Dr. Sean Stein Smith, CMA, CPA, Assistant Professor at Lehman College (CUNY), shares some of his expertise around the topic of blockchain and explains how other major focuses in technology fit into today's accounting industry. Dr. Sean Stein Smith was named to the 40 under 40 in the accounting profession in 2017 and 2018, is a member of the Advisory Board for the Wall Street Blockchain Alliance, and is widely regarded as an expert at the intersection of blockchain, cryptocurrency, and accounting. He has been published in numerous journals and magazines and has presented at a number of conferences and events on the topic of blockchain. In this episode, Dr. Stein Smith tells us about the different types and options for blockchain and how this technology fits into accounting.
Welcome back Count Me In. I'm your host, Adam Larson joined as always by my cohost Mitch Roshong. Today we have another episode about the captivating topic of blockchain and who better to listen to about this topic than Dr. Sean Stein Smith. Mitch, you talked to Sean. How did the conversation go? Thanks Adam.
Yes, Dr. Sean Stein Smith is an assistant professor at Lehman college in New York, but he is also on the advisory board for the wall street blockchain Alliance. He does countless talks on blockchain and recently received the NJ CPA 2019 ovation award in innovation and our conversation, we talked a lot about blockchain but we also talked about other technologies and innovation which we'll get to in future episodes. Let's take a listen to the first part of our conversation.
Blockchain is a very hot topic when it comes to emerging technologies and as being brought into accounting very frequently, however many do not fully understand the different types and options for blockchain. Can you please explain that to us? Sure. Thanks. So
Obviously the whole topic of blockchain, cryptocurrencies and that whole sort of blockchain space is arguably the hottest topic in accounting and finance for the last 20 years. Right. But it's always important to know sort of what exactly is being talked about, whether it's being talked about internally inside the firm or externally, right. Offering advice or some services to our external clients and partners. And sort of the term blockchain is tossed around a lot, but it's really more of a umbrella term than one point of data, right? Because a blockchain can be a public blockchain, it can be a private blockchain or it can be a consortium blockchain or basically sort of a joint venture, right? And so a public blockchain basically is the true idea of a blockchain. It's totally open source, decentralized model of storing and then sharing information in a encrypted manner. And it's the type of blockchain that is probably what most of us are going to think of in our conversations and is also the type of blockchain net underpins Bitcoin and Tther. So on top of being the biggest option out there right now in terms of active users, in terms of you know, individuals and and, and all the rest. It's also the probably the most high profile one. Now from an enterprise point of view though, having all of the corporate data on a blockchain, right? And please don't forget, even though the blockchain is a unhackable or it has been unhackable as of right now having your information stored on a public blockchain is going to give some corporations pause. Right? So and on top of that though, the actual way that blocks of data are added onto the blockchain, the proof of work model is awfully tough actually do because it takes a lot of hardware, software and also power, right? So really from a enterprise point of view, public blockchains are moving out of favor and it's pivoting towards more of a private model or a consortium model. So a private blockchain is basically a, it's almost like a traditional ERP or a application hosted inside a affirm, right? Cause it has the traits of a blockchain, meaning that it's a group based model, basically, that it's immutable in nature and that it's a permanent record. Basically after data is added onto this blockchain, it's a permanent record, can't be altered on that block by block basis. And sort of the best example to highlight this is the joint venture, right? Or the joint venture model built up by Walmart and IBM. So basically in that context, Walmart is the organizing firm and so has organized the actual blockchain, hire the programmers and all of the coders to actually build it out and isn't pushing that out to its network. And so that's, that's almost like a hybrid model, but it's more like a traditional ERP or augmented by some blockchain traits. And sort of the third big, bucket is a consortium model. And the best way to sort of think of this or to highlight this is to almost think of it like an industry focused option, right? And it can be retail, it can be healthcare, it can be food safety, it can be finance or accounting. Right? And so the big four firms have actually partnered up to form a consortium model or a joint platform basically to help them audit information out of banks. And so this consortium model currently is being used and tested with 20 banks headquartered in Taiwan. So it's going to be interesting to see sort of how this whole field evolves, right? Because all of us who got interested in blockchain probably via Bitcoin, right? And sort of that's a public blockchain model. Totally open source for, any company to join or to be a part of. But from an enterprise point of view, again, for me, the accounting and an audit point of view that's really not as helpful as a private blockchain. And again, a private blockchain is more like a traditional ERP system augmented by some traits of a blockchain. But the area that I'm most interested in going forward is this idea of a consortium model or basically a industry group or a focused type of blockchain for a certain industry. Again, be it accounting, healthcare, finance is not really as important as the idea of a common platform to store and to actually transmit data in a manner that is encrypted and safe. Right. Both for the institutions involved and their end users.
That's great. Thank you Sean. Now artificial intelligence or AI is another major focus in accounting when it comes to technology, but what is the difference between AI and RPA in terms of accounting purposes?
So the field of AI, right? It's been talked about in the media mainstream since the 50s right there there are whole movies, you know, focused on the applications of AI for good and for bad, right? But as far as a accounting focus goes, AI really is not very yet for most firms but the idea of RPA or robotic process automation is actually more tangible and more, I think sort of are currently useful for firms. So sort of the best way to illustrate the difference between RPA and AI is to almost imagine a pyramid or a ladder. Right? And so the sort of the first step there is basic automation of processes using your current ERP systems, be it you know, Oracle, SAP, Hyperion, zero, QuickBooks, whatever you are using. That sort of baseline automation. RPA though is that extra layer right? Where it builds on that baseline automation, that baseline. So documentation and then helps firms automate either entire processes or pieces of of processes. Now a interesting point to keep in mind though with RPA is that even though we are having a conversation on the counting and on finance RPA, that idea and that process, it's actually being used in a whole host of industries, right? So HR, right? HR, every person who is hired is obviously a a individual and is hired as such. But that underlying HR process, right, the onboarding process, benefits process, all that stuff is actually pretty consistent from person. The firm is actually a consistent from person to person and firm to firm, right? So then automating those processes and then really sort of thinking of how RPA can be used at a much broader level. Be it in the hiring of people, inventory counts, get bank recs. Obviously all of those types of things really unlocks sort of the true upside of it. And also versus AI. RPA actually has software tools and firms that have been out there in the marketplace for the last 1520 years, be it UI path automation anywhere blue prism. There are a whole host of firms out there who are focused in this RPA space, have products that work and actually have a actual track record of actual client service over the last 10, 15, 20 years. So AI is sort of that ultimate end goal, right? Where all of us want to be. And so that's basically where the, you know, data is, is automated, it's processed. And then on top of that, those tools and processes that are put into place by us actually can help us analyze that information on a continuous basis. Right. But just a quick point to analyze on AI, is that AI, like blockchain is often tossed around, but it's more of an overarching term than a one focus data point? Right. So there's computational AI, there's all sorts of AI is out there. So if our conversation, probably computational is the most important, but there are all kinds of AI options out there. So unimportant point to keep in mind on top of ensuring that your underlying processes via your documentation, via automation, via RPA tools are actually ready for AI. It's important to also be able to have a conversation as to what kind of AI is actually most important for you, the firm and for your external clients. And sort of a last point here is that firms want to often sort of jump ahead right to AI, just a full blown AI project, but it's not really possible to actually go from here to AI, right? It's important to make sure that your, your processes and your controls and your data flow is actually built and then controlled in a way that is actually going to help you use the AI tools, right? I mean, because AI is a fantastic tool and there are great software programs out there, but if those underlying processes and that data aren't controlled, aren't cleaned or normalized, it's going to be awfully hard to actually get the benefit out of AI that you are going to want. So to sum up, probably the best way to envision the RPA versus AI is sort of think of it as, you know, part one is automation, part two is RPA, and then the ultimate end goal. Part three is that AI or that you have self learning type of software. But it's important to make sure that as you're having conversations, uh, both internally and externally, your processes and your controls are actually moving upward to.
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