Good, Bad and Ugly of Data Analytics – A strategy to success
Data Analytics has remained to be a hot topic in majority of the conferences around Financial institutions and Internal Audit in the past few years. I did attend the Analytics track during the IIA Toronto National Conference in 2019 and realized that at times the audience gets the same messaging in various sessions but not a clear understanding of what should be the starting point? What lacks at times is having a Data Analytics strategy for IA, instead adopting an ad-hoc or side of the desk work approach as a long term goal. In my presentation I would try to explain the need, importance and components of a Data Analytics Strategy for an IA function. The three essential parts of the plan/ presentation could be (a) Data; (b) Tools and (c) Skills. Once we have these three essential elements, we can be as creative as can be, tap of a number of online resources, shift from sample testing to full population testing and make strives from preventative to detective and predictive models i.e.; sky is the limit.
Also I would like to provide a dimension of Three Lines of Defence which is commonly used in banks and how the third line (IA) can start shifting some of there successes in Data Analytics to the second line or first line through effective audit recommendations and playing the role of a dialogue and/or strategic partners in managing the risks.
The presenters in the conference (from 2019) mainly focused on a specific tool, or scenario in hand or their journey on the data analytics path, but what was missing how a medium sized IA shop can develop a Data Analytics Strategy and take steps in the right direction. Making space for a Data Analytics Strategy into the overall IA Departmental Strategy should be the way to go in 2020 – be part of it or miss the boat.