‍Julian: Hey everyone. Thankyou so much for joining the Behind Company Lines podcast. Today we have RaviSandepudi, CEO of Effectiv, a Cutting edge fraud and risk management platform.Ravi, I'm so excited to chat with you, not only because of what you're working onnow with Effectiv, but also your background, your experience in terms ofbuilding and thinking about product and, and you've had some interestingbackground experience.

I won't spoil it for the audience here.before we get into everything with Effectiv and what you're working on,especially in the fraud and risk base and in, and I know you focus a lot on thefinancial sector, which is obviously in the news, and so we'll break into someinteresting questions around that.

But what were you doing before youstarted the company? What were you doing before you started Effectiv?  

Ravi: Uh, Yeah. Thanks.Thanks Julian. By the way, thanks a lot for this opportunity. Of course. Reallyexcited to speak with you. But yeah getting back to your question Julian, so Istarted off my career at Google was part of the risk and trust and safety team,so we.

Basically build policies, systemstechnology to detect fraud and abuse across various Google products. Spendquite a bit of time on search and ads and, and products like Google Pay wherewe try to identify transaction fraud, accounting, ORs, money laundering, andscenarios of that sort. Yeah. After.

Left to join a startup calledSimilarity. I was the first employee there, so that's when I got my firstexposure into startups. Could see building startups firsthand. Was not afounder, but, but a very early employee. At similarity as well. We were frauddetection software. We eventually, found our product market fit in theenterprise banking space.

So we had customers like US BankDiscover Synchrony. Yeah. In, in, in Brazil and so on. We eventually gotacquired by PayPal in 2018. So again, a great outcome. you, I mean, I was very,very lucky there, right? So you it's not your first start and Yeah, generallyit's not. That common that you succeed with, with the first startup, but, butyeah, I was very lucky.

We had amazing founders right. So, yeah,so they, they were really great leaders. I learned a lot from them. Then again,as part of PayPal we, we saw firsthand like how yeah like good acquisitions,acquisitions can work out. So it was a really, really good fit and we reallyflourish. Under PayPal's umbrella.

So again, got to work on really highscalable like, super critical systems within, within PayPal again in the frauddetection space. So got great exposure, worked with great people there, andthen. The startup bug bits again, . And and then yeah, after working for a fewyears at PayPal myself and I have three other co-founders.

All three of them were also EliseSimilarity, and then subsequently PayPal folks. . And four of us stepped out tostart Effectiv, and again, we are continuing in the fraud detection space.Mm-hmm. , so this is my 17th or 18th year. I know it, it reveals my age alittle bit, but . Yeah. But yeah, this is a area four of us are superpassionate about.

We couldn't imagine ourselves working inany other space. But the, the more important thing is we found that it's. Anunsolved problem. Huge opportunities. I'll speak a little bit about this in thecoming minutes as well, but, but yeah, the opportunities were great. We weresuper passionate about the topic.

We had a little bit of a background inthe space as well, so everything fit in really well.  

Julian: Yeah. And I'm curiousfor those who, of us who, who aren't familiar, what are the common ways thatyou can detect fraud? And, and what are some ways that companies or evenindividuals who are in customers who use products are kind of exposed in, infor, for these different, whether I, I'm not sure if it's, whether it's hacksor whether it's identity information that they grab.

What are the common ways that you seefraud detected and. What are the common things that, people will do? One thingI recently learned is that it's like a group of people who, who start to changethese attacks and, and it's really more of like a team. It's, it's almost likea company of sorts and, and they're so strategic and organized.

So, yeah. What are the common waysyou've seen fraud? Being, not only detected, but also how are they using fraudto gather people's information? And is it just information or is it more..  

Ravi: Yeah, no, for sure.Yeah. I mean, I think the, the I would just say that a as consumers, we don'tsee all of, most of this happening behind the scenes, but, but just us, me, thebanks and financial institutions do a lot.

They're really like, they have sleeplessnights trying to. The customers, but yeah. But I, I started to appreciate it atsimilarity and, and, and it Effectiv. But yeah, I mean, for, for a, for alayman like you and I Julian, like, I think the most obvious kind of fraud thatwe would face is identity theft, right?

Like, like you mentioned. So someone.Steals our credentials, use our name or social security number to open upaccounts, apply for loans, and then just disappear. Right? So, yeah. So that'sa pretty common use case. And nowadays, I think that, that's on quote unquotethe account opening side. So someone applies for an account or a loan on yourname.

The, the second very common use case isactually transaction fraud where. . Either they steal your credentials, right?Let, let's say you have Yeah, like a Venmo app. So they, they use yourcredentials to move money out or which is get something that's getting a lotmore popular is like social fraud, right?

So someone, yeah. Like, like the datingfraud. So someone like. Try to create like relationships and then Yeah. Coaxyou into sending, sending money to them. There's also this elder fraud where,where frauds to target like older folks and again, like try to coax them intosending money somewhere.

I mean we, we've seen the Netflix show .That's a very, very, that's getting very, very common. Right. Especially reallywith, with the ramification of real time payments where the money, where youcan move money immediately, right. Previously it was checks and ACH where therewas some opportunity to pull back money.

Right. Because there's some time beforethe money moved, but, but with. with Venmo and Zelle and RTP and so on thesocial engineering frauds are, are really proliferating.  

Julian: And, and from aninstitutional level for that, mm-hmm. say, know, I know you've worked withcredit unions and banks and other kind of organizations from an institutionallevel.

Are they feeling attacks, kind of, bruteforce going through, say, firewalls and all the security measures? Or is itmore of a kind of a, a strategic and internal thing where they, I know onething I've gotten before is a message from an email, from a CEO asking me to doa specific task in a very obscure way,  

But, but is it, is it all like that? Arewe, are we seeing a task, internally and, and are, are they becoming moresophisticated and how are they becoming sophist? .  

Ravi: Yeah, yeah, no, greatquestion. Julian, so I think hit the nail on the head, right. So I think themost common but also the area where there's been a lot of development ininvestigation is on like the cyber threat side where there are hackers tryingto like hack into your system, steal credentials, and then.

Either like blackmail the, the financialinstitution into paying them before releasing the data back, or actually usingthat data to log in and move funds out, right? So, yeah. So those two things,but, but now there's some great cybersecurity companies in place and a lot offinancial institutions now, even in the.

They're highly encouraged to havecybersecurity insurance now, right? So, so that the customers don't getimpacted at least financially. But then the second is the social stuff, right?Which is a perfect, great example that you said. , someone taking over theCEO's email address or some senior executive's email address and, and thenusing it to email like the financial finance department to via the funds,right?

Or in this case, writing to the bank orcalling the bank saying that, Hey I'm calling from so-and-so org, I have a hugeaccount with you. I urgently need to pay a vendor. Please wire this, this moneyto this account. Right? So that social engineering definitely happens. Theother thing that banks and financial institutions face is synthetic ID fraud.

This is what this, the customers don't,don't face the heat of this, but the banks do. Mm-hmm. where someone justcompletely fabricate, fabricates an identity. Right. So they'll use likethey'll call themselves Julian, they'll use my s s. Someone else's emailaddress, a completely fabricated identity.

Mm-hmm. , and then create an account,apply for a loan, and then disappear. Right. So the bank gets hit. Wow. Verybadly because of it. Yeah. And the other thing is first party fraud. Right? Sosomeone applying for a loan. with no intention to repay the loan. Yeah. or, orapplying for a card with no intention to to pay back the expenses on the card.

So this is called like first partyfraud, so someone doing fraud on their own name. So that's, that's gettingpretty common as well. Especially, I mean, during economic downturns, peopletake advantage of right of these loopholes and.

Julian: Right. Yeah. And, and,and when, when they're doing that is, or I guess in the ecosystem of fraud and,and attacks and things like that, that we think about.

Yeah. Is it that they're getting moresophisticated or is it that the volume of them is increasing? What's, what's,what is, what are you seeing from an institution customer level that Yeah. Thatwe're unaware of is, like I said, yeah. Is it, is it an increase in activity oris it sophistication, or is it both?

What have you in, in yourexperience?  

Ravi: Yeah. I think fraudhas been always there. We are getting to know about it a lot more right now.Mm-hmm. , but at the same time it's fraud detection is a CATA mouse game,right? So you build systems, you build AI models to detect certain kind ofbehavior and stop, but the fraud starts just, just try to keep getting aroundit.

Right. , it's, it's an exciting spacefrom a technical point of view. Yeah. Because it's a never solved problem, butit has real life implications, right? Yeah. So real money being lost. So yeah,I think one, the volume of attacks are just going up, right? Because the attackvector is, is now much larger, right?

So they're, they're about 10,000 banksand credit unions in, in the US itself. There are now thousands and thousandsof fintechs that are built on top of these banks, right? So Neobanks yeah. Cardissuing companies and so on. So there's so many, so much activity happening inthe financial sector where.

Consumers like you and I have so manyoptions, right? For, for, yeah. Financial services. You can just download anapp, create an account, and you'll get a credit card shipped to your homewithin a day, right? Yeah. Yeah. So, so there's so many of these products now.So the attack vector for fraudsters is growing, right?

So now they can. target the FinTech orthey can target the bank or the financial, like special financial servicescompanies that are popping up. So, so, the volume is growing for sure. Yeah.And then with technology, right? So the sophistication is, is also definitelygrowing, right? So the same AI deep learning models that we used to detectfraud are also being used by the fraudsters to, to defraud.

So that's two. Third is thesophistication in, in social engineering, right? Like, like we discussedbefore, they're getting smarter and smarter, even beyond technology to, toconvince people into sending money to them. Right? So this is call, yeah, likefriendly fraud or, or elder fraud and so on. , you are the one actually sendingthem the money.

But, but, so the bank can't do anythingright? Because you, you putting your credentials, you have sent the money , butthe point is someone actually defrauded you, right? Yeah. So it started offwith the Nigerian prince thing way back when and now has gone.  

Julian: I know. Now, now it'slike people still, yeah, yeah. Now they're grabbing people from, from youractual life and putting you in scenarios.

Right. I remember knowing someone whowent through a scenario where they it was like, they had bought a ticket thatan agent had, trans transferred their number and they had to get a gift card,and it was all this whole gamut to purchase the gift card. Yeah, yeah, yeah,yeah. The social engineering, it's like, it's putting somebody into a pressurecooker in a tight situation trying to capture them.

It's, it's successful. It's sosuccessful in. We know about people's behaviors and before we go deeper into,AI and, and, and, and especially, a lot of questions around ai, especiallynowadays with chat gbt, really popularizing AI movement overall. Not sayingthat it's doing anything similar to what you're doing, but it's popularizingthe idea of it's value.

It's a tool. Yes. But thinking abouteffecti. Discuss with the audience a little bit of you. You talked, you talkedabout it, you know that that startup bug kind of, you, you had an itch that youneeded to scratch . Tell us what Effectiv does the problem that inspired youand also what were they, what were people using before Effectiv?

Discuss that.  

Ravi: Yeah, yeah. No, forsure. So Julian yeah, with Effectiv I mean, we have been, we did this in thepast with similarity, right? But, but with Effectiv, our main goal was to. Moremid-sized financial institutions. So like you mentioned, credit unions,community banks, other mid-sized lending companies, and then fintechs, right?

So all of them. Fall into the midsize segmentof financial services industry. So that was our goal, right? To serve them.Prior to that there were a lot of very sophisticated solutions for theenterprise sector, right? Like the big banks like Chase and boa, they hadaccess to really, really sophisticated systems.

Similarly, was that one example, butthere are a bunch of other folks that were building to. and they had thein-house resources to build systems as well, right? Yeah. So they had, theywere building like using price sophist, educated AI and so on. But the smallerfinancial institutions don't have that.

Yeah, right. So they don't have thepeople, the skillset and even the monetary resources to do that. And, and inthe US. The C two thirds of the US Population Bank. Mm-hmm. with a credit unionor a community bank. Right. So they, so they, they're extremely valuable to theAmerican society. And they drive most of the small businesses in, in thecountry, right?

So they're very, very critical to theeconomy. And we felt that this was. Huge missed opportunity, right? So there'sso many such financial institutions that are so critical. To our society, butnot getting the same access to technology. that yeah, the bigger folks domainly for multiple reasons, right?

Like they cannot pay that much and theydon't have the skillset to maintain and right, like build solutions on top ofsophisticated systems. So we. What we did was go back to our drawing board andfigure out is there a way to build an enterprise grade fraud detection platformfor, for these folks, right?

Yeah. Uh, Can we bring down our costs sothat we can charge them appropriately? Can we make our systems simple enoughfor, for 20 employee credit union to use us. Yeah. Right. And then have as goodas fraud protection as as chase. Right. Right. So, so with that intention, wewe, we were, were try to build Effectiv because one really, reallysophisticated technology is now available.

Right. So especially in the machinelearning side and ai. Where we could do this very economically and can do it atscale and to like, building on cloud and other, other technologies that areavailable, which can really bring down software costs, right? So if you areable to reduce our unit costs, then we can charge that much lower to ourcustomers as well.

So I think technology, domain knowledge,all that kind of worked for us to build something for them. . And with Effectivwe, because we are serving this segment of folks we try to build a full riskinfrastructure for them, right? Mm-hmm. . So we want to become their riskengine for, for a credit union, our bank.

So we operate across the board, right?So starting from onboarding, so like we discussed, it could be a loanapplication, a deposit account, opening application, car application. BN Pevent, whatever it is. So, so we, we do fraud checks there from KYC to moneylaundering, to synthetic id, fraud and so on, followed by transactions.

So, the, the financial institution canmonitor wires, ach, Zelle, rtp, yeah, check deposits, any ATM withdrawals, allof those on Effectiv as well. And also monitor things like login. Pin change,password change, those kinds of within Effectiv.

And, and the interesting part is, . Themore that they enable, the better every evaluation gets, right? Because right,they're, if they're, if we, if Effectiv, gets to see both check deposits aswell as ATM withdrawals, we are now getting more data about the user. So we areable to build better heuristics and.

We get to know, hey like Julian depositschecks on on the 16th and, and on the first of every month withdrawals are at8:00 AM withdrawals are at 11:00 AM. In the morning at a, at a Walmart. So weare able to create all of these heuristics about the users and members, and weare able to predict behavior and also detect anomalous behavior in a very, veryfine, fine grain way.

Julian: It's so fascinatingthinking about the way you, you protect and, and how you kind of assess riskand things like that. I think a lot of times we commonly think that you'realmost at a, like an AI or, or a battle between the attacker and, and, and yourown sophisticated software, but from what I'm hearing, it's, it's more sobetter understanding the users and, and their behaviors.

Right, exactly. The type oftransactions. Yeah. And so are you essentially, when you say detect risk is.Some kind of behavior that's outside of the norm. And then how do you know ifthat's one thing is like, how do you know if that's just like them taking avacation versus, actually somebody taking their transactions?

Is the model just kind of trained moremore sophisticated? Like you said, you have more evaluations, you understand,you use it that much more in their behaviors. . But is there any case wherethat that, is, is, makes a wrong assumption? Say I'm on vacation or say it I,I, I've moved but didn't inform my bank.

Are there things around that where wherethe model say, say, doesn't, always predict it correctly. Yeah. Curious,curious what you have to say about that. .

Ravi: Yeah. Excellent.Excellent question, Julian. Man, lot more about this topic. I don't expect it,but that's that's awesome. Yeah. I mean, exactly that, right?

Like first because we are not justcreating heuristics and models that a particular user level we are also lookingat the overall population, right? There are certain things that you can, youcan actually observe that like, okay, folks living in San Francisco mightholiday in, I don't know, like, might, might be in Tahoe on the weekends.

Right, right. So something like that. Sothere are these overall population trends that, that we are able to look at andreduce what we call. False positives, right? Yeah. Right. So even though yougenerally live in San Francisco, but hey, certainly there's an ATM withdrawalin Tahoe. So that it means we are, maybe this is the first time you are goingto Tahoe, but a lot of population trends.

where this kind of behavior we have seenin the past, and this is good behavior, right? So, so we are able to fall backon overall population behavior when there's something that, when we havenoticed some anomaly at a user level, right? So we create these models andtrends at both. At both the levels.

And that's how we try to reduce thesequote unquote, what you call is false positives. Right? But there's also a verystrong feedback loop, right? Right. And it, we, we can take what we call aslike step up verifications, right? Mm-hmm. . So let's say there's a fir thefirst time we are seeing an anomal, , maybe we need, need not block thetransaction, right?

So we just notify you with a message,right? Right. The second time we see an anomaly or a bigger anomaly, then wepause the transaction and call you for verification. Or we request a two factorRoth, right? The bigger AC . If the anomaly is even bigger, then, then we stopor block the card for you, right?

Without you taking an action and, andwait for you to call the bank back and, and enable and so on. . And if it'seven further, like let's say we are seeing a transaction happening from a botknown botnet or a to node or, or from a cloud IP address and things of thatsort, then we just block the account, right?

Yeah. So you can, we can take these stepup actions that can start from very like a small action like just a notifi justnotifying you, right? Hey, that transaction has, has. . If it is not, you justlet us know. Right. But we'll let it go. Right? Right. So from there to all theway to blocking the bank account itself we can, we can have these step upchecks.

And if, let's say we, we ask you for atwo factor and you have authenticated, then there's a quick feedback loop whereour model quickly learns that. Okay? Yeah. We, this was a false positive. Sowe, we, we took two harsher dec decision. So next time we see an action that isvery similar, either for Julian or for anyone else who fits the Julian profile.

Yeah. We'll, we'll take a more lenientaction, right? So, yeah. So that, that's how we try to Keep addressing thisissue, like ensure the customer has great experience, but at the same timeprotect them, from, from fraud. Right. It's, it's a very delicate balancebetween the two. But we, but with AI and, and the way that we are able toretrain models at speed this is getting more and more.

Julian: Yeah. It's sofascinating. Also thinking about, the, the two, two factor identifiauthorization, excuse me. And also, and, and how much kind of human input isstill involved in training these models, right. From like the customerstandpoint. And it's, it's so fascinating to think about how that kind of, it,it works in tandem, it's not like one, solution.

It's all, on a platform throughsoftware. Exactly. It does take inputs. That, learn and train itself. So it'sso fascinating to think about how sophisticated it can even more grow in, in termsof it's, it's it, it's, it's accuracy right in, in detecting fraud or also justunderstanding behaviors and things like that.

And I'm curious, and, and I'd love foryou to tell the audience, tell us a little bit more about your traction. Howmany, how many customers do you have now? What's been exciting about the recentgrowth that you've seen, but also what are you looking forward to in, in, notonly this year, but in the, years to come in terms of the, the direction thecompany's.

Ravi: Yeah. So we, it's justbeen little over a year since we've been in the market. So we started thecompany mid, mid 2021. But. The first six months were heads down productbuilding. Yeah. . And in early 2022 was when we, we actively started selling.We've had a really great first year and we are very lucky about we now haveabout 13 customers across fintechs and banks and credit unions.

Using us very actively. Like the frauddetection is a very critical piece in the flow, right? Mm-hmm. because theystop, wait for our response and continue. Either it's an app application for aloan or a account or a transaction. We are in, in the critical flows. So, soit's very important that from a system's point of view, both our efficacy is.

But our we are also very, very stableand, and scalable. Right, right. From purely assistance perspective. So all ofthat has been working well, like we haven't had a single second of downtimeover the last one. Yeah, it's pretty impressive. A touch word , but, but it'sbeen great. Like. I think it, it also comes back to our team's experiencebuilding these systems in the past, so we could just build on top of what we'velearned so far.

Right. So, yeah, so that was that waspretty advantages for us. And and yeah, we are given the first year success, weare very ambitious this year. We want. Grow our customer base even more. Soyeah, very, very excited. We are about 25 people now. Yeah. We are a fullyremote and distributed team.

So, which has also been very interestingbuilding that out. Yeah. And it's been working great for us because we, we, weare, Across all time zones across the globe. So we are able to provide greatcustomer service to our customers, right, because. nowadays, like financedoesn't stop when you sleep.

Right? Right. So the transactionshappening 24 by seven, and our team, there's someone on our team at any pointin time of the day. So, that's online and monitoring our systems, so

Julian: that's incredible.And, and thinking about, whether it's, externally or internally, what are someof the biggest risks that Effectiv faces today?

Ravi: Yeah. I. We are asmall company. I think obviously the things happening in the banking sectorright now was a little scary. We were also SVB customers, . We had a sleeplessweekend. . Yeah. But things work out well. I mean, we are we are so, sograteful to F D I C and the US government stepping in.

Right? Like, I mean, yeah, obviously weexpected the same and. When held through very grateful. And but yeah, I mean,with. We were a little worried on, on hey, selling to banks, how would it, howwould it change? Right. So would, would banks be a lot more careful especiallytrusting new, new vendors?

Would they even procure new vendors andso on? Mm-hmm. , but fraud is so critical. , right? Yeah. What we are seeing isactually the. Spike up since, since those events that just people want toreally improve on, on their risk management systems. Yeah. Across the board,right? It could be credit risk, fraud, risk, compliance, risk, all those kindof things.

And if you provide better economics, I.The banks are willing to switch to new emerging technologies a lot, lot morenowadays, which was in the case few years ago. Right? If they had a system inplace that was working somewhat, they. Really had no motivation to switch to anew vendor. Right? Right.

But now they're very, very eager. Right.So if you're doing something really cool, I mean that like next level andyou're able to reduce costs for them. Oh. And they have the same interest levelas as a FinTech. So , so that's been, that's been very eye-opening, right?Yeah. And we want to really take advantage of that increased interest and, andgrow very aggressive this year in building our.

Julian: It's so exciting tothink about how much behavior has changed with a lot of even traditionalorganizations, right. And right. Yeah. And if you're not looking for the newesttechnology that's up to date because things are moving at such a rapid pace,then Exactly. That you often, yeah, you often find yourself behind in, inwhether it's protecting your customers or even just running an efficientorganization.

I mean, there's so many legacytechnologies that are starting to get ripped out. and the replacementtechnology, I'm sure you've seen and you've built that Effectiv is, is beingless and less cumbersome to actually implement into organizations because ofExactly. Not having to host on their own server, being able to use the cloud.

Yes, exactly. Taking all that, thatweight essentially from the technical side outside of, outside of theorganization, and thinking about all the possibilities and if everything goeswell, what's the long term vision for.  

Ravi: Right, right. No.Yeah. For sure. Julian, I think the first wave was the pandemic. I mean, withthe lockdown.

A lot of banks and credit unions. had togo digital, right? So they had to move their account onboarding transactions.So no more like going to the branch to open up an account or apply for a loan,or even like deposit physical checks, right? So everything moved digital. Andonce you move digital, Again, you get exposed to different vectors of fraud,right?

and and you, you no longer can use a 30year old fraud detection system, which takes batch files end of day, toprocess, right? So, so there was already a strong motivation for a lot of them,like you said, even within smaller banks to, to adopt new technologies. Andthen with, with the proliferation of ai, like you said again fraud starts areusing it.

If the banks don't use, then they,they'll be in a really bad place, right? So, yeah. So I think adopting newtechnologies, going to the cloud, which again saves so much cost and it isactually a lot more secure than having systems on premise, right? So, right. Sothem getting more comfortable using cloud software.

Co things costing less people gettingmore efficient. Yeah. Having more sophisticated systems in place. So everythingworks out really, really well for, for the banks. So, yeah, I think our visionis to really change the game for, for banks and trade unions, especially themid-sized ones who we felt.

like I said, very underservedpreviously, but I think everyone, I mean even our, even our like competitorsand so on, I would like really urge to urge them to look at, look at thesector. I think they're very eager to work with tech companies like us and Ithink it's a great opportunity. I think, and I know it might sound cliche, butI think.

There's an overall greater good, right?So if you help, right, credit unions perform as well as big banks. The economyjust gets far better, right? So, they can serve small businesses better, theycan serve common folks like us better. And people may not rely I mean, yeah. .Yeah. Every financial institution would be safe.

Right? Right. So you need not just moveall your money to chase or be and feel like you are safer there because thatwould just like tilt the, the balance of power. Yeah. To the bigger folks,folks.  

Julian: Yeah. I love that.And. As technology continues to grow and expand, how accessible it is to, likeyou said, kind downhill and or those who aren't as large or don't have aninfrastructure or don't have teams around them, say, a chief security officeror somebody who deals with that sector in particular with the technologies andplatforms that it, it's almost like having that unit already kind of built inand plugged into to your company and, and I'm sure you're working on more waysto make it simple and easier to.

And work more in tandem with your. Ilove this next section and, and we'll, we'll, we'll breeze through it realquick, but I'd love to ask some founder FAQs. So I'm gonna ask you some rapidfire questions and we'll see where we get. So, first question is, thinkingabout just selling into mid-market or mid-size kind of companies, what are someof the challenges you face being that.

There might be restrictions in the teamthat they have or the technology or current infrastructure. What are somechallenges that you were unforeseen when you started selling into this kind ofcustomer base? And, and what are some of the benefits in terms of beingassociated with those customers or, or, or working with those customers?

What have you seen was the challenge?What's been a benefit? .  

Ravi: Yeah. Great. Actually,both was the same thing. , yeah. Really. So the challenge was actually getgetting into the space. Yeah. Right. So it's a, it's a very close knitcommunity. Yeah. Like all the credit unions work very closely with each other.

All the community banks work veryclosely with each other because they don't compete. Right. They have very clearcharter. Right. Unlike retail banks or commercial banks, like they don't, theydon't compete for the same person or the same, same account. So they're verycollaborative, right? So for a, for a new vendor to crack into that space, youhad to really win some, some accounts work very hard convince them when theirtrust before you enter.

But once you've won the trust of We areseeing that they are so much more open to recommending you to their peers,right? Yeah. So there's a lot of word of mouth, so the same. Point that was aslight barrier to enter into that space. Yeah. Has now become a big advantagefor us. Right? Yeah. So once you entered the they, they really put want toensure their peers are successful as well.

So, so if you're, if you got a few ofthem as your customers, but made them successful, then I think you are set outto, to succeed in this space.  

Julian: I love that. I lovethat. And another question I would like to ask, being that. A lot of companiesare adopting, blockchain and crypto assets as, as another asset class, and kindof thinking about the sophistication behind that technology, not only beingable to, look through it and validate a transaction, but also make sure thattransactions once completed, there's no fraud in there as, as we've seen somany different things.

Happened within the crypto space about,when it's kind of in this limbo period, some, someone there can be a bad actortaking out money and, and not fulfilling a transaction. How have you beenincorporating a lot of that technology into fraud detection and what'sparticularly if you have, what's particularly a nuanced about that, that thatisn't similar to web, web two technology that Yeah, you have to consider when.

in building.  

Ravi: Yeah, great question.We, we actually do have a few crypto companies using us as well. Theinteresting thing is more and more of them are getting regulated similar tolike via model Yeah. Financial services, right? So they have to go through K yC fraud checks before onboarding someone onto their wallet or, or, and thingsof that sort.

So, so the problems are very similar.Quote unquote, on ramp, right? Yeah. So when, when they're onboarding someone,within the crypto ecosystem, things get very different. You need to haveslightly different technologies to, to look at on chain transactions and ableto identify fraud and money laundering on the chain.

Mm-hmm. , that's a very sophisticatedspace in itself. We are not, I, I would be lying if we, if I say we are expertsthere, but we partner with some of. Experts in that ecosystem use theirknowledge and, and technology within our platform to, to adjudicate thatwithin, within the ecosystem where we are operating.

This is still fairly new, but getting alot of attention, right? Even banks and credit unions are very, very eager toprovide crypto related services to their members and customers. So we areseeing that happen. . But right now we are in that OnRamp phase, right? Yeah.So where it's still somewhat similar to, to fiat money related services.

But, but I think ourselves and everyoneelse in this ecosystem really need to ramp up that game. Yeah. In the. .  

Julian: Yeah, absolutely. Ialways like to ask this next question cause I think founders are awesome in theways that they extract knowledge from anything that they ingest. So whether itwas early in your career or now, what books or people have influenced you themost?

Ravi: Oh , this was actuallyrecommended by, by my co-founder, but I've. Reading this book called ChallengerSales. I'm sure a lot of, a lot of you and, and Julian, you might have heard ofit. I think it's like for a tech and product founder who, who started a companyYeah, say, Get onto salesmen. This , this is so much more critical and it is somuch more a science than, than an art.

I think the media portrays it as if it,people are born with it, but, but you can learn it like any other, any otherscience and I think I would recommend any founder learning sales. The day thatthey start the company. Right. I think we did a mistake. I, I mean, mepersonally though, my co-founders are pushing very hard on, on picking it up.

I, I never paid enough attention and Iregret it for the first six months. Right. I was just like, Hey, heads down,let's build a product. It'll sell itself and so on. But that's not the case.Right. And I was very lucky to have really great co-founders who picked up theslack there. Yeah. But. , but yeah, cha read up, gobble up all the sales booksthat you can.

Yeah. I mean, there're different kindsof techniques, like medic and all that kind of stuff. But there's somethingthat will work really well for you and the early days is when you have toexperiment very quickly, right? Like what methodology, what kind of sales. Setup and funnels are going to work for, and GTM strategies are going work foryou.

So you can do that experimentationeasily only in the early days, right? Yeah. So, so try it out. Start readingsales books. Sorry to bring such as, such a draft topic, but but it's critical.Yeah.  

Julian: A lot of foundersbring it up on the podcast about the necessity to learn sales. It's just ageneral function of, of how.

Not only, get new customers, but also tokind identify the, the sales culture for the company moving forward. What worksin your sector, what conversations are you having? What rejections are you, areyou seeing? And it's like almost like a data download in the beginning to, tofigure out, you're almost training your own model in, in terms of youroperations in sales motion to try to figure out, the methodology and how tocommunicate in your.

It's brought up a lot, so it's not adrab topic. It, it's definitely one, I think more founders, more founders havea similar experience where they're like, I needed to have learned it a littleearlier. But once you kind of get into the motional building company, youunderstand how critical, especially at the CEO level, and building thoserelationships and, and getting people to trust.

And, and then, and then obviously thenthere's a host of new problems that, that you have to address down the line. Ialways like to ask this I always like to make sure we don't miss anything. Andbefore, obviously I know we're coming close to the end of the episode, I wantto get, your websites and your plugs and your LinkedIns.

But before we do that, is there anyquestion I didn't ask you that I should have or that you would have liked toanswer?  

Ravi: No, this was both awonderful, Julian, I had such a great time speaking with. Yeah, I mean, likeif, if you're interested, anyone's interested in the financial space or fraudspace, like we are super open to speaking with you, especially if you're earlyfounders.

We are. So, I mean, we would love toshare the mistakes that we've done and give whatever small advice we can but.Yeah. I mean, FinTech and financial space is always super exciting, so Yeah.And so encourage a lot of you to try. Yeah, exactly. I would say it's changingso much nowadays, so, yeah.  

Julian: Well, last little bit.

Ravi, tell us where we can find you.Give us your websites, your LinkedIns, where we can not only support you as afounder, but also Effectiv and, and what the technology is doing and being afan of, of the mission that you're driving and, and who knows if we're acustomer, how can we get in touch and, and start using the technology.

Ravi: No, of course. Yeah.Please write to me any time of the day. I have a two-year-old kid, so I don'tsleep , so I'm, I'm on my email is Ravi, r a v i, Effectiv E F F E, CT I v.There's no e@theend.ai right to me at any point in time. My website is Effectivai. Search for Effectiv AI on on LinkedIn.

Please, please follow our page. There.Same thing on Twitter. Please follow our, please follow us on Twitter. But, butplease do write to me at any point in time, either you want to try out aproduct or just want to chat about the space. Always, always open to it.  

Julian: Amazing. Ravi, it isso incredible.

Not only learning about your background,your experience with startups, but what you're doing at Effectiv, how thetechnology. What are the challenges that you're facing in terms of, thecustomer that you're, that you, that you're addressing, and the space thatyou're addressing is, such a pleasure learning all those insights, advice forother founders as well.

And so I hope you enjoyed yourself onthe show today. I'm excited to see what's gonna come up Effectiv in the nextfew years. And we'll have to do maybe a second round, but I hope you enjoyedyourself and thank you again for being on the, the show today.  

Ravi: Yeah, thank you somuch, Julian. This was, this was so great.

Yeah. Thank you so much for thisopportunity.  

Julian: Of course.

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