Automated Bank Reconciliation Logic Development
Budget: $30 – $250 USD
Consultant Specialist in Processing Logic for Bank Reconciliation
Project Description:
We are seeking a consultant specialized in automation and data analysis to develop a solution that receives, processes, and returns bank reconciliation information based on data already extracted from our ERP. I already have a script ready to extract the data via Python, so the consultant’s focus will be on creating the business logic that performs dynamic analysis of the data and generates reconciliation outputs.
Project Scope
Data Reception:
Develop a backend-only function that accepts financial data extracted from the ERP (already properly exported in the required format, e.g. a DataFrame).
Processing and Analysis:
Create logic that dynamically analyzes the received data, applying reconciliation rules that may vary according to the context of each bank entry.
Implement functions to verify, compare, and infer relationships between transactions, taking into account exceptions and particularities in the data flow.
Solution Output:
Structure the output as a DataFrame so it can be easily integrated later into the automation system (integration will be handled by me).
Ensure the logic returns reliable results for bank reconciliation, identifying matches, discrepancies, and exceptions.
Professional Requirements
Proven experience in developing automation or data analysis solutions, preferably in financial environments.
Strong proficiency in Python and data manipulation (e.g. with pandas).
Ability to develop robust, flexible business logic that handles dynamic rules and contextual conditions.
Experience with data processing and analysis algorithms for reconciliation (or similar) is a plus.
Comfortable working autonomously, delivering clean, well-structured, and minimally documented code (just enough to explain the approach and how to customize rules).
Deliverables
Python source code for the bank reconciliation processing logic, including functions that accept, analyze, and return processed data.
Inline code comments and minimal documentation explaining the logical approach and how to customize rules if needed.
Unit tests or usage examples demonstrating the logic’s effectiveness across various data scenarios.
How to Apply
Please describe your methodology for developing the business logic and provide estimates of hours and rates for completing this project.
Notes
This project focuses exclusively on creating the processing logic; no post-delivery training or support is required, provided everything functions correctly.
I have historical transaction data available if model training becomes necessary.
I am also open to incorporating artificial intelligence workflows—accepting instructions and inputs via natural language in addition to historical data—if that adds value.
I will handle integration and automation to feed the input data into our ERP myself.
We welcome proposals that leverage low-code or no-code tools (e.g., n8n) if you believe they can add value.
Project Description:
We are seeking a consultant specialized in automation and data analysis to develop a solution that receives, processes, and returns bank reconciliation information based on data already extracted from our ERP. I already have a script ready to extract the data via Python, so the consultant’s focus will be on creating the business logic that performs dynamic analysis of the data and generates reconciliation outputs.
Project Scope
Data Reception:
Develop a backend-only function that accepts financial data extracted from the ERP (already properly exported in the required format, e.g. a DataFrame).
Processing and Analysis:
Create logic that dynamically analyzes the received data, applying reconciliation rules that may vary according to the context of each bank entry.
Implement functions to verify, compare, and infer relationships between transactions, taking into account exceptions and particularities in the data flow.
Solution Output:
Structure the output as a DataFrame so it can be easily integrated later into the automation system (integration will be handled by me).
Ensure the logic returns reliable results for bank reconciliation, identifying matches, discrepancies, and exceptions.
Professional Requirements
Proven experience in developing automation or data analysis solutions, preferably in financial environments.
Strong proficiency in Python and data manipulation (e.g. with pandas).
Ability to develop robust, flexible business logic that handles dynamic rules and contextual conditions.
Experience with data processing and analysis algorithms for reconciliation (or similar) is a plus.
Comfortable working autonomously, delivering clean, well-structured, and minimally documented code (just enough to explain the approach and how to customize rules).
Deliverables
Python source code for the bank reconciliation processing logic, including functions that accept, analyze, and return processed data.
Inline code comments and minimal documentation explaining the logical approach and how to customize rules if needed.
Unit tests or usage examples demonstrating the logic’s effectiveness across various data scenarios.
How to Apply
Please describe your methodology for developing the business logic and provide estimates of hours and rates for completing this project.
Notes
This project focuses exclusively on creating the processing logic; no post-delivery training or support is required, provided everything functions correctly.
I have historical transaction data available if model training becomes necessary.
I am also open to incorporating artificial intelligence workflows—accepting instructions and inputs via natural language in addition to historical data—if that adds value.
I will handle integration and automation to feed the input data into our ERP myself.
We welcome proposals that leverage low-code or no-code tools (e.g., n8n) if you believe they can add value.
Related categories:
Python
Machine Learning (ML)
Database Programming
Artificial Intelligence
Data Analytics