Bank Statement Analysis and Transaction Category Prediction

Bank Statement Analysis and Transaction Category Prediction involves summarizing cash inflows and outflows from statements and providing an overview of financial health of individuals. Businesses and NBFCs consider the financial history of borrowers during credit assessments and bank statement analysis tool is being used by various industries for faster processing times, efficiency, and document processing purposes. The objective of this project is to study the cashflows in terms of debits and credits for the retail customers and predict the transaction categories based on mode of transactions and counter parties etc. Various Machine Learning algorithms are used to classify the transaction categories using train data and predict the transaction categories using test data. It also recommends the algorithm that gives the best accuracy score.

Bank Statement Analysis and Transaction Category Prediction – Salient Features:
– Deriving data insights based on the states of account activities
– Tokenizing the text data using NLP
– Applying multiple different classification algorithms
– Model evaluation and testing
– Recommendation of best algorithm

Tech Stack:
Machine Learning Algorithms, NLP, Python

Industry:
Banking and Finance