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dc.contributor.authorGathoni, Hellen N
dc.date.accessioned2013-03-01T05:44:42Z
dc.date.issued2011
dc.identifier.citationMasters of science in computer scienceen
dc.identifier.urihttp://erepository.uonbi.ac.ke:8080/xmlui/handle/123456789/12690
dc.description.abstractCheque clearing process takes a long time thus lagging behind the country's economy. This is even worse for cheques collected from Upcountry's and remote areas as clearing takes 10 and 14 days respectively. The existing cheque clearing system takes 4 days for a cheque to clear and 6 days for a dishonoured cheque to get to the presenting branch within the local areas and 15 days to 21 days for upcountry and remote areas respectively. This called for need to adopt cheque truncation that has been implemented in many countries. In Kenya the process will reduce clearing cycle to two from four days taken to process cheque issued in major towns and to 4 days from 10 and 14 days respectively the number of days for clearing upcountry and remote cheques [Kenya Bankers Association (KBA)chief executive Habil Olaka said in an interview]. This has called the need for an efficient clearing system that will reduce clearing days to 1 irrespective of geographical locations of bank branches within the country. Thus the project aims at modelling cheque processing in search for efficiency. To model a modified model to achieve efficiency the researcher used data gathering techniques such as document scan, interviews and observation to understand the existing processes from the time a cheque is deposited to the time its cleared or returned. Simulation technique was used to model both the existing and the modified model which was implemented using MATLAB simulation software and hence implementation of computer science concepts. The modified models allows for image processing by truncating cheques at the branch level thus controlling processing of physical cheques and truncation of cheques when they get to CPC thus eliminating redundancy of capturing images which slow cheque processing. Optical character readers (OCR)also introduced at CPC allows for auto reconciliation of masked amount and code lines unlike before where it was done manually. This is reduced error rate of processed cheque from 12.89% to 4.04% as most the clearing errors previously detected on the second day are worked on at the time of cheque presentation thus an improved measure of efficiency.en
dc.description.sponsorshipUniversity of Nairobien
dc.language.isoenen
dc.publisherUniversity of Nairobien
dc.subjectModellingen
dc.subjectcheque processing systemsen
dc.titleModelling cheque processing systems: search for efficiencyen
dc.typeThesisen
local.publisherSchool of Computing and Informaticsen


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