MFS Data Reconciliation Officer, Fintech

The MFS Data Reconciliation Officer is responsible for ensuring the accuracy, integrity, and consistency of financial and transactional data across mobile financial service platforms. This role involves reconciling transactions between internal systems, partner banks, telecom operators, and third-party service providers, identifying discrepancies, and ensuring timely resolution. What You Will Do Transaction Reconciliation Perform daily, weekly, and monthly reconciliation of MFS transactions (wallet, bank, agent, merchant) Compare transaction records between: Core banking systems, Mobile money platforms, Switches/payment gateways, and Partner institutions Identify and investigate discrepancies (missing, duplicated, failed, or delayed transactions) Exception Handling & Resolution: Analyze reconciliation breaks and determine root causes Work with internal teams (IT, operations, finance) to resolve mismatches Escalate unresolved issues in a timely manner Maintain logs of all discrepancies and resolutions Settlement Monitoring Monitor settlement accounts (bank and wallet float accounts) Ensure timely settlement of transactions between partners Verify settlement reports and confirm accuracy of balances Data Integrity & Control Ensure completeness and accuracy of transaction data Implement and maintain reconciliation controls and procedures Support audits by providing required reconciliation documentation Compliance & Risk Management Ensure adherence to regulatory requirements and internal policies Identify potential fraud or suspicious transactions Support risk and compliance teams in investigation What You Will Bring Bachelor's degree in: Accounting, Finance, Economics, Information Systems or related field 2-5 years' experience in financial reconciliation, mobile money/fintech operations, banking or payment systems Strong knowledge of reconciliation processes and an understanding of mobile money/MFS ecosystem Proficiency in Excel (advanced functions, pivot tables, VLOOKUP/XLOOKUP), proficiency in SQL is preferred Data analysis tools, analytical skills and high attention to detail Strong problem-solving ability Ability to analyze large datasets and identify anomalies Good communication and reporting skills Time management and ability to meet deadlines Ability to work under pressure