Skip to main content

FAQs

FAQs illustration

Get answers to your frequently asked questions

Products and solutions

Bringing together data from multiple systems and applications is an expensive and time-consuming task. Without being able to share and understand the same data easily, each application or data integration project requires a custom implementation.

A Common Data Model (CDM) simplifies this process by providing a shared data language for business and analytical applications to use.  A CDM is a metadata system, which makes it possible for data and its meaning to be shared across applications and business processes. A CDM allows standardisation and metadata management and lineage that:

  • Enhances search and analysis capabilities for metadata collection and management
  • Discovers, harvests, aggregates and provides access to knowledge
  • Accommodates different types of search queries and accommodates large and complex data links and relationships.

For the past decade, Knowledge Graphs have been part of our daily lives. For example, Alexa, Siri or Google Assistant are all types of Knowledge Graphs.

For enterprise use, Knowledge Graphs use AI and graph technologies to compile structured and unstructured data, which is then served up visually, providing context and highlighting complex relationships between data entities.

Corporate data grows enormously each year, making it a challenging task for organisations to keep track of and collect every data point available. Manual efforts of extracting and mapping data take up vast amounts of time, resources and effort in getting the data needed for further analysis or processing.

Our EB Integration Engine is a data extraction and mapping product that solves these challenges by automating the extraction and mapping process, giving organisations more control and consistency over their data extraction tools.

Differentiation

Engine B is the only provider on the market extracting all of the data in your client’s ERP plus unstructured data like invoices or contracts and conforming it into a Common Data Model which you can use with any analytics tools you choose. Once the data is out, you have complete control and you’re not tied to a specific company’s tools or environment. Because the data is conformed to a common model, it’s really easy for you to pick up new audits once a client is on Engine B, because their data is already prepped and ready for you. All the data stays with you or at the client, so you don’t have to worry about data stored in someone else’s cloud. And we’re the only tool that layers a knowledge graph on top of a data model, allowing you to analyse the relationships between data points and provide next-generation assurance.

Remote access

Engine B works in your organisation’s IT environments, which means that wherever you can access your work, you can access your data. It will be up to your organisation how you want to manage access, but Engine B supports all team members having access to what they need at the same time. No one can change the source data and records of access and use are kept and available at all times, so you have a complete chain of evidence.

Our technology is accessible from anywhere your auditors have a secure internet connection, from home, from a client site, or your offices. There are some things, like making face-to-face enquiries of management, that you may still want to do in person, which can be done remotely now too. But if you move onto Engine B’s solutions to ingest the full range of data, you would not need people on-site to check documents like invoices, fixed asset registers, or other records.

Longer-term, we’re looking at options for remote auditing things like inventory and even fixed assets, depending on the information your client keeps on these and their controls. This could reduce the amount of staff travel and remote time significantly, or let you focus your site visits only on where there is material risk.

Value and ease of use

Currently, audit teams are spending significant amounts of time preparing data for audit and then matching up evidence, either reconciling datasets like the Trial Balance and General Ledger or by checking invoices or other documents to basic records. This is work that is much faster and more accurate when done by a computer, and Engine B gets all of the evidence ready so that reconciliations are done automatically and you can easily apply tools that perform confirmation to underlying evidence. This frees up staff time for judgmental areas, really focussing in on risks and helping your client manage their business better.

But even beyond these efficiencies, having a broad range of data ready-to-go makes it possible for you to get insight into your client’s business that’s just not possible in a traditional audit. By utilising Engine B’s Knowledge Graphs and connecting up to Open Banking, you could gain insight into your client’s cash management and treasury function which could save them management time and effort and improve their controls. By applying machine learning or process mining, or graph algorithms on the data prepared by Engine B you could find inefficiencies, pain points and control weaknesses that make your client’s business inefficient and risky. This enables you to make more tailored recommendations to audit committees that will help your client’s governance processes and make everyone’s experience of audit easier.

Currently, audit teams are spending significant amounts of time preparing data for audit and then matching up evidence, either reconciling datasets like the Trial Balance and General Ledger or by checking invoices or other documents to basic records. This is work that is much faster and more accurate when done by a computer, and Engine B gets all of the evidence ready so that reconciliations are done automatically and you can easily apply tools that perform confirmation to underlying evidence.

Secondly, because of the huge amounts of data audits now have to contend with, it’s very hard for auditors to identify and focus on the risks in a client’s business, meaning a lot of effort is spent auditing areas that are big but don’t pose a risk. With properly conformed data and the power of our Knowledge Graph, you can use state-of-the-art risk assessment tools which let you identify, focus on and document real risks much more easily, reducing time spent over auditing.

Data security

We’ve built in a complete chain of evidence, including summary information at every stage. You’ll be able to see every step from the client’s system into your tools. With that, you can be confident about completeness.

If you choose to deploy Engine B within your own environments, then we don’t hold any of your data, so everything is covered by your own security. We do not hold client data or share data outside of your tenant. Alternatively, we offer a Software as a Service (SaaS) model where we hold your data in a specifically designed data lake, which is different for every audit and audit firm. That way you know there’s no risk of data being shared between engagements. We keep all of your data in a data centre local to you, using the same data protection regulations of your jurisdiction. We implement the highest levels of data security at every stage. Contact us if you’d like to know more about our security set-up.

If an engagement requires BPSS, SC, or DV level clearance, you can speak to us and we’ll make sure that any staff working on the engagement for you have the appropriate clearance.

Our Audit CDM is simply a set of data models that are available to all auditors. The data itself isn’t open source and remains secure. Using our Audit CDM means all auditors can work from and understand the structure of the data, giving a shared understanding of the securely held data. Regulatory bodies are pushing for joint audits (which happens in France) and increased competition, which the shared CDM supports easily.

Engine B is opening up the market to allow greater use of standard tools and also to make it easier for firms to develop their own. If you don’t have in-house capability then you can leverage tools from other firms or tech houses thanks to our Audit Common Data Model. Creating your own tool doesn’t have to be a great technology venture as our Common Data Model works with Power BI and Power Apps – both are designed to let you build solutions with low/no-code environments.

Machine learning

We speak regularly to the standard setters for all the jurisdictions we work in. Some of our tools do use machine learning, but only ever in ways that meet the requirements of the ISAs, especially ISA 230 and ISA 500. The core Engine B data extraction platform does not use any machine learning to perform an audit, so you can be confident that you’re opting into any machine learning tools.

Machine learning tends to work on the principle of ‘training’ computers how to do a task by feeding them information and allowing them to learn how to respond to that information. Sometimes a human is still involved in ‘teaching’ or correcting the technology: we call this ‘supervised’ machine learning.

Some machine learning applications have got into ethical trouble because of how this training works, either because they have used biased data to train the algorithm, or because they have used data that wasn’t ethically sourced to do so. E.g, if you use only men’s voices to train a computer for voice commands, it may not learn to understand women. Alternatively, if you train a facial recognition system on pictures of faces you have taken from people’s private clouds without their permission, that would be unethical.

At Engine B, our ethical principles around machine learning are based on the gold standard principles for AI as well as the fundamental ethical principles which bind the accountants and auditors who design and quality assure our tools. We never use data for machine learning without your express permission, and we never share data between engagements. We assess projects before they begin to assess if there is any risk of bias in our dataset, and design alternative approaches to avoid bias where there’s a risk. And as the ICAEW is our largest external stakeholder, we are answerable to them for our ethical conduct.

Engine B is not trying to replace auditors with machine learning. We’re replacing the lowest value work that currently ties up audit experts by building technology that automates the work that computers can do best. Currently, auditors spend huge amounts of time sifting through large volumes of evidence to try and organise it before it can be assessed. This includes things like formatting spreadsheets, reconciling them, and then visually checking them against invoices. Or manually looking through hundreds of thousands of records looking for risky items. Computers can do these things much faster and more accurately than human beings can, so we’re using machine learning to automate these tasks, and to spot patterns it’s hard for human beings to find because we can only keep so much information at the front of our minds at once.

That frees people up to review the evidence once the technology has assembled it, to make judgements, to talk to management, and to take a view on risk. We will never replace human auditors, but we can make better use of them, and our tools aim to make the auditor’s work easier and more valuable.

Audit methodology

The Audit CDM and Knowledge Graphs alone don’t change your audit methodology: they just give you more options. Using analytics tools on top of the CDM and Knowledge Graphs can give your audit much more power. Unlike traditional sampling techniques, Engine B’s analytics solutions have a laser-like focus on the real risks – so if we find anomalies or items for consideration we group them like-with-like and present them in context to allow auditors to only test what needs to be tested. This is a change in methodology which is completely standards-compliant and which provides greater assurance, but without generating significant additional work.

You have the choice about how to use Engine B’s solutions within your methodology. You can use our data extraction tools to make getting evidence easier and then continue with the methodology you’re currently using. If you choose to add the Knowledge Graph or any analytics on top, we can provide support and examples about how to incorporate those into your methodology, and they come with full documentation to help you use them well.

Engine B is interested in the wider possibilities that technology opens up for audit, and we do cutting-edge research into new technology-enabled methodologies, both with academic research and with audit firms. If you’re interested in refreshing your methodology using technology, we’d be happy to talk through how we might co-develop and pilot a 21st-century methodology that suits your firm.

Regulatory compliance

We speak regularly to both regulators and standards setters, including the FRC and bodies like the IAASB, and we’re part-owned by the ICAEW. They are all on board with Engine B solutions and our purpose.

All Engine B products are designed with IFRS, IAS and ISA standards in mind. EB Integration Engine (data extraction and mapping) is designed to support ISA 500: Audit Evidence and ISA 230: Audit Documentation by giving you a clear record of all of your data at every stage. From there, different EB Graph Insights Engine (Audit Common Data Model and Knowledge Graphs) can be used to comply with different requirements. For example, our Going Concern use case is designed to cover ISA 315 and ISA 240 on risks of material misstatement and fraud, as well as ISA 570: Going Concern. You can select the tools you want to meet the requirements of your audit portfolio.

ERP systems

This is a common problem with ERP implementations and firms. All larger audit firms are solving this problem, one client at a time, with lots of inefficiencies. Engine B uses modern tooling to allow for the rapid mapping of client ERP systems to the Engine B data model. This mapping allows us to extract all the data you need for your audit without inefficiency. Many of these ERPs have already been mapped and they can be fine-tuned to a specific implementation. For those that we haven’t mapped, we will work with you to get these maps done.

All Engine B products are designed with IFRS, IAS and ISA standards in mind. EB Integration Engine (data extraction and mapping) is designed to support ISA 500: Audit Evidence and ISA 230: Audit Documentation by giving you a clear record of all of your data at every stage. From there, different EB Graph Insights Engine (Audit Common Data Model and Knowledge Graphs) can be used to comply with different requirements. For example, our Going Concern use case is designed to cover ISA 315 and ISA 240 on risks of material misstatement and fraud, as well as ISA 570: Going Concern. You can select the tools you want to meet the requirements of your audit portfolio.