Now to specific examples of use. I will show you three examples from our portfolio to give you some ideas and have divided them into three different categories. Firstly, I will use the example of a traditional duplicate payments analysis to explain how known, transaction-based analyses can be improved. I will then describe new analytical approaches, based on the specific example of a comparison of master data quality expressed as an objectively determined indicator. The third example shows the segmenting of business partners in financial accounting – not in the traditional way but based on the posting structure exhibited by these partners.
Artificial intelligence and machine learning – no matter the medium you use (print media, online portals, radio or TV), you will generally come across one of these terms sooner or later. But as the saying goes – everything has already been said, but not yet by everybody.
In this blog post I outline some important issues when analysing SAP® accounts payable postings. Specifically, I discuss which documents should be considered and which can be ignored – or the attributes according to which a compression may, where applicable, also make sense. As this depends on the individual (or on the analysis objective), this should be seen as a suggestion.
Have you already registered for our free webinar? In just 60 minutes you will learn how to embed automated controls into a holistic GRC system. The webinar focuses on the IKS-relevant areas of Galvanize's Highbond Suite.
"Data Lake," more than a new buzzword?! In the future, data analysis will make more comprehensive use of the various data sources of a company. The own data sources should be considered together with publicly accessible data as a big whole as a so-called "Data Lake".
The “Gartner Data & Analytics Summit” took place in Frankfurt on 23 and 24 October 2018. My fellow director Martin and I attended this event to learn about current trends in data analytics. Buzzwords such as artificial intelligence, machine learning, cloud analytics and NPL (Natural Language Processing) are on everyone’s lips and it’s obviously important for us to gauge the current status quo and look at what the future could hold.
The second episode of our interview-podcast is now available online. After the successful first episode of the interview between professor Winkelmann and Stefan Wenig and me, the sequel of the talk is available on several online portals.
In this blog post I will show you how you can objectify and automate risk assessment within your company by linking it with data analyses.
Risk management has always been a key element of a company’s management process. Risks are identified and assessed, measures are taken to mitigate risks and new assessments are performed at regular intervals. This process is present in many companies. Risk assessment is often based on a professional judgement of one or more managers. But why should it always be individuals who have to re-assess risks when data can supply far more objective criteria? With its autumn 2017 release, ACL GRC prepared the way for data-driven risk management. I will now proceed to explain the Assessment Drivers (“key assessment factors”) and the associated benefits in more detail.
When analyzing data in checks or audits, you often find that not everything which looks like a problem really is one. You may frequently check whether compulsory entries in the data are missing, and then possibly deduce problems in data consistency – sometimes your conclusions prove to be false.
In this blog post we want to look at the question of why open items in accounts payable can be well worth a closer look. We will illustrate this taking data from an SAP® IDES system; we will look at the data with ACL™ analytics software.
This year Audit Challenge 2016 (http://audit-challenge.com/) took place from June 20 through 24 in Frankfurt. As part of the event we had the opportunity of delivering a practically oriented paper titled "10 years of successful data analytics" together with Anke Giegandt of BSH Hausgeraete (formerly BSH Bosch Siemens Hausgeraete).