Yanisse: Yes, yes, yes.
Alexis Gay: Are you a good loser? Do you exercise humility when you lose the races?
Daniel Yanisse: Definitely, I exercise the humility. No, I'm proud of him. He's awesome, and he's still one second faster than me on most tracks. So, I'm working hard to catch up to him.
Brianne Kimmel: Good.
Alexis Gay: Well, if you want to learn more about Checkr, I strongly encourage you to. Daniel, where can people learn more about the company?
Daniel Yanisse: Yes. On checkr. com, on social media. Follow us on LinkedIn, on Twitter, on Instagram. We'd love to share what we do in the company for our mission, with our customers, and partners. So, yeah. We're excited to connect with more people.
Alexis Gay: Fantastic. Well, Daniel, thank you so much for coming on The Shake Up today. Brianne and I had a fabulous time talking to you.
Daniel Yanisse: Thank you. It was super fun. I enjoyed it. Thank you.
Alexis Gay: Hey, Brianne. Are you ready to do that thing we practiced?
Brianne Kimmel: Oh my gosh. Is it time? I'm ready.
Alexis Gay: Okay. 3, 2, 1. Don't forget to subscribe and leave us a review.
Brianne Kimmel: Don't forget to subscribe and leave us a review.
Alexis Gay: Pretty good. Today's episode was written and produced by Matthew Brown. Production support comes from Lauren Shield. Our engineer is William Lowe with research from Corey Braccialini and special thanks to Kyle Denhoff and Lisa Toner.
Brianne Kimmel: We have some amazing guests coming up this season that you won't want to miss.
Alexis Gay: See you next time.
Checkr, a winner of Fast Company's 2021 World Changing Ideas Awards, is reducing friction in the hiring process while helping companies avoid bias through AI. And co-founder & CEO Daniel Yanisse has just the racing metaphor for you.
From fragmented data to missing APIs, Daniel walks us through all the ways companies can not only reduce friction for customers but help genuinely change their lives for the better.