In this article, Engine B’s Head of Audit and Ethics, Franki Hackett, explains why quality data and data extraction tools are the key to executing an effective digital audit.
It’s been clear that getting good quality, well-organised data has been the main barrier to unleashing technology-driven audit for some time. Firms have tried building their own data extraction tools, manually manipulating vast volumes of data, and building advanced analytics only to find they simply can’t scale them without consistent data for years.
The market has introduced some useful part-way solutions, and some firms have had reasonable success in getting out the real basics, like a section of the general ledger. But until now, no solution has been able to crack the nut of truly comprehensive audit data. Why? Because approaches have started with the diversity of the client’s systems and attempted to meet the problem there. This has meant that the only area tools have been able to address so far is the tiny proportion of data which is truly consistent from entity to entity. Unfortunately, this doesn’t address the problem.
A new approach to audit technology
Engine B is taking a different approach. By working with the ICAEW, and audit firms of all sizes, we’ve decided to approach the problem from the other end: by thinking about what audit needs to succeed. That’s enabled us to collaboratively build a Common Data Model (CDM), into which the data from any audit entity can be mapped. This means that instead of trying to find the overlap between every audit client we’re making space for their individual approaches to storing and labelling their data, while leveraging the power of our Microsoft backing to conform it to a common standard.
The potential of this move is revolutionary. Instead of settling for a small sub-set, you can instead extract every field from every table of a client’s ERP system, and know that all of that data will be captured and prepared for easy use by analytics. The CDM is open source, so you can go in and see for yourself how complete it is – and it’s a living document, so more areas (for example the data stored in payroll systems, or process management systems) will be added over time. It also gives you significant control: you can adopt the CDM internally to your audit firm right now, all you have to do is map your client data into it. You can deploy Engine B and have us do the mapping and data ingestion for you, storing the data safely within your firm without ever sharing it with Engine B or anyone else. Or you can even deploy Engine B in your clients, giving you a window into their data without ever having the risk of holding it yourself.
Easy data analysis at your fingertips
Once data is in the CDM, it’s ready for analysis, which means you can quickly and easily scale analytics across your audit portfolio. To make this even simpler, Engine B adds a Knowledge Graph layer, defining the relationships between different data points, so you can interrogate the data and analyse relationships in a straightforward way. For example, the Knowledge Graph will link purchase orders with goods received notes, purchase invoices, purchase transactions and (if you have an open banking link) cash, giving you instant visibility of problems in the purchase to pay process. After that it’s up to you to design your own data-led tools to perform audit, buy a solution from the analytics company that best meets your needs, or come and speak to Engine B if you can’t find anything in the market that you like. We’re not an analytics firm, but we do develop tools where the market hasn’t stepped in yet, if only to get the competition started.
So the only question remains: what would you be able to do if all your audit data was ready to go at the touch of a button?