Research Article
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For Loan Processing a Fuzzy Process Mining

Year 2023, Volume: 9 Issue: 3, 511 - 530, 20.09.2023
https://doi.org/10.28979/jarnas.1239492

Abstract

Process mining has been used extensively in recent years to develop the steps of the business and it is an important technique to remove waste and reduce process costs. The aims of this study indicate congestion, workflow which lived a long time, and stuff or system statistics in the banking real estate transaction process. The process mining practice is applied in bank business loans. In the bank process, the most used and complicated business is a bank loan transaction. The process mining implementation pattern is created with sample and flow gains of process development. Then, the new workflow is designed and the pattern is executed. In the first stage of the total loan period, 7.84 hours of earnings are obtained. Visualizations of the process have been affected with the help of fuzzy model algorithms necessary for a huge number of incidents and activities. Workflow analysis and gathering information for studies were to be effortless with the support of fuzzy models. As a result of the analysis based on the flows, the knowledge pool is created by getting the know-how such as the average duration of the process and the deviations in the users or systems. The results indicated that process mining is a significant methodology for developing bank loan transactions and enhancing their performance.

References

  • Aalst, W., Reijers, H.A., Weijters, A.J.M.M., Van Dongen, B.F., Alves deMedeiros, A.K., Song, M., and Verbeek, (H.M.W. (2007). Business process mining: An industrial application, Inf. Syst., 32 (5) 713-732, http://dx.doi.org/10.1016/j.is.2006.05.003
  • Arpasat P. (2022), Data-Driven Analysis of Loan Approval Service of a Bank using Process Mining, 20th International Conference on ICT and Knowledge Engineering, 1-6.
  • Bahaweres R., Amna H., Nurnaningsih D. (2022), Improving Purchase to Pay Process Efficiency with RPA using Fuzzy Miner Algorithm in Process Mining, 2022 International Conference on Deci-sion Aid Sciences and Applications (DASA).
  • Caron, F., Vanthienen, J., and Baesens, B. (2013) Comprehensive rule-based compliance checking and risk management with process mining", Decis. Support Syst., 54 (3) 1357-1369. http://dx.doi.org/10.1016/j.dss.2012.12.012
  • Castellanos, M., Alves de Medeiros, A.K., Mendling, J., Weber, B., and Weijters, A.J.M.M. (2009) Business Process Intelligence. IGI Global, 467-491.
  • De Weerdt, J., Schupp, A., Vanderloock, A., and Baesens, B. (2013) Process mining for the multi-faceted analysis of business processes—A case study in a financial services organization, Com-put. Ind., vol. 64 (1)57-67, http://dx.doi.org/10.1016/j.compind.2012.09.010
  • Dogan O. (2021), Process mining technology selection with spherical fuzzy AHP and sensitivity analy-sis, Expert Systems with Applications, 178, 114999, 1-9.
  • Erdogan, T.G., and Tarhan, A. (2018) A goal-driven evaluation method based on process mining for healthcare processes", Appl. Sci. (Basel), 8 (894) 1-22.
  • Fernández-Llatas, C., Benedi, J.M., García-Gómez, J.M., and Traver, V. ( 2013).Process mining for individualized behavior modeling using wireless tracking in nursing homes", Sensors (Basel), 13 (11) 15434-15451, http://dx.doi.org/10.3390/s131115434 PMID: 24225907
  • Force, I.T. (2011) Process Mining, Manifesto Lecture Notes in Business Information Processing, 1, Springer,. Günther, C. W., and Van der Aalst, W. M. P. (2007) Fuzzy Mining – Adaptive process simplification based on multi-perspective metrics, BPM, 328-343.
  • Huang, C., Cai, H., Li, Y., Du, J., Bu, F., and Jiang, L., (2017) A process mining based service compo-sition approach for mobile information systems", Hindawi Mobile Information Systems, 1-14, http://dx.doi.org/10.1155/2017/3254908
  • Lee, C.K.H., Ho, G.T.S., Choy, K.L., and Pang, G.K.H., (2014) A RFID-based recursive process mining system for quality assurance in the garment industry", Int. J. Prod. Res., 52 (14) 4216-4238, http://dx.doi.org/10.1080/00207543.2013.869632
  • Li, M., Liu, L. Yin, L. and Zhu, Y. (2011). A process mining based approach to knowledge mainte-nance, Inf. Syst. Front., vol. 13, no. 3, pp. 371-380, http://dx.doi.org/10.1007/s10796-010-9287-4
  • Okoye, K., Tawil, A.R.H., Naeem, U., Bashroush, R., and Lamine, E., (2014) A semantic rule-based approach supported by process mining for personalised adaptive learning", Procedia Comput. Sci., 37, 203-210, http://dx.doi.org/10.1016/j.procs.2014.08.031
  • Orellana, A., Castañeda, L.,and Valladares, A. (2018) Analysis of hospital processes from the time perspective using process mining", Rev. IEEE Am. Lat., 16 (6) 1741-1748, http://dx.doi.org/10.1109/TLA.2018.8444394
  • Roldán, J.J., Olivares-Méndez, M.A., del Cerro, J., and Barrientos, A. (2018) Analyzing and improv-ing multi-robot missions by using process mining", Auton. Robots, 42 (6) 1187-1205, http://dx.doi.org/10.1007/s10514-017-9686-1
  • Valensia L., Andreswari R., and Fauzi R. (2021), Implementation of Process Mining to Discover Stu-dent Learning Patterns using Fuzzy Miner Algorithm (Case Study: Learning Management System (LMS) Telkom University), 3rd International Conference on Electronics Representation and Al-gorithm (ICERA), Doi: 10.1109/ICERA53111.2021.953878
  • Weber, P., Bordbar, B., and Tiño, P. (2013) A framework for the analysis of process mining algo-rithms", IEEE Trans. Syst. Man Cybern. Syst.,43(2) 303-317, http://dx.doi.org/10.1109/TSMCA.2012.2195169
  • Werner, M. (2017) Financial process mining - Accounting data structure dependent control flow infer-ence", Int. J. Account. Inf. Syst., vol. 25, pp. 57-80, http://dx.doi.org/10.1016/j.accinf.2017.03.004
  • Yazıcı, I.E., and Engin, O. (2018) Use of process mining in bank loan transactions", 6th International GAP Engineering Conference- GAP2018, 787-791 Urfa, Turkey
  • Yazici, I.E., and Engin, O.( 2020) Use of process mining in bank real estate transactions and visuali-zation with fuzzy models", Proceedings of the INFUS-International Conference on Intelligent and Fuzzy Systems, 265-272 Istanbul, Turkey, Springer. https://doi.org/10.1007/978-3-030-23756-1_33
Year 2023, Volume: 9 Issue: 3, 511 - 530, 20.09.2023
https://doi.org/10.28979/jarnas.1239492

Abstract

References

  • Aalst, W., Reijers, H.A., Weijters, A.J.M.M., Van Dongen, B.F., Alves deMedeiros, A.K., Song, M., and Verbeek, (H.M.W. (2007). Business process mining: An industrial application, Inf. Syst., 32 (5) 713-732, http://dx.doi.org/10.1016/j.is.2006.05.003
  • Arpasat P. (2022), Data-Driven Analysis of Loan Approval Service of a Bank using Process Mining, 20th International Conference on ICT and Knowledge Engineering, 1-6.
  • Bahaweres R., Amna H., Nurnaningsih D. (2022), Improving Purchase to Pay Process Efficiency with RPA using Fuzzy Miner Algorithm in Process Mining, 2022 International Conference on Deci-sion Aid Sciences and Applications (DASA).
  • Caron, F., Vanthienen, J., and Baesens, B. (2013) Comprehensive rule-based compliance checking and risk management with process mining", Decis. Support Syst., 54 (3) 1357-1369. http://dx.doi.org/10.1016/j.dss.2012.12.012
  • Castellanos, M., Alves de Medeiros, A.K., Mendling, J., Weber, B., and Weijters, A.J.M.M. (2009) Business Process Intelligence. IGI Global, 467-491.
  • De Weerdt, J., Schupp, A., Vanderloock, A., and Baesens, B. (2013) Process mining for the multi-faceted analysis of business processes—A case study in a financial services organization, Com-put. Ind., vol. 64 (1)57-67, http://dx.doi.org/10.1016/j.compind.2012.09.010
  • Dogan O. (2021), Process mining technology selection with spherical fuzzy AHP and sensitivity analy-sis, Expert Systems with Applications, 178, 114999, 1-9.
  • Erdogan, T.G., and Tarhan, A. (2018) A goal-driven evaluation method based on process mining for healthcare processes", Appl. Sci. (Basel), 8 (894) 1-22.
  • Fernández-Llatas, C., Benedi, J.M., García-Gómez, J.M., and Traver, V. ( 2013).Process mining for individualized behavior modeling using wireless tracking in nursing homes", Sensors (Basel), 13 (11) 15434-15451, http://dx.doi.org/10.3390/s131115434 PMID: 24225907
  • Force, I.T. (2011) Process Mining, Manifesto Lecture Notes in Business Information Processing, 1, Springer,. Günther, C. W., and Van der Aalst, W. M. P. (2007) Fuzzy Mining – Adaptive process simplification based on multi-perspective metrics, BPM, 328-343.
  • Huang, C., Cai, H., Li, Y., Du, J., Bu, F., and Jiang, L., (2017) A process mining based service compo-sition approach for mobile information systems", Hindawi Mobile Information Systems, 1-14, http://dx.doi.org/10.1155/2017/3254908
  • Lee, C.K.H., Ho, G.T.S., Choy, K.L., and Pang, G.K.H., (2014) A RFID-based recursive process mining system for quality assurance in the garment industry", Int. J. Prod. Res., 52 (14) 4216-4238, http://dx.doi.org/10.1080/00207543.2013.869632
  • Li, M., Liu, L. Yin, L. and Zhu, Y. (2011). A process mining based approach to knowledge mainte-nance, Inf. Syst. Front., vol. 13, no. 3, pp. 371-380, http://dx.doi.org/10.1007/s10796-010-9287-4
  • Okoye, K., Tawil, A.R.H., Naeem, U., Bashroush, R., and Lamine, E., (2014) A semantic rule-based approach supported by process mining for personalised adaptive learning", Procedia Comput. Sci., 37, 203-210, http://dx.doi.org/10.1016/j.procs.2014.08.031
  • Orellana, A., Castañeda, L.,and Valladares, A. (2018) Analysis of hospital processes from the time perspective using process mining", Rev. IEEE Am. Lat., 16 (6) 1741-1748, http://dx.doi.org/10.1109/TLA.2018.8444394
  • Roldán, J.J., Olivares-Méndez, M.A., del Cerro, J., and Barrientos, A. (2018) Analyzing and improv-ing multi-robot missions by using process mining", Auton. Robots, 42 (6) 1187-1205, http://dx.doi.org/10.1007/s10514-017-9686-1
  • Valensia L., Andreswari R., and Fauzi R. (2021), Implementation of Process Mining to Discover Stu-dent Learning Patterns using Fuzzy Miner Algorithm (Case Study: Learning Management System (LMS) Telkom University), 3rd International Conference on Electronics Representation and Al-gorithm (ICERA), Doi: 10.1109/ICERA53111.2021.953878
  • Weber, P., Bordbar, B., and Tiño, P. (2013) A framework for the analysis of process mining algo-rithms", IEEE Trans. Syst. Man Cybern. Syst.,43(2) 303-317, http://dx.doi.org/10.1109/TSMCA.2012.2195169
  • Werner, M. (2017) Financial process mining - Accounting data structure dependent control flow infer-ence", Int. J. Account. Inf. Syst., vol. 25, pp. 57-80, http://dx.doi.org/10.1016/j.accinf.2017.03.004
  • Yazıcı, I.E., and Engin, O. (2018) Use of process mining in bank loan transactions", 6th International GAP Engineering Conference- GAP2018, 787-791 Urfa, Turkey
  • Yazici, I.E., and Engin, O.( 2020) Use of process mining in bank real estate transactions and visuali-zation with fuzzy models", Proceedings of the INFUS-International Conference on Intelligent and Fuzzy Systems, 265-272 Istanbul, Turkey, Springer. https://doi.org/10.1007/978-3-030-23756-1_33
There are 21 citations in total.

Details

Primary Language English
Subjects Industrial Engineering
Journal Section Research Article
Authors

İbrahim Ethem Yazıcı This is me 0000-0003-2778-934X

Orhan Engin 0000-0002-7250-0317

Early Pub Date September 19, 2023
Publication Date September 20, 2023
Submission Date January 19, 2023
Published in Issue Year 2023 Volume: 9 Issue: 3

Cite

APA Yazıcı, İ. E., & Engin, O. (2023). For Loan Processing a Fuzzy Process Mining. Journal of Advanced Research in Natural and Applied Sciences, 9(3), 511-530. https://doi.org/10.28979/jarnas.1239492
AMA Yazıcı İE, Engin O. For Loan Processing a Fuzzy Process Mining. JARNAS. September 2023;9(3):511-530. doi:10.28979/jarnas.1239492
Chicago Yazıcı, İbrahim Ethem, and Orhan Engin. “For Loan Processing a Fuzzy Process Mining”. Journal of Advanced Research in Natural and Applied Sciences 9, no. 3 (September 2023): 511-30. https://doi.org/10.28979/jarnas.1239492.
EndNote Yazıcı İE, Engin O (September 1, 2023) For Loan Processing a Fuzzy Process Mining. Journal of Advanced Research in Natural and Applied Sciences 9 3 511–530.
IEEE İ. E. Yazıcı and O. Engin, “For Loan Processing a Fuzzy Process Mining”, JARNAS, vol. 9, no. 3, pp. 511–530, 2023, doi: 10.28979/jarnas.1239492.
ISNAD Yazıcı, İbrahim Ethem - Engin, Orhan. “For Loan Processing a Fuzzy Process Mining”. Journal of Advanced Research in Natural and Applied Sciences 9/3 (September 2023), 511-530. https://doi.org/10.28979/jarnas.1239492.
JAMA Yazıcı İE, Engin O. For Loan Processing a Fuzzy Process Mining. JARNAS. 2023;9:511–530.
MLA Yazıcı, İbrahim Ethem and Orhan Engin. “For Loan Processing a Fuzzy Process Mining”. Journal of Advanced Research in Natural and Applied Sciences, vol. 9, no. 3, 2023, pp. 511-30, doi:10.28979/jarnas.1239492.
Vancouver Yazıcı İE, Engin O. For Loan Processing a Fuzzy Process Mining. JARNAS. 2023;9(3):511-30.


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