How to identify recurring patterns in this set of transactional data
I don't know the model you use, but I would suggest the perhaps old-fashioned feature engineering approach: 


In each set of transactions, calculate the duration between two consecutive transactions for every pair of consecutive transactions (i.e. difference between the dates). Then add the standard deviation of these durations as a a feature, so that a very regular transaction set should get a near zero value.
Same idea with the amount of the transaction: the standard deviation will be zero if the amount never changes.
Additional ideas:


number of distinct amounts across all transactions
number of distinct duration values between transactions in days, weeks, months, years. 
standard deviation of the sum by day/week/month/year