Case study: Bank Account Forecast
A well-known commercial bank in Australia is interested in estimating the number of new bank account opened by customers in each year. The number of new accounts opened in this bank has increased slowly over years even during the global financial crisis (2008–2009). Top management strongly believes that they need a long-term strategic plan for the bank which is a 5-year forecast for the number of new accounts opened. To achieve this aim, the bank operations manager examined past account data and also extracted the employment rate over 30 years (1991-2020). The resulting data are shown in below table:
Year
No of new account(000)
Employment Rate (%)
Year
No of new account(000)
Employment Rate (%)
1991
3.136
90.42
2006
6.007
95.22
1992
3.309
89.27
2007
5.826
95.62
1993
3.803
89.13
2008
8.266
95.77
1994
6.807
90.28
2009
7.128
94.44
1995
2.386
91.53
2010
9.670
94.79
1996
4.643
91.49
2011
11.419
94.92
1997
2.911
91.64
2012
11.335
94.78
1998
2.553
92.32
2013
9.358
94.34
1999
4.422
93.13
2014
10.418
93.92
2000
3.613
93.72
2015
10.459
93.95
2001
3.948
93.26
2016
7.328
94.29
2002
3.347
93.63
2017
9.004
94.41
2003
3.907
94.07
2018
8.559
94.70
2004
4.071
94.60
2019
8.476
94.84
2005
6.666
94.97
2020
8.635
93.39
Using the following forecast methods discuss which method fits best for the bank’s strategic plan. You need to justify the selection of one method over another.
Moving average (you need to find the best value for n)
Linear trend (trend projection)
Linear regression
Can you exclude a portion of the data for the analysis? If yes, why?
The bank operations manager also collected the data on Australia’s GDP Per Capita (Gross Domestic Product) and believes that GDP Per Capita can also affect the number of a bank accounts. Below table shows the data for the same period:
Year
GDP Per Capita (000A$)
Year
GDP Per Capita (000A$)
1991
18.8218
2006
36.04492
1992
18.57012
2007
40.96005
1993
17.63453
2008
49.60166
1994
18.04614
2009
42.77236
1995
20.31963
2010
52.02213
1996
21.86133
2011
62.51783
1997
23.4686
2012
68.01215
1998
21.31896
2013
68.15011
1999
20.53304
2014
62.51079
2000
21.67925
2015
56.75572
2001
19.49086
2016
49.97113
2002
20.08248
2017
54.02797
2003
23.44703
2018
57.35496
2004
30.43068
2019
55.0572
2005
33.99924
2020
51.81215
Between GDP Per Capita and employment rate which one do you think can better estimate the number of new bank accounts?
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The post OMGT2228: A well-known commercial bank in Australia is interested in estimating the number of new bank account opened by customers in each year: OPERATIONS MANAGEMENT Assignment, RMIT appeared first on Singapore Assignment Help.