ACL Con­nect­ions 2018 – new SAP® con­nector, ma­chine learning, predictive analytics

ACL™ Connections 2018 was held in Philadelphia from 14 to 18 October. This is the annual global customer event of our partner ACL Services Ltd., headquartered in Vancouver.

Here is a brief summary of the most important topics covered.

Generally, we received very good feedback from participants about the event. It is a mix of product-related information on the data analytics, audit and risk management products ACL™ Analytics, ACL™ Analytics Exchange and ACL™ GRC. The software manufacturer also shares its current roadmap with its customers and gives an insight into its direction and strategy. This is supplemented with training sessions (such as workshops on project management or efficient design of visualisations and data storyboarding) which are also useful beyond the ACL™ portfolio itself.

While we clearly cannot give a full résumé of the contents of the three days, here are a few key points viewed from our perspective.


1. Redesign of data extraction from SAP®

ACL™ analytics tools offer a number of predefined connectors for a wide range of data sources, such as Salesforce, Twitter, Exchange, Email, SQL, Hive, Amazon Redshift, and Spark, to name just a few. This range is being expanded to include a new connector for SAP® data. We are pleased that the underlying technology is based on our product dab:Exporter and that we have had the opportunity to support ACL™ in implementing this connector.

Fig. 1: Connectors in ACL™ (including SAP® access)

As data access is incorporated into the existing usability concept of ACL™ connectors, its look and feel is slightly different to what existing customers of our client/server product are accustomed to. However, a decisive part of our know-how has been incorporated into the underlying technology. Release is planned for the end of this year – so you can look forward to new possibilities for “access to SAP® data” using ACL™. Obviously, the connector will in time also be expanded to include new functionalities, so you can expect lots more from us here in future.


2. Enhancement to include machine learning and predictive analytics

It’s hardly surprising that data analytics products are being expanded to include the latest machine learning methods. The K-MEANS clustering algorithm was presented as a first example. This unsupervised learning algorithm is now available in ACL™ analytics tools and makes it possible to identify new correlations in your databases.

Fig. 2: Example of the K-MEANS algorithm which is to be implemented in ACL™ in future

Extended predictive analytics functions via an existing R/Python connection or a new outlier identification feature were also announced. These are all important steps, as combining traditional data analytics with AI/ML methods is a vital part of current technical development; in this connection, please also see our blog post on the Gartner Data Analytics Summit. Data scientists will thus continue to receive future-proof support with ACL™ products and can also rely on ACL™ to build analyses based on explorative self-service.


3. From insight to action – completing the ACL™ GRC product portfolio

The product ACL™ GRC has also been enhanced to include key functionalities. As detailing all innovations would exceed the framework of this post, we will limit ourselves to a just few highlights. As well as supporting audit departments and data analytics specialists, the cutting-edge cloud platform ACL™ GRC also offers excellent opportunities pertaining to risk management (enterprise risk management) and the internal control system.

Fig. 3: Definition of a metric (e.g. KPI or KRI) based on the example credit note volume

Performance of regular controls can be monitored transparently via the mission control cockpit, both by the control owner at management level and also by the control performer as part of operational control. Data analytics results can in turn be managed in the results module; this involves mapping KPIs/KRIs based on the data, including notifying the competent individuals via automated workflows.

Fig. 4: Setting up a real-time trigger (workflow)

Another important topic is the visualisation of facts in storyboards and case management of analytics results, i.e. the processing of individual transactions which are triggered by the controls. (The latter can, incidentally, provide an excellent basis for implementing supervised learning/semi-supervised machine learning approaches). As a whole, it is of course also an excellent basis for BPM (Business Performance Management).

Fig. 5: Example of a business performance storyboard

In summary, ACL™ definitely has its finger on the pulse as a solutions manufacturer – both as regards pure data analytics and also the ACL™ GRC platform, which combines data analytics, audit, compliance, risk management, internal controls and business performance management in one environment and integrates the various stakeholders.

As official distributor of the ACL™ solution in the German-speaking D-A-CH region, we will of course be pleased to answer any detailed questions you may have on this topic.

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