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An Expert System to Assist Businesses in Financial Decision Making to Enhance Efficiency

International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Year of Publication: 2018
Fuseini Inusah, Anokye Acheampong Amponsah

Fuseini Inusah and Anokye Acheampong Amponsah. An Expert System to Assist Businesses in Financial Decision Making to Enhance Efficiency. International Journal of Computer Applications 181(7):32-39, August 2018. BibTeX

	author = {Fuseini Inusah and Anokye Acheampong Amponsah},
	title = {An Expert System to Assist Businesses in Financial Decision Making to Enhance Efficiency},
	journal = {International Journal of Computer Applications},
	issue_date = {August 2018},
	volume = {181},
	number = {7},
	month = {Aug},
	year = {2018},
	issn = {0975-8887},
	pages = {32-39},
	numpages = {8},
	url = {},
	doi = {10.5120/ijca2018917592},
	publisher = {Foundation of Computer Science (FCS), NY, USA},
	address = {New York, USA}


This research proposes developing an expert system to assist businesses in financial decision making. It is a more technological means of storing and using the knowledge of the human expert. This helps in minimizing cost and inconveniences in hiring experts. No business can survive without effective and efficient management. The major activity in management is decision making. The efficiency of management in decision making is based on speed, accuracy and how easy it is for the decisions to be implemented. This is a herculean task for an average expert. As an exploratory research, the responses of all the fifteen (15) managers were carefully analyzed to get a solution to the problem. With a target of using one day in making a decision, only sixty percent (60%) of human decisions were accurate whiles hundred percent (100%) of the decisions on expert systems were accurate. The speed of the human expert is one (1) decision for every seven (7) days representing 0.14 decisions per day whiles that of the expert system is one (1) decision per day. Only two (2) decisions out of every five (5) decision of the human decision were easy to implement while all the five (5) decisions were easy to implement using the expert system due to the clarity and consistency in its results. The cost of hiring the human expert and the bureaucracy in decision making can be eliminated if an expert system is used. Also, interoperability (systems developed to pick data automatically from other systems) minimizes the errors in data entry.


  1. Jackson, Peter (1998), Introduction To Expert Systems (3 ed.), Addison Wesley, p. 2, ISBN 978-0-201-87686-4
  2. Nana Yaw Asabre (2012) A Mobile Medical Expert System for Health Institutions in Ghana, International Journal of Science and Technology (2 ed) p333-344 ISSN 2224-3577
  3. Duan, Yanqing (1993). The use of expert systems for decision making in organizations. PhD thesis, Aston University.
  4. Buchanan, B.G.; Shortliffe, E.H. (1984).Rule Based Expert Systems: The MYCIN Experiments of the Stanford Heuristic Programming Project. Reading, MA: Addison-Wesley. ISBN 978-0-201-10172-0.
  5. Moses Joel, Macsyma: A Personal History. Invited Presentation in Milestones in Computer Algebra, MIT (May 2008) page 2-7
  6. Lee D. Erman, Frederick Hayes-Roth, Victor R. Lesse, D. Raj Reddy (1988). The Hearsay-II Speech-Understanding System: Integrating Knowledge to Resolve Uncertainty. Blackboard Systems, page. 31 – 86
  7. Brian S.Everitt, ‎Christopher Pa (2011) the PROSPECTOR system for mineral exploration. Menlo Park: Stanford Research Institute Final Report, Project 8172. ... Slocum, J. and Sutherland, G. L. 1977: Development of a computer-based consultant for mineral exploration. Experimental computer-based diagnostic consultant for general internal medicine.
  8. Alan, Hofmeister (1994). "SMH.PAL: an expert system for identifying treatment procedures for students with severe disabilities.".Exceptional Children 61 (2).Retrieved 30 November 2013.
  9. Salvaneschi, Paolo; Cadei, Mauro; Lazzari, Marco (1996). "Applying AI to structural safety monitoring and evaluation". IEEE Expert - Intelligent Systems. 11 (4): 24–34. doi:10.1109/64.511774. Retrieved 5 March 2014.
  10. Smith, Reid (May 8, 1985). "Knowledge-Based SystemsConcepts,Techniques,Examples"(PDF). Research.Retrieved 9 November 2013.
  11. Leondes, Cornelius T. (2002). Expert systems: the technology of knowledge management and decision making for the 21st century. page 1–22. ISBN 978-0-12-443880-4.
  12. W. B. Rauch-Hindin, Artificial Intellisence in Business. Science, and Industrv, Prentice-Hall, Englewood Cliffs, New Jersey, 1986.
  13. C. W. Holsapple and A. B. Whin- ston, Manauer's Guide to ExvertSvstemsUsins Guru, Dow Jones- Irwin, Homewood, Illinois, 1986.
  14. Amita, Etzioni, Humble decision making, harvard business review. 1989, page 122-126
  15. Plous, Scott (1993), The Psychology of Judgment and Decision Making, p. 233
  16. Hodgkinson, Gerard P. (1997-11-01). "Cognitive Inertia in a Turbulent Market: the Case of UK Residential Estate Agents". Journal of Management Studies. 34 (6): 921–945. doi:10.1111/1467-6486.00078. ISSN 1467-6486.
  17. Steven Lucas Counselling. (2009, December 29). Psychology Definition Of The Week: Selective Perception. Retrieved March 18, 2013,
  18. Chua, E. F.; Rand-Giovannetti, E.; Schacter, D. L.; Albert, M.; Sperling, R. A. (2004)."Dissociating confidence and accuracy: Functional magnetic resonance imaging shows origins of the subjective memory experience" (PDF). Journal of Cognitive Neuroscience16 (7):page 1131–1142. doi:10.1162/0898929041920568. PMID 15453969
  19. Perneger, Thomas V.; Agoritsas, Thomas (December 2011). "Doctors and patients' susceptibility to framing bias: a randomized trial". Journal of General Internal Medicine26 (12):page 1411–1417. doi:10.1007/s11606-011-1810-x. PMID 21792695
  20. Schacter, Daniel L.; Gilbert, Daniel Todd; Wegner, Daniel M. (2011) [2009]. Psychology (2nd ed.). New York: Worth Publishers. ISBN 9781429237192.OCLC 755079969.
  21. Sharot, Tali (2011). The optimism bias: a tour of the irrationally positive brain (1st ed.). New York: Pantheon Books. ISBN 9780307378484.OCLC 667609433.
  22. Ebenezer NyakorAssabil (2008) Ascertain guide. Financial accounting for beginners in tertiary institution. Page 295-300
  23. Weston. H, Agor, the logic of intuition: how top executives make important decisions, organizational dynamics, 14, 1986, page 5-18


Expert system, Expert verse Human System, Decision Making, Efficiency