Downloading: Intelligent Agents Based Fuzzy Liquidity Management Technique for Mobile Money Transfer
International Journal of Science and Research (IJSR)

International Journal of Science and Research (IJSR) | Open Access | Fully Refereed | Peer Reviewed International Journal

ISSN: 2319-7064

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Intelligent Agents Based Fuzzy Liquidity Management Technique for Mobile Money Transfer

Millicent Murithi, George Okeyo, Michael Kimwele

Abstract: Mobile money transfer technologies are providing services to millions of people. People can safely transfer money through the mobile phones without necessarily relying on bulky cash. M-Pesa is an example of a mobile money transfer system prominent in Kenya. Mobile money liquidity management, having approximately the right amounts of both the physical cash and e-cash, remains a key challenge for many mobile money retail agents. In most cases, the mobile money customers are unable to transact. On the other hand, mobile money retail agents have to make one or more trips to the bank in order to rebalance the liquidity. The mobile money transfer systems operate in uncertain environment. A review of intelligent agents and fuzzy logic based applications in uncertainty management shows that integrating the two one can have a more precise mobile money liquidity management technique. In this paper we present liquidity management technique that allows integration of intelligent agent and fuzzy logic. Intelligent agents will analyze both internal and external environment of the mobile money transfer system to collect all the data affecting liquidity management. Fuzzy logic manages the accumulated data to give a more precise output of a predicted e-cash and physical cash. Evaluation of the technique showed that it effectively managed liquidity with lower percentage error as compared to the existing liquidity management techniques and tools. The study recommends the possibility of linking the tool with EFTPOS or the banking systems that directly or indirectly affect the mobile money transactions of a specific group of people in order to provide more meaningful data trends / patterns on mobile money.

Keywords: fuzzy logic, liquidity management, e-cash, physical cash and MPesa