Hi All,
Please share any idea about the possible use case for implementing machine learning in identifying risk identification and fraud detection which may occur at branch level in a bank. Further there is a window dressing concept in banking sector which might be a good kick-off to work on.
If this is the case so please guide me how to create a sample dataset to work on or give me suggestion which ML algorithm is suitable for identifying requirement for Internal Audit.
Many thanks & kind regards,
Dr. Raza.
These tendencies are distinguishable between fraudsters and honest customers thanks to machine learning algorithms. Because these algorithms can leverage larger data sets, they can identify fraudulent activity much more quickly and precisely than conventional rules-based systems.
Machine learning algorithms may be trained to evaluate even the most seemingly unconnected material in order to uncover a pattern, unlike humans and rules-based programmed systems that may unintentionally or intentionally omit pieces of information.
Machine learning-based solutions for preventing fraud and managing risk begin by gathering and classifying as much previously accumulated data as they can. This covers data on honest business dealings and dishonest business dealings that are categorised as good (honest business dealings or clients) or bad (fraudulent business dealings) (fraudulent transactions or customers).
The machine learning computer is then "taught" by this data how to forecast whether a specific client or transaction is fraudulent or not. It is best to have as much data with fraud patterns as possible for this fraud detection system to be successful because this will provide the algorithm many samples to learn from.
As soon as the machine learning algorithm has been trained, the programme is tailored to the industry and is suitable for usage in a bank's fraud management framework.
Naturally, the algorithm needs to be changed occasionally because it is not perfect. However, it undoubtedly has a number of advantages as a fraud detection tool.
Pritha Chaturvedi : Thank you very much for your swift response. But could you please guide me how to identify the use case. I am stumbling upon the detection of fraudulent cases or to identify any other case related to internal audit. You are requested to please give me an idea how to start and work on use case related to internal audit functionality.
I am actually searching for the start and then I should gather the data. I have a case in mind that I should classify the Agri loan customers and through their profile and other factors, and then identify and predict those customers who are liable to be default in future.
Thanks,
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