Developing Evaluation Criteria
The report is intended to show the appropriateness of the chart in the Bendigo and Adelaide Bank. The report is based on the annual report of the company published in 2015. The main from of the evaluation of the report is extracted from the annual report of the company in 2015. The first part of the assignment has been status on the development criteria of the graphs and the development criteria in the graph. In this particular segment of the report different aspects of the progress criteria of the graphs has been clearly specified. The second portion of the assignment has been able to state evaluation of the information stated in the first section (Wang 2014).
This section has discussed important form of graphs such as bar graph (vertical bar graph and stacked bar graph), doughnut graph and pie chart
360 Degrees Segregation: The Pie Chart has been able to consider 360 degrees segregation. The main benefit of this has been seen with the data representation with relative data depicted in multiple classes. For example, the main benefit has been seen with the base remuneration, STI index and LTI index (Asnicar et al. 2015).
Percentage values: This value is seen to be based on the percentage value of the specific weightings as per LTI and STI index.
Simple representation of multiple classes: The pie chart has been able to segregate the data based on the relative proportion of the data in multiple classes. This form of the data representation is based on the simplest representation (Zhang et al. 2014).
Change of variables in terms of currency: This evaluation is evident in the stacked and vertical bar graph.
Change of variables in terms of percentage: The is commonly used in vertical bar graph and stacked bar graph.
Change in the values adding up to a final value: The vertical graph has been seen to be ideal for these types of the representation.
Particular range of information in currency: The various types of the other consideration have been seen with the vertical bar graph with histogram. The X-axis may consist of number of years and the Y-axis can consist of currency. The vertical bar graph has considered Y-axis can be discerned in form of percentage (Asnicar et al. 2015).
Effective variables used: These values have been seen with the operating expenses, Net Income Interest and credit expenses. The bar graph has been identified to consider reducing trend in the financial data.
Mentioning all points in the trends: This particular representation of the data has been seen with the vertical bar graph integration. The main benefit of this has been seen with higher or lower variables. The Y-axis of the data is identified with the cash EPS (cents). In vertical bar graph the items such as STI paid is seen in X-axis. The Y-axis has been further able to consider cash earnings, Credit, Tax and Net Interest income (Martin and Bryan 2016).
Depiction of trends overtime: This particular aspect is evident by histogram. The X-axis has been depicted with the years to represent the particular trend.
Range of variables: Same as the vertical bar graph, kindly show the usefulness of stacked bar graph and identify the quantity in the individual groups.
Percentage-of-the-whole data for each group-The various identified has been inferred as percentage of entire of the each group and the plotting is done based on individual percentage applicable to total amount in all the groups (Ma et al. 2014).
Conversion of multiple data sets in one single stacked information – The stacked bar is useful for the identification of the quantities in the individual groups. It has been further seen that the different variable are evaluated as percentage-of-the-whole of each group and plotting of the same as per individual percentage applicable to the total value in group. The X-axis considers plotting of the information based on liability pricing, asset mix and liability mix.The Y-axis considers the percentage movement of the different types of the variables, which has been used in the graph (Nomoto, Sakurai and Yokoo 2017).
Report Evaluation
Combining all points in data set: This has been seen to be particularly evident in line graphs. The various types of the evaluations from the X-axis have been represented based on number of period and the Y-axis is shown with the different values such as market indices.
Changes in the data: The graph has been seen to be useful with the usefulness in the representation of the data based on multiple fluctuations.
Process of Encoding: The short and the long figure have been maintained for the simplicity in the data.
Integration of Data: The integration of the data has been considered based on the financial representation of the data.
Customization of the data: The data customization has been identified in different legends, in a particular dataset.
Determinants of Geometrics: The geometric metric has been taken into consideration based on 360-degree segregation. The main form of the variables has been considered based on the STI index and LTI index.
Association with different information- In this particular case the data may be associated to two or more styles focusing on the different nuances used in the study.
Bendigo and Adelaide Bank is seen to use pie chart to depict the base payment, long-term incentives and short-term incentives. The company has been further seen to be prompt enough to show the various types of the factors associated to the remuneration of the Executive Customer Voice, Managing Director, CFO and Executive Director. It has been identified that the company has been able to represent executive risk (Schulz and Toni 2015).
Based on the relevant values of the data such as remuneration, STI and the LTI, the various types of the values have been seen to be depicted based on the 360 degrees and percentage values. This evaluation is matched with (Criteria1 and criteria 2) and depicts the same in the pie chart of the report (Bourdelle,. and Cathelineau 2015).
It has been inferred that information representation related to the various information associated to the division and other variables like equity remuneration and cash remuneration. This has been further seen to be related to the equity remuneration. The varied range of the variables has been matched with the criteria 11.
Bendigo and Adelaide Bank has been able to vertical bar graph to show the different aspects of the data that is identified as cash earnings for the financial year 2014 to 2015.
Matching Criteria's
The cash earnings of the company has been further seen to be ranging as per Staff costs, Homesafe, Net Interest Income and other expenses. This has been seen with a total increase of the same from $ 382.3 m to $ 432.4. The particular increase has been further seen to be depicted from the Increase or decrease of variables as per the variables set under the Criteria 4.
The depiction of the criteria 5 has been has been met with the decrease or the increase in terms of the percentage. For example, the first graph has been able to depict the total percentage increase of 13.1 % due to the cash earnings.
The cumulative adding values have been identified with the addition of the relevant variables amounting to FY 14. For instance, $(65.9+382.3+31.8+13.1-29.1-25.3+13.6-19.9) m = $ 432.4 m. In this particular way, the requirement is identified to be matching with the increasing or the decreasing values adding up to the final value mentioned in the Criteria 6 of the report.
In a similar way, the X-axis has identified the operating expenses of the company has been recognized in terms of the variables such as staff costs, rent, IT expenses and consideration of other expenses. This particular integration has been matched with Criteria 17.
The graphical representation of Bendigo and Adelaide Bank has been seen with interpretation of Short-term remuneration outcomes from 2011 to 2015. Number of years has been taken into consideration in the X-axis. The histogram has been further able to depict the average STI paid which has been further expressed in percentage. Histogram is able to consider all the points trends, which needs to be adhered, based on Criteria 14. Considering all the data set points, the relevant criteria’s has been stated as per Criteria 13.
Bendigo and Adelaide bank has been further seen to signify the analysis of the net margin on the interest. The representation of the same has been further depicted in both positive and negative increase of the Y-axis. The variables in the X-axis have included asset pricing, asset mix and liability mix. The Y-axis has been depicted with the community bank and alliance share. This has been seen with community bank and alliance share, the same has been match criteria 17.
The X-axis in the given case the graph has been plotted with the variables ranging from the asset pricing, liability pricing and liability mix. The Y-axis of the data has been able to consider the percentage movement of the data.
The stacked beneficial for retail term and depicting deposit in a single graph. It has been further depicted that the different aspects of the data placed in the stacked bar graph is placed in the X- axis comprising of asset pricing, asset mix and liability mix. It has been also seen that the Y-axis of the data in the graph has been shown based on community bank and alliance share. This particular fluctuation has been seen matching with criteria 15.
In a similar way the company has been use the three tiers of the data for requirements for doubtful debts.
It has been seen that the bank has used doughnut graph show the composition of the loans. This is effective under criteria 8 and criteria 20.
Conclusion
The different aspects of the study has showed the graphical representation of the data in Bendigo and Adelaide Bank. The important considerations has been made as per third party banking information and cash earnings.
References
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Asnicar, F., Weingart, G., Tickle, T.L., Huttenhower, C. and Segata, N., 2015. Compact graphical representation of phylogenetic data and metadata with GraPhlAn. PeerJ 3: e1029.
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Martin, D.M.A. and Bryan, G., 2016. DMAP-Graphical representation of physical and genetic map correlation. bioRxiv, p.090415.
Nomoto, K., Sakurai, Y. and Yokoo, M., 2017. Coalition Structure Generation Utilizing Graphical Representation of Partition Function Games. In AAAI (pp. 4977-4978).
Schulz, C. and Toni, F., 2015, January. Logic Programming in Assumption-Based Argumentation Revisited-Semantics and Graphical Representation. In AAAI (pp. 1569-1575).
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