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AUDITCHAIN & BUSINESS CONTROLS



What does the complete automation of accountancy using process-control NFTs mean for accountants? Discussing Auditchain, the world's first decentralised accounting, reporting, audit and analysis metaverse that automates and provides proof of assurance on the world's financial and business information.


Webinar transcript, recorded 1 June 2022, on Youtube here.

With Andrew Noble and Electra Frost, accountants.



Transcript

+ Slides


Welcome, future accountants on the blockchain!


Andrew Noble:

I was invited along to tell you a little bit about Auditchain. I said to Electra - you know, I'll talk about Auditchain but I really want to throw in some information about business controls as well. Because Auditchain is ultimately a kind of a business control and will provide business control-like functionality.


Electra Frost:

Hi, everyone, this is an Accountants On-Chain webinar and we're meeting Andrew Noble. You might know him from LodgeiT. We're going to talk about all Auditchain today but also business controls, and how it all relates to our own practice.


Assuming that all of you here are accounting industry professionals, that you use digital technologies, were probably part of the first early adopters of cloud technology and you’re interested in lowering your costs and being effective and efficient for your clients to be competitive. As we’re learning more about blockchain, we're thinking about ways it can be applied to our clients' businesses and looking at the tooling for their businesses. But do we ever stop and think about our own accounting practices?


We think about how our clients will learn-to-earn with future technology, and how they'll monetize their data. But maybe we should stop and think about how the emerging technologies will have an impact on our own practices. We're going to find out tonight about some accountants’ tooling that's not on the market yet, but it's being built out with accountants, and has the accounting industry in mind.


So that's why we're here. Take it away, Andrew.





Andrew:

Nice to meet everyone. I'm in Perth. I am a Fellow of the Institute of Public Accountants and a tax agent, and I still do have some clients that I look after. I run a platform called Logic, which is sold primarily through QuickBooks and QuickBooks Online, and it's taken up by their accounting firms. We also sell directly to the market for business owners who want to DIY into that sort of tax compliance space.


I'll dive in and tell you a little bit about Auditchain and how I got to know about Auditchain through Charles Hoffman, who I've been in communication with for a good 10 years. Charles Hoffman is a CPA out of Seattle in the US and was the inventor of XBRL, which is an extensible business reporting language. We're going to touch on XBRL through through this presentation.


Electra:

I don't think many of us are familiar with XBRL.


Andrew:

It hasn't been mandated in Australia, but it's certainly mandated for US GAAP, large companies have to submit their filings to the SEC using this, which is essentially machine readable data sets put into a format that machines can consume. XBRL can understand and read it.


Electra:

So rather than a PDF of a balance sheet, it’s in readable language that can be read by a computer?


Andrew:

Yeah, that's a good point Electra. You know, we as accountants, you could give any of us a set of financial statements, and we'd be able to look at those financial statements and make sense of them. We'll see familiar patterns in there, we'll see balance sheets, statements of financial position, statements of cash flows, profit or loss. It's the old term, but regardless, we'd be able to look at a set of financial statements and we'd make sense of it. And we can look at those financial statements whether it's on Word or PDF doesn't bother us.


But certainly if you give a PDF of financial statements the machine has a bit of difficulty So there's this language or this methodology for sharing information with machines when it's financial statement information.


In that case, if you use this syntax, or this language, which is XBRL, then those machines can make sense of the financial statements. And we'll touch on that more as we go through.


But anyway, through Charles Hoffman I came to meet the founder of Auditchain, Jason Meyer, probably just before COVID. He ran an event in New York and I had the opportunity to go over there and go to that event. It was all about getting lawyers and accountants together and getting them interested in building a technology platform, which would solve automation of audit. That's what we're going to jump into, as we go through this presentation.


That's a bit of the background as to sort of how I got involved. When I found out about Auditchain I subsequently bought tokens in the project. So that's how they brought the project to life.


Electra:

As a matter of disclosure, I've got some tokens in Auditchain too, and am staking it to learn and earn more.


Andrew:

Buying tokens and staking in token based projects is a whole new way of engaging in technology going forward. The great thing with token based projects is - especially in the case of Auditchain tokens - it gives you the ability to both be a stakeholder and at the same time, you can use the tokens for interacting in that data economy. And that's something we're going to cover.


LodgeiT is the company that I mentioned I'm a founder of. We have started Accziom now, which is another platform. Electra has put this whole event together to learn about Auditchain. So thanks. That's fantastic.


Here is the Auditchain introduction.


Electra:

There’s a lot in there to unpack. The world's first web 3 decentralized accounting, reporting, audit and analysis metaverse. I noticed recently they started calling it web3 and a metaverse. .. that automates and provides proof of assurance on the worlds of business and financial information.

So it’s a pretty big, pretty big plan there that they've got for the world.



Webinar agenda




Andrew:

So here’s the agenda. I obviously want to cover off on the problems that Auditchain aims to solve. As I've said to Electra, I didn't want to do this presentation without touching on business controls, which is something that I've been massively interested in lately, and I've got some bits and pieces that I can share with you around that.



Electra

As accountants, most of us are small practice owners and as such we’re deeply involved with our practice management software and all the controls around what we do.


Andrew:

Yep. And, you know, with Auditchain it's based around controls.

We’ll touch on Pacioli and what I call the robotic accountants. That is actually the XBRL reading machine that Charles Hoffman has been involved in. Then covering off on how the Auditchain platform and system works and how you can engage with it. And finishing the presentation by recapping around how the bits and pieces when it comes to audit when it comes to automating audit and business controls can rarely be brought to life in any business.



The problems with audit today






Andrew:

So, we all hear about these audit failures regularly. There have been plenty of audit failures over the years where the auditors just didn't manage to find whatever finally brought down the company whether it was fraud or, or just bad management or whatever. The reason for this is that audit was invented the way that audit is carried out now, which is very much around randomized selection. Subjective and conditional attestation was put together in the age when audits were carried out with paper.


But now we're in this digital age. Our old methodologies for audit don't work very well and hence why there's these failures. It’s believed we're moving into a world where we've got more open transparent ledgers that we're going to be working with.


Electra:

And although we're not auditors here, we share origins. As accountants we're like mini auditors. We're constantly in a way auditing all the information that we deal with.


Andrew:

Yeah, definitely. As a compliance accountant, myself, I spent my work life in compliance and that's actually something I've figured out recently. The compliance work we end up doing is always at the back of the problem and rarely solves a lot of the problems that we have with compliance. You're better off moving to the front of the problem, and figuring out why problems happen in the first place. A huge, huge problem for accountants right now we have more compliance than ever to deal with.


Auditchain proposed solution







Andrew:

So the solution that Auditchain is proposing is what they call streaming financial data. Essentially, they foresee a time when financial information streams through on blockchain or blockchain-like technology. Hence, here you can see Bitcoin style validation.


I've got some demos where I can actually show you some real life examples of how it doesn't have to be directly on the blockchain, but it could be like on a blockchain and you get a similar kind of solution. But certainly their long term vision is streaming real time data flowing through an audit engine, which is constantly carrying out validation. That stage is a little way off.


And certainly when I jumped into talking to you and demonstrating the patch to the robotic accountants, you'll sort of get a feel for where they're at, but certainly their long term plan is real time monitoring of accounting information.



The value of business controls





Andrew:

I did say that business controls is something we need to touch on before we really dive into the Auditchain stuff in more detail. This is something that I've been quite fascinated with recently. And let me just, I'm gonna jump out of here for a moment and just show you a couple of things over here. So you know, when it comes, and this is a mind map, so mind mapping technology, pretty interesting way to sort of have a look and understand things.


TheBrain view of Controls






Electra:

What are we looking at here?


Andrew:

Exactly what we are looking at is a mind map that helps you to look at something and get a very quick idea of what it is. That's under consideration. Here we're looking at internal controls, internal business controls, and you can see we've got the reasons for these achievement of objectives authorized by the Board of Directors, designed to provide reasonable assurance.


Determine if different processes require so you've got these pieces of information that point to the internal controls. And then from that from the internal controls down, you've got the types of internal controls internal control standards, and you can drill down into these so you can see here, we've got four main types of internal controls. Application controls, dependent manual controls, general controls and manual controls.


For most businesses, the issue with controls is when you've got manual controls, right? This is where you'd have an invoice that is generated on Word. And then that and then that, you know, that invoice is transmitted to a bookkeeper who then puts that into the system. So you've got manual steps, and then you'd have to think about how you're going to control that process.


Obviously with modern technologies, they allow you to do all of those steps from engaging with your customer, all the way through to the final invoice and that's all captured through digital workflow. So you've got methods for handling controls.





You can see here, you've got ways to jump through this and then look at the business processes. Obviously use your controls to manage your business processes. So what are your business processes, activities ordered in time and space? If you're going to have a mission objective with your business and business processes, then you can jump down here into the soft details.


A mind map is a nice way to explore and look around and get a very quick, easy feel for a knowledge space. That's why it’s called a mind map.


Read more about enterprise controls here: https://accziom.com/enterprise-controls/



ISAE 3402 audit


Andrew:

Now, we talk about ISAE 300, which is the international standard on assurance engagements. When we think about audit, we often think about the tick in the flick pile of stuff. But there's a whole other aspect to audit, especially this.



This is a 3402 audit. And that's more about managing your business controls like I was talking about, where you'd have an audit that goes into the enterprise and looks to see who has access to what, who's doing what, how are the systems deployed, and you know, as a result of how their systems are deployed, how are those how are those controls working, controlling the information and making sure that making sure that there's quality across the information controls and making sure that it's limited opportunity for fraud, and that kind of stuff to transpire.


Electra:

We're seeing more audit trails to kick off audits as we currently have visibility over many of our client controls, with training and documentation. It’s not exactly something that accountants or their clients look at very often, these diagrams of controls.


Andrew:

I don't think, especially in the smaller end of town, that there's enough effort put into thinking about and making sure that controls are well curated in the clients’ software. We don't really know what they’re doing. I think there’s a really great opportunity for accountants to move from compliance to control management, which would be doing things like, for instance, exactly what you're saying, going and checking who's got access to what functions in a software application. Checking that there are controls in place, permissions or or just finding the right software for your clients which would help with controls.


Electra:

So this is a way we could help our clients. Okay, yeah.


Andrew:

So great opportunity for all of us to help all manner of businesses right, putting in place the right controls.


Sarbanes Oxley Internal Controls - The Fraud Triangle


Now, here's another topic here in the control space: Sarbanes Oxley.








This came into place after Enron. It all starts with a fraud triangle.


And you know, what, what drives fraud? You know, so the pressure, there can be pressure on people. That's generally what happens when people come under financial pressure. And then because the controls are not in place, there's an opportunity that carries out the opportunity, and people will rationalize it. It's hard but you know, that person is a great person, they’d never engage in fraud… but under certain conditions, people will rationalize and justify their reason for carrying out fraud.


So there's a reason for that and you know, this whole Sarbanes Oxley view, if you read through this, you'll see that they really thought about putting in place internal controls and all the rest but it still brings us back to if I can bring this back to what we had. It still brings us back to the state where when it comes to audit, the old issue still persists, which is the audit is not it's not auditing, every data point, it's selective and things can slip by so hence why there's the opportunity. And the price is a 3402 audit.






Baseline Protocol


Andrew:

Now I will get to the baseline protocol. I might actually jump out now and show you what baseline protocol is.




The value of business controls is part of this is a 3402 audit, which is more it's not so much auditing that financial data. It's more about auditing the control procedures that are in place within the organization. That's typically how these audits are carried out.


They don't have to look at every data point. But certainly, I guess the Auditchain project is pretty much focused primarily on the audit of the financial information and we'll see that when we get to the Pacioli engine. But um, I guess this is just touching on some of these extra things that can be considered like for instance, the baseline protocol.


What is the baseline protocol?


Baseline works with the Ethereum blockchain and as a way to secure verification and validation over a data point. So this is a prototyping environment where we're testing out some of these capabilities. And one of those capabilities we're testing is fetching contract data has failed. That's not good because that's going to mean that I can't show you this. This baseline, I know it is dry, I guess so there it is now, so here's a contract. And what you'd have with a contract, is you have information about what the contract is, maybe something about the delivery and maybe something about the payment right? But when all of that information is put into something, and shared as in, I've verified I signed my contracts and my supplier so here you've got the supplier signs, the contract, the customer supplies the contract.


The contract contains metadata, which is all of this information about what the contract is about. And it's possible to baseline that contract so that it's linked to the blockchain in such a way that the metadata is metadata, right you can see that something a machine can read. And then what the machine can do is it can read this data and check the signatures and then verify whether the made it whether that metadata has been tampered with, since the signatures were placed and you can see customer signature on the blockchain supplier signature on the blockchain.


It's not actually directly on the blockchain, but it uses the blockchain to derive the hashes that provide the proof against the document. So it's like a digital signature methodology that allows you to get verification and validation across any set of metadata. And that you know, that baseline protocol is actually a free open source protocol. And essentially what you're getting is the equivalent of a digital signature that you can take into a court of law and you could run this verification across the metadata and derive a proof as to whether that metadata had been tampered with since the signatures were placed on the document.


So the new way of getting a digital signature essentially, when it comes to your NFTs. A non fungible token is a way of getting a hash on some metadata in a way that you could then search for and find that find that metadata, and it would be and you'd, you'd be able to at any given time, discover whether the metadata had been tampered with or changed.


So non fungible tokens can be used for a lot of different things and probably you've seen and heard about non fungible tokens being used in the world of art. That's where I think that most common but certainly there are more ways to use NFTs in business. I'll show you an example of what I'm talking about with an NFT and business where this is a business search engine.


So let me do a search across the top of this. We do a search - I'll search for my business using Accziom here:




This is searching and it's actually got something called an axiom database, which is storing information on logic. You can see here there's information stored on logic, and then that same information is possibly harvested from some of these prior, I guess, business, databases, Australian Business register ACM.


There are also ways to pull in information on a business here and you can read about what logic does. This is discovered from the Bing robot that will then tell you what that business is probably involved in, given the name, never going to be particularly accurate. A map, but it gets the end of the day. This kind of technology can provide a snapshot of a business, but the long term goal for this kind of technology is to give each business its own NFT and then say here's a way of using blockchain to pay for a service.


So you need a mnemonic - it's like a phrase that is almost like a password. It's only now that like, oh, okay, so you've talked about those? Yeah. So I've thrown my mnemonic and then I've got access to the to spend these MERC total tokens. And what I want to do now is spend my MERC tokens to find further information that's deeper in the database that's not free. So if we search for BHP limited… let's see what we get here.







Electra:

“The data is needed to pay”

We're all familiar with paying a fee to do searches. Yes. So bring everything out into a sort of aggregated open source environment.


Andrew:

The idea here is that the data is owned by the business owner, and it's not by ASIC. It's in the business owner’s best interest.


So you can see some of the data is behind a paywall. So how do you gain access to that you've got to you've got to spend money, or you've got to withdraw so you've got to once you know you can see here, I've got enough tokens in here. Now I'm paying and then when I pay with my token, it'll take a fraction of a token out of my wallet, and then I've got access to the data that's behind the payment.


The difference is, in the case of ASIC, they believe they own the data. But in this case, the database is built, built around the principle that the business owner should own the data. And then if people want to search for the data, of course, they'll discover the public information for free, but there'll be certain information about your business that you will keep behind the paywall. Maybe your phone number, maybe people's details, you know, maybe email addresses, and that or maybe even some of your financial information, and that information will only be available when someone pays.


So technologies are enabling us to have ownership over our data and enabling that ownership to be monetised for ourselves.



Electra:

And that is how we have ownership of our data that we can then monetize for ourselves. With NFT’s that is in the context of JPEGs and art and getting it but now we're talking about our business information being monetised for ourselves.


Andrew:

Yes. So in this in this case, the monetization is in the revenue is split between three parties, the party that runs the mining, the mining node that that holds this, this set up MERC tokens in place this special so this is a quite an advanced search engine technology here, because you'll see it through things like discovered address of other other entities that share this location. It's also the address of these other entities that share that location.


But ultimately, the revenues go back to the database provider, provides a special technology for the search to the business owner and to the mining folks who run the node operation for making sure that the NFT's are secure and that the MERC tokens are split evenly between whomever is entitled to a split which would be the which would be the data owner and as I said the search engine as well.


So that's just a little look, that's just a little look at how, in this case, ultimately an NFT would be associated with any business could come along, grab themselves an NFT, associate that data and then ultimately they will be entitled to these tokens.


You're entering into the token economy where you're engaging with tokens that ultimately you swap out for another type of token. Or you could ultimately swap back out for cash. Yeah. So t that's sort of a real life example of the baseline protocol and the NFTs. So let's just keep going with this presentation. Okay, so control artifacts.


Control Artefacts






Electra:

Can we just understand what control artefacts mean?


Unknown Speaker 31:16

Yeah, so artefacts are those things, the technologies and the things that we use in our lives to gain control. And one of the things that we use to gain control of our businesses is x. So we use axioms, which are like rules of thumb and the primary rules of thumb that we have in the accounting world are all of those rules of thumb that we use to make accounting work - debits and credits, assets minus liabilities equals equals equity, at least in Australia, in the US level, and they like to do it the other way around. They'll say liabilities and equity equals assets, but it's the same, same equation.


So those are the sorts of rules of thumb that we would use and you can imagine that once once you expand out on your rules of thumb, you can actually derive financial reports and those financial reports that we can put together in PDF or Word or whatever, are generated out of software like Xero.


Ultimately, in the world that we're going into, you can have a digital doppelganger, which is, you have these ways of, you can have these ways of putting together financial information, which gives you like a mirror image of the world which is using things like taxonomies, which is an excellent XBRL concept, and ontologies so you use technology to derive a digital representation that then becomes machine readable.


And the importance of machine readability in the digital age, is that you could share your financial statements around and it's going to be not so much about an accountant or a bank manager reading it. But more so about another machine being able to take that set of financial statement information and read it and make sense of it. And that's where we're gonna get to some of these things that the Auditchain guys are bringing out.


Electra:

Are we talking about AI here?


Andrew:

Well, you know, AI is sort of a rubbery kind of term. I wouldn't worry too much about the AI concept. I'd be thinking about this more from the perspective of what's logical and reasonable.


Electra:

That is what I wanted to mention because we're hearing a lot about AI in our profession at the moment …but really here we're talking about logic processes. We're following logic when dealing with things like accounting and tax law. It's a logical series of statements and understanding the information. And I see what we're dealing with here with nothing as fancy sounding as AI. It's logic.


Andrew:

Believe it or not, the logic that's used with the Auditchain Pacioli engine is actually a logic engine. That was the original AI, how it was built. It was built around something called declarative programming, declarative programming, where you declare your statements, which is like your axioms and then you can test your statements. So you can very easily test assets minus liabilities equals equity by having values in the similar sections, and then you could run a declarative statement across the top of that, and then see if your derivation matches your prediction according to your axioms.


So, other control artefacts that we would use would be things like our trade contracts, and how finance contracts. And if you look at everything that happens through your accounting system, it's all about those things, right? Everything sort of derives from how you initially set up your trade contract or you have a trade contract for what it is for whatever goods or services that you're selling. And then when it comes to facilitating things like any financial activity, you know, settling HP, for instance, it's all money for money, and finance contracts and all of those things can be well handled by these, you know, by these logical processes.


And certainly, if you thought about your controls, that you you always will get your controls into place straight away as quickly as you can, making sure that you know if you've got a contract that's running into a financial system try not to have steps where it comes out of the software and goes into something like a PDF or a Word document and then manually keyed back in, if it's kept all the way through. That's where you've got the sort of digital straight through flow of the, you know, offset of that control artifact.


So we know also without agencies, like for instance, or, or our standard sports, those are really cohorts, right? So you've got to have agents who agree to adopt certain standards before the standards become useful. There's no point just having a single agent who goes oh, this is a great control. You've got to have others in the community who will accept your control methodology, and then those controls become useful and certainly with the types of controls that we're going to be adopting.


You're going to see that there's going to be cohorts of agents that sign off on those controls. And we're going to get to how controls can be attached to NFTs as action-based identities and curating business information. Just take yourself back to what I just demonstrated, where you've got these new kinds of search engines, and someone's maintained or someone will take responsibility for maintaining the business information in the database. And who is that going to be that's going to be the business that's going to be the owner of the business where whichever agent has control of that business, it will be in their best interest to curate and maintain their own business information. So it's accurate and up to date.


And certainly for all of us, we know we know that as we're sort of working in the world now. You're building up profiles on LinkedIn, people get to know who you are, and that becomes part of your action-based identity. And later on, that's going to be important for how you engage with these cohorts. And you know, which cohorts will want you to join their cohort to sign off on it on a certain set of controls. And we'll get to some of those controls that will be attached to NF T's in a moment. So this brings us to back to 1494 and Luca Pacioli.


Electra:

Let’s pause a moment just to see if anyone has any questions about those control artefacts. Feel free to jump in and ask us to interpret what we're discussing. I'm not a technologist. I've just been very keenly working on the bleeding and cutting edges of technology for the last 20 years. I'm fascinated by all this, like many of you are, but I don't speak the language very well yet. I am attempting to pause where I think we might need to clarify something into a context familiar with compliance accountants. If anyone has a question, please comment and we'll pause and discuss it.



Pacioli Logic and Rules Engine





Andrew:

Okay. Okay, I'll keep rolling. So back to 1494. And we had Luca Pacioli, who came up with the double entry bookkeeping system. I've just shown you a triple ledger system, which was a way to get a blockchain hash onto a contract. The triple ledger is the hash of the proof that would allow both sides of that contract the the buyer and the seller who both have a copy of that contract, to at any time, go back and demonstrate to someone that that contract is a legitimate contract.


Why is it a legitimate contract? Because it's baselined and tied to a blockchain. And it's provable because there's a hash on the document or a hash in the metadata.


Electra

I recently did some e-invoicing and noticed the hash associated with the invoice transaction. That was the third entry that made that triple entry accounting.


Andrew:

Yeah, quite possibly. If it was Luca+ you're right. Those guys actually have their own blockchain that they use to derive that hash, which is exactly the same as what I just showed you with the baseline protocol method. The baseline protocol method is just another. I guess it's more of a sort of open source open standard methodology that any software developers in the world could adopt and use it to derive and hash into their contractual documentation.


Electra

We could be doing triple entry accounting and with a software user interface and not even know!


Andrew

You wouldn't even know it, but it would be useful later if you had to go to a court of law. And they say, Well, you know, where's the contract? And how do we know that's an original contract? Or, you know, where's the where's the where's the offering, except where's the order? You know, where's the invoice right? So let's have a look at that invoice. How do we know it's an original invoice that you're, you know, that your counterparty says it's not not original? Well, then you'd be able to say, Well, look, here's this set of metadata that's associated with the contract or the invoice. And embedded in that metadata is a hash which can be proven that the information in that document hasn't been tampered with, since the hash was introduced into the dataset.


Electra:

That would save a lot of time on collecting other evidence.


Andrew:

It's a way it's a way of proving originality, but I guess the real value of that comes from the ability to ultimately feed those documents because that'd be an electronic format into a machine and that's where this patchy only or patchy logic engine comes into its own, because it's ultimately a robot that's derived that's I guess, built to handle and ingest business information and then derive a solution.


There's this Boston Dynamics stuff and you can certainly see that … When it comes to robotic technology, these robots now almost have an ability to act on their own, almost like a sentient being. And certainly if I'm going to show you a, you know, a Petrelli logic engine or a machine that can be reasonable like a human accountant I can't show you something that's so intriguing as a Boston Dynamics robot if it just doesn't look exciting, right?


And that's the unfortunate reality when you're an accountant. Never going to be that thrilling and that exciting. So what is this Pacioli logic and rules engine? It’s probably the original AI, which has the capability if it's given XBRL schema that it can look at, essentially it would be like this it would be like me giving you a set of financial statements. I can position the financial statements, however, I like using whatever funds but the line items in some kind of hierarchy but if you're a good accountant, you'll be able to look at pretty much any balance sheet and make sense of that balance sheet. You'll understand to check your balance sheet to make sure it balances. You might look inside your inside the equity section to make sure that the equities or the retained earnings reflects what's brought up from the profit and loss, the net profit, you'd be able to look to make sure that there's a roll the roll forwards are correct.


You'd be able to look to do things like foot and carry so you can see across if for instance you had some blocks within the financial statements which were reflecting, say you were looking at revenue from the point of view of divisions, so maybe you've got divisions by state or location and then you've got another way of looking at that block, pivot table type of block and you're looking at it from the perspective of maybe colors, red, blue, green, whatever. You'd want to know that those pivoted blocks always tie back to the revenue. Those are the sorts of things that you as accountants would do. You would know you know to expect maybe there's a cash flow statement in their statement of financial position.


Electra:

So they can go and see Pacioli running live. Follow that link. And you can see what we're looking at here these companies that are analyzed through the Pacioli logic:






Andrew:

Logic engine can currently look at any financial statements that are presented to it using this open source SBR format, and they can come up with a derivation as to whether there's any errors in the in the dataset,


So the information in this case is that these are all publicly listed companies like Microsoft, for instance. They they file those financial statement reports instead of filing them like we, you know, our public companies would file to ASIC and now public companies would file in PDF so whereas in the US and Europe and Japan and a lot of other countries, they moving to filing in this machine readable format, which is XBRL extensive reporting.

The Australian Tax Office the ATO actually tried XBRL 10 plus years ago, and gave it away. Because what they realize is their information is very it's forms based right? Every form is exactly the same as every other form. And XBRL was overkill for them. But you know, when it comes to financial statements, not every financial statement is exactly the same as every other one. I'll give you an example. If you're a financial institution like a bank, you don't you don't lay out your balance sheet as in current, current assets, non current assets, you lay out your balance sheet where it's all done on a on a liquidity basis, you have your most liquid assets first and then you run down on a liquidity basis to your least liquid assets, whatever those are some kind of, you know, some kind of fancy bond or whatever.


But certainly, you know, those financial statements, which are for publicly listed companies, they could, you know, they could have extra extra information in there, that you just don't have other financial statements. So it's certainly not like a full financial statement would be slightly different. Every financial statement will have different kinds of pivot tables covering different kinds of granular information.


And that's where you need one of these logic engines to be able to read that financial statement, which is in a machine readable format, just want to be human so that actually only logic and logic engine comes along, reads the financial statements. And obviously, that's a very important starting point because you can see here where the statements that are being submitted currently have certain failures. The roll ups…






Electra:

Is that matching data to another report? Is that looking for other reports?


Andrew:

Or what it's doing is it's using rules. It’s a rules engine. I'll give you an idea where the roll ups are failing. So a roll up would be something you'd be familiar with this way, I guess. So you've got cash and cash equivalents. And then you go to the notes section for cash and cash equivalents. And then maybe you've got a list of all the types of cash and cash equivalents you've got. And then that would summarize to a total, which hopefully, is equal to the cash and cash equivalents carried on the balance sheet. It's actually pretty simple, right? So don't, don't look at it and say it's way too complex. I can't get my head around it. It's really a robot that's doing some pretty basic stuff. It's checking for consistencies in their financial statement information,


Electra:

Is it also catching rounding errors with a continuous audit process? So maybe like picking up errors all the time that might be immaterial?


Andrew:

So certainly what I'm talking about now, it's very far away from streaming real time. Financial Statement verification, right? This is very much about an engine or robot that does nothing more than look at and inspect. Static financial reports will be nothing more than what we're all used to: balance, statement of financial position, cash flow statement, maybe something about the equity, that sort of stuff. That's all this engine currently does. So the idea of streaming financial data real time to derive a conclusion as to whether there's inconsistencies that's still a long way off. Sorry, if I've let you down.


Electra:

We want to understand where things are at and where things are headed.


I'm imagining a machine that is scanning reports back to see what I've got in the ledger, to see whether it's actually calculated and reporting correctly, but maybe I'm wishful thinking.


Andrew:

You've imagined something that's not yet there. Yes. Okay. But certainly I think that is their intention, but this is their first step, which is to bring out a robot and obviously is not as impressive as the Boston Dynamics robot that can fight guys with guns and all the rest.


But anyway, that you know, that is what they've got now. And certainly, it's still useful because we are moving into an age where financial reports will be delivered in a machine readable format. It's just impractical to derive and work with PDF financial statements forever in a day. So we are sort of moving into this world where financial reports will be delivered, especially to regulators in a machine readable format.


And definitely later that same approach, I guess, will be used by the marketplace to verify and validate financial reports. For instance, if you're going for finance, there will come a day when the bank will say well give me your open source, financial statements in this machine readable format. And we will have our engines which will be something like Apache only rules engine that could be a robot that will roam across the top of the data set and verify and validate.


Electra:

We're becoming familiar with concepts that our younger staff will grow into and definitely we need to be kind of familiar with it. This could be in 10 years where we have a completely digitized practice.


Andrew:

Yeah, and you can imagine where this goes from here. From here goes to a case of a now you've got your block which shows your cash and cash equivalents. And the robot then can then look at a particular line item CBA and then it can trace back. And this works particularly well if the transactions are based on blockchain, because then instead of tracing back to your bank's front door knocking and saying, Hey, is that the correct balance on their balance sheet? It simply calls back to the blockchain and checks that wallet address and goes Yep, okay, that had that date on the blockchain. It can't be changed for the market and see verified validated by various


Some blockchains are more or less risky than others. Some are more stable and have been there longer and more trusted. But certainly that's the sort of idea right? So you'd have a machine you'd have a machine actually logic engine that not only combs through the financial statements that you give it, but it also does calls back to sources to collect verification for the for the values that are carried on, on the on the actual statement, and perhaps even calls back as far as requesting the general ledger detail, and then combing through that and use certain rules to look for exceptions, right.


So anyway, this sort of brings us to the Auditchain approach to deploying that logic engine or that Pacioli robot. And this is the world that we're moving into currently, you would expect that you know, you've got a big public company that deploys an engine for instance. But in this case, we'll be moving into where the marketplace and the participants in the marketplace would be participants in running those logic engines.



Pacioli Nodes and Operators






So who are those participants going to be, all of us accountants will have the opportunity to run these Pacioli logic engines or robots? And where would you run them? You'll run them wherever you can buy some computer resources, which might be in a data center. You might have an office with a fast fiber link, and you'll run an engine there.


So you'll have all of these logic engines that are positioned all across the world. And then what will happen is when when there's a requirement for a verification or validation across the top of a set of financial statements, it will be that that set of financial statements and any of its links back to source will be consumed into one of these robots somewhere on a node which will be run by so a node would be a node is that concept of one of these Pacioli logic engines running under the control of and deployed by an accountant.


Electra: Could it be run using software on my computer?


Andrew:

It’s probably not going to be on your computer in the office, but more likely to be it's more likely to be running in a data center. Or will be likely that if you do have an office that's got a very fast connection in and out. You could probably run it locally in your office. Yes. So you know, currently, it's still pretty primitive in the way that you run up a note and I know, electrodes waiting to run up a node herself, which she'll actually have one of these patchy logic engines running under her control. And to run one of these logic engines you have to stake so there's a concept of staking some AUDT token so this comes back to the AUDT token economy. Auditchain token.



AUDT Token Economy





Electra:

Yes, we have some AUDT tokens for staking. Is Auditchain like a layer 2 blockchain?


Unknown Speaker 55:42

It's a layer two protocol blockchain, which the primary use case for this blockchain and its tokens is to execute and run the AUDT token economy.


So it incentivizes people like me and you to run up a node to deploy a Pacioli logic engine for the service of whoever wants to use these logic engines. So instead of one logic engine, you could have a million of these logic engines all over the planet. And then anytime anyone wants to verify a set of machine readable financial statements, and their entitlements, whether that's a general ledger detail, carrying back to a blockchain, somewhere where there's very value carry, you would get one of these, you would get one of these Pacioli logic engines to query the data set. And then it'll give you a report as to whether that's valid and free of error, essentially, and then later on obviously, also carry out the back checks to see that right.


If there is say for instance, on that balance sheet there's a statement that there's X value of whatever it can then carry out a check back to some data source, right? Maybe that's another blockchain. That's obviously the value that comes with Blockchain technology. But certainly the AUDT token economy is built around that AUDT token that permits the staking because you can't just run up a node you actually have to stake almost like if you go and rent a building. The landlord will ask you for a downpayment.


So essentially, this is the same thing you put down a 5000 AUDT down payment, and then you can and then you can operate a node. Now you might go, Well, what happens if my node doesn't get caught and doesn't get query off enough to make income? Well, there's value in making sure there's enough of these robots running on the network. And therefore, you will still be rewarded even if your engine doesn't get called every day. But certainly that I guess the goal is that the economy for the service will grow and then your node will be called and utilized when others are requesting verification validation across the top.


Electra:

What is the consensus mechanism?


Andrew:

Well, the actual verification and validation is based on the rules and the logic that exists in the robot. That token runs on Polygon, which is a layer two network, which is associated with the Ethereum blockchain. And you'll know that if you want to buy a AUDT you've got it. You've got a bridge into Matic into the Polygon network. Yes, so the validation is carried out by an AUDT engine but it will ultimately write it into Matic as well. I believe I'm not 100% sure on that, but you will get verification coming through. Probably on that. On that layer two, network. That's something I'm not 100% sure on, but certainly, I think that's possible.



Right. But in terms of that ADT token economy, it's about right. So if you want to play the game, you've got a stake, which is, as I said, much like putting down a deposit to get into a building. And then you'll also use AUDT tokens to request a service. So I've got a set of financial statements, verification and validation. Then I have to use AUDT to pay the network, and then the network will route the tokens to the node operator that carries out the function of the verification which is the audit verification right?


So some, some node operators somewhere will earn AUDT tokens. And then finally, we come to NFTS for process controls. So what is a process? In this environment with open source technology, which is the XBRL standard, anyone can create controls, which would help the logic engine reach a conclusion. So one, a very simple control example would be something like for instance, assets minus liabilities equals equity right now, all the controls have to be built by someone who has a very simple control. There could be other controls that would be put in place to verify and validate other information in a financial statement.


Someone somewhere has to make the control. So that's like a programming kind of task. But there are tools that are coming into place that allow accountants to actually make those controls directly themselves. And then a controller is no good on its own. You actually have to find a community who will agree that your controller works as you say it does, right? Because there's no point building a controller that you say checks that assets minus liabilities equals equity, but somehow you built the control wrong and it doesn't check anything, you know, so someone has to check your control.


Now those controls go much further than just simple arithmetic. Let's get right into language. And there is something called Logical English. I'm not gonna go into great detail now, but that can certainly carry out complex tax legislation. So someone who wants verification around something like small business CGT concessions, and then those controls can be tested and carried out across the top of your data set. So for instance, you might go, could this company be entitled to this small business CGT concession that they have claimed and taken advantage of, to receive some, some discounts? And then you could use these controls and the and the logic engine to verify given the information that's available to say, hey, no, you know, this company has taken advantage of CGT concessions that it wasn't entitled to and therefore you should be to be careful of relying on the business because, you know, the data set might be right but never have used that that Tax Concession. Therefore there's a risk associated with this company.


So the controls can go right into natural language as well as simple arithmetic types of checks. Yeah, yeah. And that's what's going to be the real power of the Pacioli logic engine or what I like to call a robot. Obviously, obviously, not as exciting as the Boston Dynamics kind of robots that I had a little video for. But anyway, you know, token economies are all about community participation, and community reward because everyone in the community can.


You obviously need the tokens to gain access to the network to verify financial information. But at the same time, you can actually engage as a participant by running a node or providing services. For instance, building these controls and then these controls can be attached to any non fungible token. So very different to attaching a GIF, or image, you could actually attach your controls, and then you can have your community of participants agree that that control is valuable. And then you can break out the reward so you might go: “Okay, guys, let's put together some controls for small business CGT concessions. I need 10 of you who will check the controls and verify and validate that they work as I say they do because I made the controls I made the logic”


And then we can break out the reward so that there's an owner of the controls and maybe the owner of the control is the community or can be one person who then just pays off the other community members to verify and test that the controls work as promised. So certainly there's an opportunity to to build these controls and put them into the into the into the domain where others can use the controls at any given time and then every time those controls are used you as the NFT owner, which represents the controls, gains the reward, so you may gain some AUDT tokens staked.. So you can see it's an economy where you can engage from multiple perspectives, and you can gain the reward from the AUDT tokens. And of course, these are work tokens. So these are networks of decision community specific work tokens each and the value. Really, really close on the value of the token will get more and more valuable.


Participants support the AUDT token economy. So that's sort of a summary for what we just covered.


Electra:

That was the most amazing description of an accountants’ DAO.



Andrew:

Yes. So the DAO comes back to this governance piece. Actually, I didn't I didn't touch on that. Because so who's going to be running the AUDT community


So the accountants who participate in the economy will also use their AUDT tokens to vote on anything. That's going to be a change in the way that economy works. As I set them, one of the primary voting things will be around accepting new controls. And obviously, there's, you know, there's doubt there's decentralized autonomous organization methods for getting, you know, getting different cohorts of the community to agree to doing something or not doing something and moving the whole economy forward. But it's, it's a different kind of, it's a different kind of world to the world where you've got, you know, a traditional company that earns revenue, and you know, and has equity. It's quite different.


Electra:

The new shareholders are token holders. We don't have shareholders in this kind of company.


Andrew:

You don't have shareholders, you have token holders, and the tokens are multifunctional. So with shares, shares, typically you don't use the shares. It would be a little bit like Xero having Xero tokens, which you could own which gives you a piece of essentially owning Xero. And the same time you use the Xero token to gain access to Xero.


It’s far more powerful, even though I really would have liked to do so, so you can only add tokens and then you can use them as well for access to functionality that the network provides. And you can also vote on certain activities that the network that the economy will, will do or change almost like a government that's the governance, right.


Summary of process-control NFTs




So that's, so that's us covering off on the NFTS. So I've shown two use cases for NFTS. One is, one is controls, you associate your controls with an NFT allows you if you say you went to a lot of trouble building and if a building controls you concessions, which was reused over and over by everyone in the network, you own the NFT that gives you ownership of the of that set of controls all of the reward comes to you as the NFT owner, but then at some stage goes on to sell those controls.


Someone else can own them and get the rewards in the future. So that's another part of the economy. The other example I gave for an NFT was as a business owner owning all about your own business and providing access to your information. Above and beyond what might be just a sight of public information. You got certain information below the waterline which you privately provide. You're prepared to share it. You're prepared to share it under certain conditions, ie you get paid for it.


In that case, you're associating that with an NFT as well, because it's possible that you sell your business and then what do you do if someone else doesn't want to go to the trouble of curating and preparing all that information again. They just simply take it over the internet - you sold an NFT when you sold it with the business information


Whatever the business information is that might end up in one of those databases. So that sort of gives you an idea. Hopefully that gives you an idea of what we're talking about in terms of how that economy works.


Providing full automation in future?







If we use Auditchain and tokens it’s a completely new perspective and very different aspects of the utility of this for our application. How does it all pull together? So that Auditchain does this? How does this ultimately pull together?


We'll take a snapshot of how our business might operate. In the near future. I wouldn't say this is that far off. Let's say it's a blockchain economy. Essentially what's happening is you have your private keys to all of the NFTS for controls. Same time you've got the private keys to all of your wallets that you use to gain access to sending and dispersing tokens for certain functions, activity functions, or just to pay people for services. Or goods.


And then ultimately, what you would do is you would simply point your robot at your blockchain and then the blockchain for all of your contracts which are baseline, because obviously those contracts don't sit on they don't sit directly on blockchains. But they've got hashes on them that provide the utility for the proof that they were original, you provided. You provide your patch to the lead logic engine, the robot accesses all of that information, and then it spits out, spits out a report from a set of reports, or it tells you if there's anything amiss in the data set.


So that would be the endpoint goal, where ultimately, ultimately the concept of having to extract data from all of your blockchains and all of your contracts and put it into another accounting system becomes redundant because you've just got with you information, with everything. In terms of metadata stored, either on blockchains or baseline.


Electra:

Do we have any questions? It’s OK if you don't yet. This is an overview. You know, we listen to these webinars to familiarize ourselves with new things we want to understand, a new language, you've been reading it and now you're hearing it and your mind is putting it all together into context. Don't feel like you have to understand it all. We continue and then we talk about it.


Auditchain launching next week, so this isn't something on the shelf that we go plug into from Xero marketplace. This is something much bigger than that. It's been in development for quite a number of years, since 2016 I think.


The launch at UK Digital Accountancy Show was streamed and is a moment in world history!



Watch Jason Meyers the CEO in action below, ready to disrupt the accounting world, very entertaining!
"Hey Johnny, you haven't asked for a raise in ages...oh that's ok, I am making 300,000 quid a year writing controls for Auditchain and I get the ideas from your lousy accounting department..."


Now where to from here...


Andrew:

They've been doing research over a number of years and they'll be launching their first robot on the statements on 8 June. Definitely this stuff is all quite new. And there's definitely a learning journey to sort of get your head around how this stuff is going to impact. You know, as an accountant in the future. It's probably not something that you completely get your head around in five minutes, it takes a lot of reading. A lot of you know a lot of digging into the technologies and also playing with the technology is important.


Electra:

We can collaborate with the developers to make this happen. Yeah, so like, I wouldn't know how to turn one of my business processes into an NFT but we can learn and I can't wait to. It's just like learning something complex in Excel.


Andrew:

I think it'll be one of those kinds of processes that that complexity gets abstracted away and eventually it will be you know what you want to run a node. You want to run a node and be rewarded by the tokens staked and your stake opens and then you press a button and there'll be hosting providers all over the place that will have access server capacity.


And you run up a node with a press of a button and a couple of tokens. You know, a lot of the complexity will be abstracted away and you won't actually have to deal with too much complexity. But at the end of the day, that is you know, there is a certain amount of information that you need to think about and and you know, try to get your head around and that will probably take some time.


Electra:

A lot of our time is spent learning the foundational concepts of blockchain. We just have to get familiar with them for a long time.


Come back to what Luca Pacioli would have thought about this. I think he’d be pretty proud of us being here right now.


50 years ago using your computer was very manual and now it's so easy. Now anyone could do it. This is going to become part of our lives in the next five years. We’re motivated to have a go at using it early.


Andrew:

The end point is if you do start your business processes with trade contracts and finance contracts, digital trade contracts and finance contracts, which you either baseline or run on a blockchain then ultimately there will be no concept of journals and manual adjustments. And everything will simply be a machine reading your financial activity. It's as simple as that.


Electra:

Do you have to buy AUDT and run a node to earn AUDT with journals like that, or can you delegate or are you best to run a node?


Andrew:

So currently you have to buy your tokens to stake and get running. I bought a lot of AUDT tokens. And there is a concept that I will be able to essentially lease my tokens out to those accountants who just don't want to buy AUDT. They want to engage in the token economy, but they don't want any risk associated with buying anything and of course, it'll be for me to lease my tokens to those who want to run a node but don't want to pay a cent upfront.


Electra:

And part of the learning experience,


Andrew:

Well, you might want to, as you'll be earning as well. But instead of getting all of the reward you'll be sharing the reward with the person who provided the tokens for you to stake. If that makes sense, essentially you will participate with no risk.



Auditchain Australia - How to get involved






Electra

What we’re doing here is the beginning of an Australian Auditchain meetup where we'll continue talking about these ideas that we're interested in. To find ways to participate, and learn more about what we can do with NFTs to earn a professional income in future.


Auditchain Discord: https://discord.gg/GkCEgvEn Accountants On-Chain Discord: https://discord.gg/vP87htgf Subscribe to updates: https://www.digitalplayhouse.com.au/accountants


Andrew:

Electra, I wanted to say is you are obviously going to run up a node and you and you've got someone that will help you with that, your IT Manager. And he may very well be interested in monetizing his service for running a node. And you know, that's something that you'll be able to share with others who don't want any technical pain.


If you want to run up a node, earn some reward, and that's a way to do it. So it's like any economy. It's all about participating and finding ways to collaborate and get others to help you and share the reward. These kinds of token projects don't count for anything unless there's velocity in the token economy. Those tokens are no good just sitting around; they actually have to be used.


Electra:

Thank you. Well, Andrew, this has been absolutely fantastic. Thank you so much for sharing all that and it’s been great to learn from you. And thank you everyone for being here this evening. I look forward to speaking with you more and if you connect with me on LinkedIn (with a personalised message), I'll share a lot you might find interesting too.

Thanks, everyone. Bye







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