How machine learning performs better for internal audit department in the banking industry than usual audit practices. What objectives could be achieved from branch audit, IT audit, Management audit, Thematic audit, and International audit through Machine Learning?
MACHINE LEARNING employs pattern recognition. When applied to auditing in banking or other industries, for purposes of compliance or not compliance, pattern recognition by machine learning is useful to a certain level. However, certain issues that deals with human judgments, conventional human audit approach must also be used. Combining machine learning with human conventional audit approaches would give high audit productivity.
Hi Raza Abidi
Here are some links that will aid your research.
https://quantaverse.net/news-and-blogs/transforming-internal-audit-investigations-with-artificial-intelligence-technology/
https://towardsdatascience.com/artificial-intelligence-for-internal-audit-and-risk-management-94e509129d49
https://blog.protiviti.com/2020/01/02/artificial-intelligence-and-internal-audit-a-pragmatic-perspective/
Hope this helps
Regards
Paul Louangrath : Thank you very much for your swift response. Yes, indeed, I want to combine the human conventional approaches with machine learning. Pl. share some more info and articles if you have.
Looking forward to hearing from you soon.
Best,
Raza.
Akpofure A Enughwure : Thank you very much for your swift response. I surely will go through the details inside the sites you shared with me but also pl share some articles or info that how can I transform and automate the conventional human audit through machine learning.
Human learning is also useful including human learning augmented by today's data analytical tools like Power Query which has inbuilt AI.
Article Beneath the data: Using self-service business intelligence d...
Christopher C Kelly : Thank you very much for your swift response. I shall be very grateful if you tell me about any use case regarding internal audit working which I can use that to implement machine learning model on it.
Hi Raza Abidi . To implement machine leaning in an audit context requires a great deal of data from which the machine can learn. We can do those kinds of audits in payroll, supply chain & suppliers, inventory, and other areas as summarised in my 'Beneath the data' article per my previous response to your question (which provides several examples). To progress from raw data to machine learning, we are looking at - but have not yet used - Azure Synapse Analytics which usefully brings together big data and machine learning into the same environment with AI machine learning built in. This is how I see internal audit evolving in the coming years.
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