Jashore University of Science and
Technology (JUST)
Department of Finance and Banking
A Report
on
“Predictive Modeling in Business Decision Making:
An Analysis on Dutch-Bangla Bank”
Course Title : Advance Business Statistics.
Course Code: FB-2201.
PREPARED BY:
PREPARED FOR:
Explorers
Al Amin Biswas
BBA 2nd year 2nd semester
Assistant Professor,
Session: 2022-23
Department of Finance and Banking
Department of Finance and Banking
Jashore University of Science and
Technology.
Jashore University of Science and
Technology
Date of Submission: 03/08/2025
Page | 1
Letter of Transmittal
3rd August, 2025
Al Amin Biswas
Assistant Professor,
Department of Finance and Banking
Jashore University of Science and Technology.
Subject: Submission of a Report on “Predictive Modeling in Business Decision Making: An
Analysis on Dutch-Bangla Bank”.
Respected Sir,
I hope this letter finds you well. We are pleased to submit our report on Predictive Modeling in
Business Decision Making: An Analysis on Dutch-Bangla Bank, as assigned for our term paper.
Following your instructions, we have maintained a formal report structure. This task provided
valuable insights into the financial statements of a company, enhancing our analytical and
practical skills. We have put our best effort into making the report effective and useful,
concentrating on relevant information. The experience gained will undoubtedly benefit my future
professional endeavors.
We would greatly appreciate your thoughts and feedback on the report. It’s our humble request to
inquire about any aspect, and we will happily respond.
Thank You.
Yours sincerely,
Explorers
BBA 2nd year 2nd semester
Session: 2022-23
Department of Finance and Banking
Jashore University of Science and Technology.
Page | 2
Group Members of ‘Explorers’
Name
Md. Jamiul Islam Sheikh
Md. Abu Talha
Md. Rahat Talukder
Fariha Islam Sifa
Sushanta Kumar Saha
S M Mahfuj
ID
222003
222007
222009
222012
222036
222039
Page | 3
Acknowledgement
At first, We express our gratitude from the core of heart to almighty Allah for enabling us to
complete our report.
We would like to show my deepest honor to our course teacher Al Amin Biswas sir for giving us
the opportunity to present our report and we are grateful to you for your precious guideline.
A report writing is very important to improve skill as a student of business faculty. We can gather
practical knowledge by making reports. This report gave us knowledge about predictive modeling
in business in details.
This report is created only for academic purpose not for any other reason.
Page | 4
Executive Summary
This term paper analyzes the financial performance of Dutch-Bangla Bank from 2014 to 2023
using statistical tools such as 3-year and 5-year moving averages, linear trendline equations,
and forecasting for the years 2024–2028. The key financial indicators assessed are Total Assets
(TA), Total Equity (TE), Total Liabilities (TL), Return on Equity (ROE), Return on Assets (ROA),
and Earnings Per Share (EPS).
The analysis shows a steady and consistent growth in Total Assets, Total Equity, and Total
Liabilities over the past decade, reflecting the bank's expansion and operational scaling. ROA has
shown gradual improvement, indicating increasing efficiency in asset utilization. In contrast, ROE
and EPS exhibit declining trends, suggesting challenges in shareholder returns and profitability.
Forecasting models predict continued growth in assets and equity but a potential further decline in
EPS and ROE if existing trends persist.
Overall, the financial trends highlight a mixed outlook, while the bank demonstrates strong growth
in size and stability, maintaining profitability and returns to shareholders remains a challenge.
Page | 5
Table of Contents
Chapter-1: ROA (Return on Assets) ............................................................................................... 7
Chapter-2: ROE (Return on Equity) ............................................................................................. 10
Chapter-3: Total Assets ................................................................................................................. 13
Chapter-4: Total Equity ................................................................................................................. 17
Chapter-5: Total Liability.............................................................................................................. 21
Chapter-6: EPS (Earnings Per Share) ........................................................................................... 24
Conclusion .................................................................................................................................... 27
References ..................................................................................................................................... 28
Page | 6
Chapter-1: ROA (Return on Assets)
MOVING AVERAGE
Year
ROA(%)
2014
2015
2016
2017
2018
2019
2020
2021
2022
2023
1.1
1.3
0.7
0.9
1.3
1.2
1.3
1.1
1.1
1.4
Three-year
moving average
Five-year moving
average
1.03
0.97
0.97
1.13
1.27
1.20
1.17
1.20
1.06
1.08
1.08
1.16
1.2
1.22
1,6
1,4
1,2
Time Series Plot of ROA%, Three-Year Moving Average, and Five-Year Moving Average
ROA%
1
0,8
0,6
0,4
0,2
0
2014
2015
2016
2017
2018
2019
2020
2021
2022
2023
Year
ROA%
3 Years moving average
5 Years moving average
Interpretation of the Graph: The graph shows the ROA% (Return on Equity) from 2014 to 2023,
along with its three-year and five-year moving averages. The blue line shows noticeable
fluctuations in ROA, with a significant dip in 2016 and a steady recovery afterward, peaking again
in 2023. The orange line represents the 3-year moving average, which smooths out short-term
volatility and reveals a gradual upward trend starting from 2017. Meanwhile, the gray 5-year
moving average line indicates a more stable and consistent improvement in ROA over the longer
term. Overall, despite some yearly instability, both moving averages suggest that the company has
been improving its asset efficiency in recent years.
Page | 7
LINER TREND EQUATION
Time
1
2
3
4
5
6
7
8
9
10
Year
2014
2015
2016
2017
2018
2019
2020
2021
2022
2023
ROA%
1.1
1.3
0.7
0.9
1.3
1.2
1.3
1.1
1.1
1.4
Trend
1.02
1.0467
1.0734
1.1001
1.1268
1.1535
1.1802
1.2069
1.2336
1.2603
ROA
y = 0,0267x + 0,9933
1,6
1,4
1,2
1
0,8
0,6
0,4
0,2
0
2014
2015
2016
2017
ROA
2018
2019
2020
2021
2022
2023
Линейная (ROA)
Interpretation of the Graph: The graph also presents ROA from 2014 to 2023, but with a dotted
linear trend line fitted to the data points. This trend line has a positive slope, represented by the
equation y = 0.0267x + 0.9933, indicating a gradual long-term increase in ROA over the period.
While the actual ROA values fluctuate yearly, the positive slope of the trend line confirms that the
overall direction is upward. This suggests that the organization’s profitability relative to its assets
has been improving incrementally, supporting a positive financial trajectory over time.
Page | 8
FORCASTING (2024-2028)
Time
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
Year
2014
2015
2016
2017
2018
2019
2020
2021
2022
2023
2024
2025
2026
2027
2028
Trend line
1.02
1.0467
1.0734
1.1001
1.1268
1.1535
1.1802
1.2069
1.2336
1.2603
1.287
1.3137
1.3404
1.3671
1.3938
Trend
1,6
y = 0,0267x + 0,9933
1,4
1,2
1
0,8
0,6
0,4
0,2
0
2014 2015 2016 2017 2018 2019 2020 2021 2022 2023 2024 2025 2026 2027 2028
Trend
Линейная (Trend)
Interpretation of the Graph: This graph shows a forecast of ROA% for the next five years based
on the trend line equation y = 0.0267x + 0.9933. The solid orange line represents the historical
trend, while the orange dotted line extends the trend into the future (years 11 to 15). The forecast
indicates a continued increase in performance if current conditions remain the same
Page | 9
Chapter-2: ROE (Return on Equity)
MOVING AVERAGE
year
2014
2015
2016
2017
2018
2019
2020
2021
2022
2023
ROE%
Three-year moving average
16.2
19.3
15.27
10.3
14.27
13.2
14.40
19.7
16.70
17.2
18.43
18.4
17.23
16.1
16.30
14.4
16.13
17.9
Five-year moving average
15.74
15.94
15.76
16.92
17.16
16.8
22
ROE%
18
14
10
2014
2015
2016
2017
2018
2019
2020
2021
2022
2023
Year
ROE%
Three-year moving average
Five-year moving average
Time Series Plot of ROE%, Three-Year Moving Average, and Five-Year Moving Average
Interpretation of the Graph: The graph illustrates ROE% (Return on Equity) trends from 2014
to 2023, along with three-year and five-year moving averages. ROE% experienced notable
fluctuations, with a sharp rise until 2015, a steep dip in 2016, and a strong rebound peaking in
2018. Afterward, ROE gradually declined through 2022, before recovering again in 2023. The
three-year moving average captures these short-term ups and downs with some lag, providing a
clearer picture of medium-term changes. In contrast, the five-year moving average smooths out
volatility and reflects a more gradual upward trend until 2020, after which it begins to flatten. The
alignment of all three lines between 2021 and 2023 suggests improved stability and more
consistent financial performance in recent years.
Page | 10
LINER TREND EQUATION
Time period
year
1
2
3
4
5
6
7
8
9
10
ROE%
2014
2015
2016
2017
2018
2019
2020
2021
2022
2023
Trend line
16.2
19.3
10.3
13.2
19.7
17.2
18.4
16.1
14.4
17.9
17.768
18.202
16.942
17.348
18.258
17.908
18.076
17.754
17.516
18.006
30
25
y = 0,14x + 15,5
ROE%
20
15
10
5
0
1
2
3
4
5
6
7
8
9
10
Time
ROE%
Trend line
Interpretation of the Graph: The graph illustrates the movement of ROE% over 10 time periods,
showing noticeable fluctuations. ROE% initially rises, dips significantly around time 3, then
recovers and peaks at time 5 before stabilizing with minor variations. The dotted trend line, with
the equation y = 0.14x + 15.5, indicates a slight upward trend, reflecting gradual improvement
in overall performance. Despite short-term volatility, the long-term direction suggests a steady
increase in profitability. This implies that the company is showing signs of consistent growth in
returns over time.
Page | 11
FORCASTING (2024-2028)
Time period
year
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
Trend line for next five years
2014
2015
2016
2017
2018
2019
2020
2021
2022
2023
2024
2025
2026
2027
2028
15.64
15.78
15.92
16.06
16.2
16.34
16.48
16.62
16.76
16.9
17.04
17.18
17.32
17.46
17.6
Forcasting for next five years
Trend line
18
y = 0,14x + 15,5
16
14
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
Time
Trend line
Forcasting for next five years
Interpretation of the Graph: The graph presents a five-year forecast of ROE% based on the
existing trend line equation y = 0.14x + 15.5. The blue line represents historical trend data up to
time 10, while the red dotted line projects values from time 11 to 15. According to the forecast,
ROE% is expected to continue rising gradually, reaching nearly 18% by time 15. The consistent
slope of the trend line indicates steady and predictable growth in profitability. This suggests that
if current conditions hold, the company's financial performance is likely to improve modestly over
the next five years.
Page | 12
Chapter-3: Total Assets
Total Asset
Definition: The total value of everything a bank owns or is owed, including cash, loans,
investments, and property, used to generate income and measure financial strength.
Why It Matters
In banking, Total Assets represent everything a bank owns or is owed—such as cash reserves, loans
out to customers, investments, and fixed assets. They’re a key measure of a bank’s scale and
capacity to earn income.
They appear on the balance sheet under the assets section and are crucial for regulatory metrics
(like capital adequacy).
Moving Average of Total Asset
Year
Total asset (In Million)
Three-year moving average
Five-year moving average
2014
214,498.5
2015
244,057.6
241,117.8
2016
264,797.4
273,587.3
276,345.8
2017
311,906.8
307,724.3
311,518.5
2018
346,468.8
349,579.2
357,178.1
2019
390,362.0
403,062.1
407,098.6
2020
472,355.4
459,039.1
455,811.9
2021
514,399.8
514,076.3
505,294.8
2022
555,473.6
554,585.5
2023
593,883.1
Trend Analysis of Total Asset with 3-Year and 5-Year Moving Averages
Page | 13
Total Asset Performance Over Time
600000
500000
400000
300000
200000
100000
0
Total asset (In Million)
Three-year moving average
Five-year moving average
Graph Interpretation: Total Asset Performance Over Time presents the trend of a company's
total assets along with its 3-year and 5-year moving averages. The blue line represents actual
asset values, which show a consistent upward movement, indicating steady growth. The orange
and green lines represent the 3-year and 5-year moving averages, respectively. Both moving
averages closely follow the actual data, with the 5-year average appearing smoother due to a
longer time frame. This suggests that the company's asset growth has been stable over time, with
no major fluctuations. The overall trend reflects positive financial health and long-term
asset expansion.
Linear Trend Equation
Total asset (In Million)
700 000,0
y = 44652x + 145233
600 000,0
500 000,0
400 000,0
300 000,0
200 000,0
100 000,0
0,0
2014
2015
2016
2017
2018
2019
2020
2021
2022
2023
1
2
3
4
5
6
7
8
9
10
Page | 14
Forecasting (2024-2028)
Time period
Year
Trend line
1
2014
189885
2
2015
234537
3
2016
279189
4
2017
323841
5
2018
368493
6
2019
413145
7
2020
457797
8
2021
502449
9
2022
547101
10
2023
591753
11
2024
636405
12
2025
681057
13
2026
725709
14
2027
770361
15
2028
815013
Forecasting for next five years
900 000,0
800 000,0
700 000,0
600 000,0
500 000,0
400 000,0
300 000,0
200 000,0
100 000,0
0,0
2014
2015
2016
2017
2018
2019
2020
2021
2022
2023
2024
2025
2026
2027
2028
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
Total asset (In Million)
Trend line
Page | 15
Graph Interpretation: Forecasting for Next Five Years shows a steady increase in total assets
from 2014 to 2023, with a clear upward trend. The red trend line closely follows the actual data,
indicating stable and consistent growth. From 2024 to 2028, the forecast suggests continued asset
growth, reaching nearly 700,000 million by 2028. Overall, the graph reflects a strong and positive
financial outlook for the coming years.
Page | 16
Chapter-4: Total Equity
Total Equity
Total equity is the total value of assets that belong to shareholders after all debts are paid. It
reflects the net worth of a company. This includes share capital, retained earnings, and reserves.
It shows the financial strength of the business.
Moving Average of Total Equity
Moving Average is a statistical method that calculates the average of a data set over a specific
number of periods to smooth out short-term fluctuations and reveal long-term trends.
Year
Total Equity
Three-year moving average
Five-year moving average
2014
14517.4
2015
16574.3
16254.8
2016
17672.7
17909.73333
18266.52
2017
19482.2
20080.3
20851.7
2018
23086
23337.16667
23988.18
2019
27443.3
27595.33333
27846.92
2020
32256.7
32222.13333
32278.24
2021
36966.4
36953.96667
37295.6
2022
41638.8
42259.33333
2023
48172.8
Page | 17
Trend Analysis of Total Equity with 3-Year and 5-Year Moving
Averages (2014–2023)
Total Equity Performance Over Time
60000
50000
40000
30000
20000
10000
0
2014
2015
2016
2017
2018
2019
2020
2021
2022
2023
1
2
3
4
5
6
7
8
9
10
Total Equity
Three-year moving average
Five-year moving average
Graph Interpretation: The graph shows a steady increase in Dutch-Bangla Bank’s total equity
from 2014 to 2023. Total equity grew from around 16,000 million to over 48,000 million Taka.
The 3-year moving average smooths short-term changes, confirming upward growth. The 5-year
moving average shows an even more stable long-term trend. Both averages reflect consistent and
sustainable financial performance. This indicates strong equity growth and solid financial health.
Page | 18
LINER TREND EQUATION
LINER TREND EQUATION
60000
y = 3742.4x + 7197.7
50000
40000
30000
20000
10000
0
2014
2015
2016
2017
2018
2019
2020
2021
2022
2023
1
2
3
4
5
6
7
8
9
10
FORCASTING (2024-2028)
Time period
Year
Trend line
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
2014
2015
2016
2017
2018
2019
2020
2021
2022
2023
2024
2025
2026
2027
2028
10940.1
14682.5
18424.9
22167.3
25909.7
29652.1
33394.5
37136.9
40879.3
44621.7
48364.1
52106.5
55848.9
59591.3
63333.7
Page | 19
Forecasting for next five years
70000
60000
50000
40000
30000
20000
10000
0
2014
2015
2016
2017
2018
2019
2020
2021
2022
2023
2024
2025
2026
2027
2028
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
Total Equity
Trend line
Graph Interpretation: The graph titled “Forecasting for next five years” shows the trend of Total
Equity from 2014 to 2028.
The graph compares two curves:



Blue line represents Total Equity (actual historical data) up to 2023.
Orange line represents the Trend line (forecasted values).
Green line continues the forecasted values for 2024–2028 based on the trend equation.
The trend shows a steady upward linear growth from 2014 (10,940.1) to 2028 (63,333.7). There
is a close alignment between Total Equity and the Trend line from 2014–2023. The forecast for
2024 to 2028 shows a continued positive linear growth, indicating financial strength or
increasing equity.
Decision:
Positive financial outlook: The increasing trend suggests strong and stable growth in equity.
Page | 20
Chapter-5: Total Liability
Strategic planning: The upward trend can support decisions like expansion, new product
Moving Average
launches, or securing funding.
Total Liabilites(BDT in Millions)
Year
2014
2015
2016
2017
2018
2019
2020
2021
2022
2023
Total Liabilities
168762
206192
273383
325433
364000
390140
472355
514400
555474
593883
Three Year Moving Average Five Year Moving Average
216112
268336
320939
359858
408832
458965
514076
554586
267554
311830
365062
413266
459274
505250
Moving Average
700000
600000
500000
400000
300000
200000
100000
0
2014
2015
2016
2017
2018
2019
2020
2021
2022
2023
Years
Total Liabilities
Three Year Moving Average
Five Year Moving Average
This graph and table smooth out the year-to-year fluctuations in Dutch Bangla Bank's total liabilities to reveal
the underlying long-term trend. The actual liabilities, which rose from 168,762 million BDT in 2014 to 593,883
million BDT in 2023, are plotted alongside a three-year and a five-year moving average.Three-Year Moving
Average: This average is calculated over a three-year period to show a medium-term trend. It is more responsive
to recent changes in total liabilities. For example, the value of 216,112 million BDT for 2015 is the average of
the liabilities from 2014, 2015, and 2016. This average steadily rises from 2015 to 554,586 million BDT by
2022, confirming a consistent upward trajectory.Five-Year Moving Average: This average is calculated over a
five-year period to provide a clearer, more stable view of the long-term trend. It is less affected by single-year
fluctuations than the three-year average. As shown in the table, the five-year moving average begins with a value
| 21 million
of 2667554 million BDT in 2016 (the average of 2014-2018) and continues to rise smoothly toPage
505,259
BDT by 2021. The five-year moving average provides the smoothest line, clearly confirming a stable and
continuous upward trend over the decade, without any signs of a decline.
Linear Trend Equation
Time
Code
1
2
3
4
5
6
7
8
9
10
Year
Total Liabilities
Trend
2014
2015
2016
2017
2018
2019
2020
2021
2022
2023
168762
206192
273383
325433
364000
390140
472355
514400
555474
593883
169774
217914
266054
314194
362334
410474
458614
506754
554894
603034
y = 48140x + 121634
Trend Equation
700000
600000
500000
400000
300000
200000
100000
0
2014
2015
2016
Time Code
2017
2018
2019
Total Liabilities
2020
2021
2022
Линейная (Total Liabilities)
2023
During the initial years (2014–2016), actual total liabilities remained close to the trend values. In 2014, the actual
figure (168,762) nearly matched the trend (169,774), showing a good fit. While liabilities in 2015 (206,192) fell
slightly below the predicted (217,914), they exceeded the trend in 2016 (273,383 vs. 266,054). In the mid-years
(2017–2019), the actual and trend values remained moderately aligned. For instance, in 2018, liabilities were
364,000 compared to the trend of 362,334, though 2019 showed a slight dip below the trend. From 2020 onward,
actual liabilities consistently exceeded or closely followed the trend line, indicating accelerated growth. In 2023,
actual liabilities reached 593,883 against a trend estimate of 603,034.
The linear trend equation y = 48140x+121634 suggests an average annual increase of 48,140 units in liabilities, with
the base level starting at 121,634. This steady upward movement reflects growing financial obligations over the
Page | 22
years.
Forecasting (2024-2028)
Total Liabilites(BDT in Millions)
Time Code
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
Year
2014
2015
2016
2017
2018
2019
2020
2021
2022
2023
2024
2025
2026
2027
2028
Trend
169774
217914
266054
314194
362334
410474
458614
506754
554894
603034
651174
699314
747454
795594
843734
Forecasting for next 5 years
y = 48140x + 121634
900000
800000
700000
600000
500000
400000
300000
200000
100000
0
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
Time Code Years
Time Code
Forecast
Trend
The forecasting graph visually extends the linear growth trend of total liabilities beyond 2023. The dotted line
indicates the predicted values for the next five years, showing a steady upward trajectory. The slope remains
consistent with the historical trend, projecting an average annual increase of 48,140 million BDT.
This indicates that if the current financial pattern continues, the organization’s total liabilities are expected to
cross 800,000 million BDT by 2027, reaching 843,734 million BDT by 2028.
Page | 23
Chapter-6: EPS (Earnings Per Share)
MOVING AVERAGE
year
2014
2015
2016
2017
2018
2019
2020
2021
2022
2023
EPS(TK)
11
15.1
8.9
12.3
21
8.7
10
8.8
8.14
10.72
Three-year moving average
Five-year moving average
11.67
12.10
14.07
14.00
13.23
9.17
8.98
9.22
13.66
13.2
12.18
12.16
11.328
9.272
Moving Average
25
EPS(TK)
20
15
10
5
0
2014
2015
2016
2017
2018
2019
2020
2021
2022
2023
Year
EPS(TK)
Three-year moving average
Five-year moving average
Interpretation of the Graph: The graph and table show the actual EPS (Earnings Per Share) of
Dutch Bangla Bank from 2014 to 2023 along with the three-year and five-year moving
averages to smooth out short-term fluctuations. The actual EPS line shows sharp ups and downs,
with a peak in 2018 (21 TK) and noticeable drops in 2016 and 2019. The three-year moving
average (orange line) follows the actual EPS more closely and responds faster to changes, while
the five-year moving average (gray line) is smoother and shows a more stable long-term trend.
Both moving averages confirm a rise until 2018, followed by a gradual decline. Overall, the
moving averages help to identify the general trend of EPS, reducing the noise from year-to-year
changes.
Page | 24
LINER TREND EQUATION
Time Code
1
2
3
4
5
6
7
8
9
10
Year
2014
2015
2016
2017
2018
2019
2020
2021
2022
2023
EPS(TK)
11
15.1
8.9
12.3
21
8.7
10
8.8
8.14
10.72
Trend Line
13.401
12.971
12.541
12.111
11.682
11.252
10.822
10.392
9.962
9.532
Trend Equation
25
EPS(TK)
20
y = -0,4299x + 13,831
15
10
5
0
2014
2015
2016
2017
2018
2019
2020
2021
2022
2023
1
2
3
4
5
6
7
8
9
10
Time Code
Year
EPS(TK)
Trend Line
Interpretation of the Graph: The graph and table show the Earnings Per Share (EPS) of Dutch
Bangla Bank from 2014 to 2023, with actual EPS values and a trend line indicating the overall
direction. The EPS fluctuated during this period, reaching a peak of 21 TK in 2018 and a low of
8.7 TK in 2019. The trend line, represented by the equation y = -0.4299x + 13.831, shows a gradual
downward trend, suggesting that EPS has been decreasing by about 0.43 TK each year on
average. Although some years performed better or worse than the trend, the overall pattern
indicates a slow decline in EPS over time.
Page | 25
FORCASTING (2024-2028)
Time Code
Year
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
2014
2015
2016
2017
2018
2019
2020
2021
2022
2023
2024
2025
2026
2027
2028
Expected
EPS(TK)
13.401
12.971
12.541
12.111
11.682
11.252
10.822
10.392
9.962
9.532
9.102
8.672
8.242
7.812
7.383
Expected SPS(TK)
Forecasting for next five years
14,0
13,0
12,0
11,0
10,0
9,0
8,0
7,0
6,0
5,0
y = -0,4299x + 13,831
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
Time Code
Expected EPS(TK)
Forecasting
Interpretation of the Graph: The graph and table show the historical and projected Earnings
Per Share (EPS) of Dutch Bangla Bank from 2014 to 2028. The data reveals a steady decline
in EPS over the years, starting at 13.401 in 2014 and dropping to 9.532 by 2023. Based on the
linear trend equation, the forecast for the next five years (2024–2028) shows a continued
decrease, with EPS expected to fall to 7.383 by 2028. This consistent downward trend suggests a
long-term weakening in the bank’s earnings performance.
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Conclusion
The study concludes that Dutch-Bangla Bank has experienced robust growth in terms of assets and
equity from 2014 to 2023. However, despite these positive developments, key profitability
indicators such as ROE and EPS have declined, signaling the need for strategic focus on improving
financial performance. Moving average and trendline analyses provide clear insights into longterm patterns, while the five-year forecasting helps anticipate future challenges. To ensure
sustainable growth, the bank should aim to enhance operational efficiency, control costs, and
develop strategies to improve shareholder value.
Page | 27
References
1. Dutch-Bangla Bank PLC. (n.d.). Dutch-Bangla Bank PLC. Retrieved August 2, 2025, from
https://www.dutchbanglabank.com/
2. Dutch-Bangla Bank PLC. (2023). Annual report 2023. Dutch-Bangla Bank PLC. Retrieved
from
https://www.dutchbanglabank.com/investor-relations/Annual-Report-2023/Annual-Report-20
23.pdf
3. Dutch-Bangla Bank PLC. (2015). Annual report 2015. Dutch-Bangla Bank PLC. Retrieved
from
https://www.dutchbanglabank.com/investor-relations/Annual-Report-2015/Annual-Report-20
15.pdf
Page | 28