I am currently working on a dataset which contains basically incoming money flows for several clients.So for a given client I'm going to have: a timestampan amount of money incoming for the transactionother informations such as the bank transaction label, client characteritics, and so on and so forthMy goal would be to detect recurrent transations, typically salaries, social aids, or any periodic revenues that can happen monthly for instance. In my opinion this is not a hard task I presume, but I'm not used to it from machine learning point of view. I have heard about ARIMA model, that could be used to decompose the time series I have, but I cannot see how it could help actally in my very case.I am also thinking about using clustering techniques in order to classify the different periodic money flows I have, but I don't know if it is possible in this case.Would you have any ideas?Any help would be appreciated!
Time series - detect similar periodic events
clustering;time series