Banking in Emerging Economies - Madjid Tavana in Emerging Economies ... analysis and to consult experts with specific knowledge of bank expansion ... Algeria); Asia (China, India,

© 2014, CMK Inc. or its subsidiaries. All rights reserved

Banking in Emerging Economies

Group Project: Big Data and Decision Analytics

Page 2 © CMK Konsulting Inc.

Contents

Abstract .......................................................................................................................................... 3

Problem Statement ....................................................................................................................... 4

Additional Information ................................................................................................................................. 5

Background Information .............................................................................................................................. 5

Specific Question ........................................................................................................................................... 5

How does a bank do this analysis? ............................................................................................. 6

What factors are they looking at? .............................................................................................. 8

What factors do they want to avoid?......................................................................................... 9

Method ........................................................................................................................................... 10

Filter ............................................................................................................................................................... 10

Organize ........................................................................................................................................................ 10

Norm ................................................................................................................................................................ 12

Decide .............................................................................................................................................................. 13

Analyse ........................................................................................................................................................... 13

Data/ Decide ................................................................................................................................. 14

Africa .............................................................................................................................................................. 18

Asia ................................................................................................................................................................. 19

Europe ............................................................................................................................................................ 19

Latin America .............................................................................................................................................. 20

Analysis ....................................................................................................................................... 20

All countries – Analysed Together .......................................................................................................... 22

Asia ................................................................................................................................................................. 23

Europe ............................................................................................................................................................ 23

Latin America .............................................................................................................................................. 24

Africa ............................................................................................................................................................. 24

Opportunities for Further Analysis ........................................................................................................ 25

Sources ......................................................................................................................................... 26

Legal Information ........................................................................................................................ 27

ABSTRACT

ABSTRACT


Abstract

The CMK Konsulting Company was engaged by the customer, Dr. Tavana, to

evaluate countries for potential expansion. The conclusion is that five

countries are recommended as potential candidates. These are Estonia,

Czech Republic, Poland, Mexico and Slovenia. These five countries are

relatively equally distributed and the customer will face individual

challenges in each. No particular country is a specific favourite.

Additionally, China represents a special case. The extremely strong

economy may outweigh some of the additional challenges that would be

faced expanding into China. The customer is advised to make further

analysis and to consult experts with specific knowledge of bank expansion

in China. CMK would look forward to preforming this analysis in a separate

contract.

The analysis was done with the following methods. First, the FONDA

method was used by filtering the data, organizing it, followed by

normalizing the data. The decisions were made and finally analysed. The

detailed analysis is described in this report and is available in a separate

excel file.

Graphically and tabular representations of the key data are included in this

report in the decision and analysis chapters.

Figure 1 Beijing (source:china.com)

PROBLEM STATEMENT

PROBLEM STATEMENT


Problem Statement

The customer, Dr. Tavana, prepared the following problem statement:

The determinants for the internationalization of banking are based on

country characteristics and market dynamics and bank-specific advantages.

Primarily the country characteristics consist of barriers to entry to provide

services, the type of activities allowed and the type of investment allowed,

as well as, regulations on capital flows and taxation and repatriation of

profits, or indeed, tax benefits offered by a government to attract foreign

banks to invest directly to encourage spill-over effects in the industry. The

size of the market for banking products and specifically the product

markets that are targeted and the potential growth of these are other

factors. In terms of the foreign financial market dynamics the potential

performance and profitability depends on the interaction and rivalry among

existing banks in the market, the number of these their nationality and their

size distribution, that is whether it a concentrated oligopolistic market with

a few large banks and some other smaller banks, or it is a highly

fragmented market. Different product markets and customer segments,

that is, individual or corporate customers, may have different levels of

rivalry and margins and hence profitability is different for each type. The

more a bank has distinctive competencies the more that they may be

transferred abroad. By definition when they have distinctive there must be

some competitive advantage for the bank.

The decision to enter an emerging economy by a multinational bank is a

very important one, as many factors need to be considered. We consider

the following 24 countries in 4 continents: Africa (Tunisia, South Africa,

Morocco, Algeria); Asia (China, India, Vietnam); Europe (Bulgaria, Czech

Republic, Estonia, Hungary, Latvia, Lithuania, Poland, Romania, Slovakia,

Slovenia, Turkey, Ukraine, Georgia, Russia); and Latin America (Argentina,

Brazil, Mexico). PESTEL analysis (political, economic, social, technological,

environmental, and legal analysis) is used to initially collect over 500

factors grouped into the political, economic, social, technological,

environmental, and legal categories. We then use FONDA to Filter,

Organize, Normalize, Decide, and Analyse the data. A minimum of 200

(Note: the customer changed the requirement to 400) factors for the above

mentioned 30 countries must be used in the final data set. More

information is available at: http://tavana.us/project/.

Figure 2 Mexico City (source:wikipedia.org)

PROBLEM STATEMENT

ADDITIONAL INFORMATION


Additional Information

Furthermore, the following background information was provided to the

CMK team as input to the problem statement.

Background Information

The following data files were provided:

These files were collected by other consulting groups that have worked on

similar issues in the past and were provided by the customer in order to

reduce the team’s efforts and overall billable hours for this project. This is

reflected in a reduction to the offered costs. Please see the commercial

documentation.

Specific Question

The customer requested that the CMK specifically address the following

questions in their report:

Write about how a bank does this analysis?

What factors are they looking at?

What factors do they want to avoid?

a.xlsx b.xlsx c.xlsx d.xlsx e.xlsx

Figure 3 Prague (Wikipedia.org)

HOW DOES A BANK DO THIS ANALYSIS?



How does a bank do this analysis?

Before a bank analyses which countries to expand into, they would have to

undertake several steps.

First, the bank would make the decision to expand abroad.

Then they would evaluate in which countries to expand to and how they

would expand.

They would create an expansion plan (Kahn p. 3) and…

Finally, the bank would execute the plan, evaluating progress continually.

The decision to expand abroad could be motivated by many factors:

The bank may want to provide services to local customers that do

business in the new country. An example of this may be that a Turkish

Bank could possibly want to expand into Germany. Germany is Turkey’s

largest trading partner and it is quite plausible that a Turkish Bank may

want to offer Turkish exporters or importers the possibility of complete

services for international transactions.

The bank may want to protect itself against being dependant on a

specific country’s economy. A Bank in a Euro country may want to invest

abroad in a non-Euro market in order to have a chance for growth when

the Euro-country’s growth is stagnant.

The bank may want to grow and may feel that the local market is

saturated and their growth is limited. An example is that a bank which is

highly skilled with specific products, such as an American bank that

supports tech start-ups, may want to move abroad into a foreign country

known to have strong Tech start-ups. An American Bank may be sick of

the competition in Silicon Valley and may choose to expand to India or

Israel in order to obtain new customers where they have reduced

competition.

The bank may simply not have faith that its current market will

constantly be strong (Kahn p. 4).

Figure 4 Analysis

(source: www.ultraoilforpets.com)




Banks may have been providing services for foreign clients through their

national offices and may have decided that this was insufficient (Buch p.

5). Either they were losing clients who wanted local offices, or they saw

the potential for expansion. Perhaps through this route, the banks

already knew the foreign market and could more easily make the

decision to expand.

The banks may simply see the growth of global banking and may have

decided that if the bank itself does not grow and become global, it will

lose out to the global banks. These banks may have no other motivation

than to keep up with the trend of globalization.

The bank would then prepare to decide which country to expand to.

Based on the reasons to expand internationally, this decision may

involve evaluating many factors. It also may be very simple and limited a

go / nogo decision for a specific country.

If many countries are going to be evaluated, the bank may choose to do

this in house, or they may choose to hire a consulting company, such as

CMK Konsulting, to present this work for them. The consulting company

will interview the bank’s management to understand the goals of the

bank and then prepare a report (such as this report) and make a series

of recommendations to the bank – for countries which ideally meet the

bank’s needs.

Then, after (and if) the bank has chosen, they will create an expansion

plan to enter the new country. This plan will describe a series of

milestones necessary to expand. These will range across the board from

simply acquiring offices and hiring people, to completing the necessary

licencing, and finally to opening and beginning business.

The consulting company may also offer additional services to assist the

bank in executing the expansion plan. These can range from continuing

to act in an advisory role to more extensive services such as making

local connections, finding office locations, assisting in hiring and bringing

expats to the new market.

Finally, the bank will evaluate the success of the action plan and

constantly monitor KPIs to determine if the expansion is successful or

not.

Figure 5 Algiers

(source tourist-destination.com)

WHAT FACTORS ARE THEY LOOKING AT?

WHAT FACTORS ARE THEY LOOKING AT?


What factors are they looking at?

Banks look at many factors before deciding upon expansion. According to

Bhattacharya, some of these factors include:

Following existing customers: Banks have a significant advantage

entering new markets if they already have customers in the new country.

Bhattacharya also states that banks have significant savings if they

have, for example, already evaluated customers for creditworthiness and

do not need to repeat this work. Bhattacharya notes, surprisingly, that

banks do not necessarily enter markets in line with international trade.

Poor performing inefficient local banks are also a target for international

banks that would like to expand. It is likely that a national banking

industry has reached some kind of complacency. When the market is

opened, international banks are more efficient and can quickly profit and

expand.

Local banks can be targeted when their stock earnings are low,

especially when foreign currency is stronger.

In some cases, countries open up their markets by reducing national

regulation. This is very attractive to banks as they often face difficult

regulation.

Banks seek to diversify risk by expanding internationally. Bhattacharya

shows evidence that even though banks may face lower earning after

expanding abroad, they reduce their risk. For many banks, this may be a

conscious decision.

Banks may also expand, if they are doing international business anyway.

Banks have lower costs monitoring the international business if they

have local businesses and local know-how.

Figure 6 Decision Factors

(source: footage.shutterstock.com)

WHAT FACTORS DO THEY WANT TO AVOID?

WHAT FACTORS DO THEY WANT TO AVOID?


What factors do they want to avoid?

In 2013, Ernst and Young prepared a publication titled: Banking in emerging

markets seizing opportunities overcoming challenges. In this publication,

E&Y interviewed bankers active in ten rapidly growing markets about their

experiences. This publication suggests factors that banks want to avoid in

emerging markets:

Markets that have already transitions: Banks are most interested in

experiencing a period of rapid growth. There is much less potential for the

banks after the rapid growth is completed. Therefore, the banks want to

avoid new markets that have had very strong growth which has slowed

down.

Political Upheaval: The bank expansion can be severely delayed or

compromised in periods of political upheaval. The current unrest in the

Ukraine and in Syria would make both of these countries extremely

unattractive for expansion. The remaining Arab Spring countries such as

Egypt reflect similar political uncertainty.

Social Upheaval: Periods of social upheaval can be just as disruptive as

political upheaval, and often happens concurrently. E&Y quote bankers who

are concerned with investing in Nigeria due to kidnapping risk and

vandalism, as well as Columbia where trade unions have disrupted industrial

activities (such as coal and coffee).

Investment in Infrastructure: Banks doing business in emerging markets

spoke about the concern that governments were not investing in

infrastructure improvements. The banks believe strongly, that without

these investments, the economies will not improve and the expected

growth would not come.

Ernst and Young report that their sources state that they are concerned

about margin compression, increased competition, increased costs and

changes to regulations.

Margin compression: Banks express concern that national central banks are

reducing interest rates to stimulate the economy. This puts pressure across

the board to lower interest rates which reduce, in turn, the bank’s profit.

Figure 7 Factors to Avoid

(source: bizblogs.fullerton.edu)

WHAT FACTORS DO THEY WANT TO AVOID? / METHOD

FILTER / ORGANIZE


Increased competition: The international banks expanding in emerging

markets are not the only ones, and other foreign banks (both global banks

and regional banks from neighbouring countries) increase competition for

customers and drive prices down.

Regulatory changes: More and more regulations are increasing the cost of

operations. These regulations are not only international, but national as

well.

Method

The customer requested that CMK Konsulting team perform their analysis

on the provided data set using the FONDA method. The steps of the FONDA

method are described in the following sections.

Filter

First, the CMK filtered the provided data sets. The purpose of this was to

bring the data set in a proper form to effectively organize it. The filtering

was done with the following. All the variables were checked and labelled:

‘1’ Necessary to include in the final analysis.

‘2’ To be discussed by CMK Konsulting and can possibly be included in

the final analysis

‘3’ Not included The data set shall not be included in the analysis.

This filtering step ended up with approximately 375 Necessary and

approximately 50 to be discussed variables.

These 425 variables were checked again for duplicates and reduced to a

final number of approximately 400 (as per the customer request).

Organize

The next step of the FONDA method is to organize the data. This was done

by dividing the data into positive attributes and negative attributes and

assigning each attribute a PESTEL category.

Figure 8 Method (source:

http://www.aaindustrial.com.au/)

METHOD

ORGANIZE


Positive and Negative Attributes: Each of the factors was checked to

determine if it could be interpreted as pro- or contra- indication for a bank

to expand into a country. For example, GDP is considered a pro- indication

to expand into a country for the reason that a higher GDP indicates that the

economy is better and there is more capital available for the bank to

provide services for. The corruption index is an example of a contra-

indication. This is because a country with a high level of corruption may be

extremely dangerous, expensive (especially with respect to hidden costs),

may violate bank policy and would be highly risky. It should be noted that

there are some attributes which could be interpreted as either positive or

negative – one example of this is “import duties,” which could be perceived

as a threat or opportunity. To properly account for these borderline factors,

a holistic approach is required, looking at the totality of the data and

making educated judgments. Furthermore, some factors may have quite

different effects in different countries, and for this reason it is important to

consult local experts before making any final decisions about expanding

into a new territory.

PESTEL Category: Each data factor was then assigned to one of the six

PESTEL categories. Godfrey provides the diagram below and describes the

six PESTLE categories on this blog.

Figure 10 Pestel Catagories

(Godfrey Blog entry)

Figure 9 Marrakesh (source: telegraph.co.uk)

METHOD

ORGANIZE / NORMALIZE


The following descriptions of the PESTEL categories are described by

Godrey as well:

Political – Category for issues related to the political state in the proposed

country. Relevant to the general political situation, to import/exports and

political orientation with respect to support (or hindrance) to specific fields.

Economic – Obviously, for a bank, the overall economic situation and all

factors related to it are extremely important. This includes, but isn’t limited

to: current and projected stock and bond performance, bank and bond

interest rates, economic indicators, specific performance in important

industries, and many more.

Social – Everything in the social category describes the overall data of the

population. How and what they are doing, who they are, important changes

and issues in which the social state of the people are similar and different

to other countries.

Technological – What technology is available in the country being evaluated

and what are the general technological trends. This applies to all branches

of technology: personal computing, computer use, industrial use of

technology etc.

Environmental – This applies both to the overall environmental quality as

well as to the climatic conditions.

Legal – for issues related to legal issues in the proposed country. The legal

issues may pertain to general law, import/export law, legal support (or

hindrance) to specific fields, standards and regulations as well as the

overall political situation.

Norm

Figure 12 Normed Data (source: www.alwyncosgrove.com)

Figure 11 Hanoi (source: dilemma-x.net)

METHOD

NORMALIZE / DECIDE / ANALYSE


The data categories collected are in many different units. In order to

evaluate them together, these data are all normalized to the same scale –

from 0 to 1 (or 0% to 100%). This method allows us to consider data with

different units (and different scales) together. An example of different data

types would be ‘population’ and GDP. Both of these values are measured in

different units (number of people) compared with (currency). The ranges

are different as well. By norming or scaling all of the categories from 0 to 1

(or 0% to 100%) we can use these values together.

Decide

The data is presented with several different views for all countries together

as well as in four global regions.

Africa: Tunisia, Morocco, South Africa, Algeria

Asia: China, India, Vietnam

Europe: Bulgaria, Czech Republic, Estonia, Hungary, Latvia, Lithuania,

Poland, Romania, Slovakia, Slovenia, Turkey, Ukraine, Russia, Georgia

Latin America: Argentina, Brazil, Mexico

Analyse

The data is then analysed and several conclusions are presented. For each

region countries are presented as recommendations and indicated to avoid.

Figure 13 Decision (source: litemind.com)

DATA/ DECIDE

DATA/ DECIDE


Data/ Decide

The data for all countries was analysed according to the method described

above in the following steps.

All the data was sorted into positive and negative factors coded red and

called threats and coded green and called opportunities.

Examples of positive factors are: Annual Growth Rate Industrial Value

Added, Business > total registered (#) by country, Income Receipts.

Examples of negative factors are: crime as a % of population, Firing

costs (weeks of wages), Closing a Business

Following this, the data was normalized so that the ranges of the factors

were between 0 and 1. This was done using the formula:

Normed Value =

Figure 14 Screenshot of data sorted into positive and negative factors (see excel file worksheet Transposed)

Value – Minimum Value

Maximum Value – Minimum Value

DATA/ DECIDE

DATA/ DECIDE


The results after normalization appeared as follows in the Excel file:

Next, the threats and opportunities were averaged (threats averaged

separately to opportunities), and the Euclidean distance was calculated

using the following formula:

𝑑 = √(1 − 𝑜)2 + (0 − 𝑡)2

where o is the average opportunity value for a country, and t is the average

threat value for a country.

The ranked results were as follows:

Figure 15 Screenshot of normed data (see excel file worksheet Normalized)

Figure 16 Screenshot of averaged and ranked data

(see excel file worksheet Averaged & Ranked)

DATA/ DECIDE

DATA/ DECIDE


The data was then sorted by rank:

Figure 17 Screenshot of averaged and ranked data (see excel file worksheet Sorted By Rank) (see

excel file worksheet Averaged & Ranked)

0.000

0.100

0.200

0.300

0.400

0.500

0.600

0.700

0.800

0.900

AlgeriaArgentina

Brazil

Bulgaria

China

Czech Republic

Estonia

Georgia

Hungary

India

Latvia

LithuaniaMexico

Morocco

Poland

Romania

Russia

Slovakia

Slovenia

S. Africa

Tunisia

Turkey

Ukraine

Vietnam

Figure 18 Screenshot of radar chart

(see excel file worksheet Radar

chart)

DATA/ DECIDE

DATA/ DECIDE


A PESTEL analysis was also done and the PESTEL values were ranked.

Figure 19 Screenshot of PESTEL data (see excel file worksheet PESEL)

DATA/ DECIDE

DATA/ DECIDE / AFRICA


Finally, the data was plotted on a scatter chart. Note that the individual

countries are not labelled. An ‘exploded’ version of this chart is

presented in the analysis section.

Africa

The ranks of the African countries are listed here:

Country Continent Avg. Opportunity

Score

Avg. Threat

Score

Euclidean

Distance Rank

Tunisia Africa 0.32 0.32 0.750 20

S. Africa Africa 0.36 0.43 0.770 21

Morocco Africa 0.32 0.38 0.776 22

Algeria Africa 0.30 0.43 0.822 24

Figure 20: Screenshot of scatter plot

(see excel file worksheet Scatter plot II)

DATA/ DECIDE

ASIA / EUROPE


Asia

The ranks of the Asian countries are listed here:


Score

Avg. Threat

Score

Euclidean

Distance Rank

China Asia 0.57 0.38 0.571 1

India Asia 0.45 0.42 0.694 9

Vietnam Asia 0.34 0.32 0.730 17

Europe

The ranks of the European countries are listed here:


Score

Avg. Threat

Score

Euclidean

Distance Rank

Czech Rep. Europe 0.43 0.32 0.656 2

Estonia Europe 0.40 0.30 0.669 3

Poland Europe 0.40 0.31 0.679 5

Slovenia Europe 0.41 0.34 0.680 6

Slovakia Europe 0.38 0.28 0.680 7

Lithuania Europe 0.36 0.25 0.688 8

Latvia Europe 0.36 0.28 0.696 10

Hungary Europe 0.39 0.34 0.702 11

Bulgaria Europe 0.35 0.29 0.710 12

Georgia Europe 0.35 0.29 0.712 13

Russia Europe 0.41 0.41 0.716 15

Romania Europe 0.32 0.28 0.731 18

Turkey Europe 0.38 0.38 0.731 19

Ukraine Europe 0.33 0.39 0.779 23

Figure 21 Argentina City

(source: wallsave.com)

DATA/ DECIDE / ANALYSIS

LATIN AMERICA / ANALYSIS


Latin America

The ranks of the Latin American countries are listed here:


Score

Avg. Threat

Score

Euclidean

Distance Rank

Mexico Latin America 0.41 0.32 0.673 4

Brazil Latin America 0.45 0.46 0.716 14

Argentina Latin America 0.39 0.37 0.717 16

Analysis

The countries are presented together on the scatter chart on the following

page. This chart contains two axis to show both the level of opportunities as

well as the level of threats.

y axis – levels of threats

x axis – levels of opportunities

The chart is further divided into four quadrants with specific labels:

Abandon Ship: Low Opportunities and High Threats

Three Sheets to the Wind: Low Opportunities and Low Threats

Loose Cannons: High Opportunities and High Threats

Smooth Sailing: High Opportunities and Low Threats

Figure 22 Bratislava (source: grayline.com)

ANALYSIS

ANALYSIS


0.20

0.25

0.30

0.35

0.40

0.45

0.50

0.55

0.60

0.20 0.25 0.30 0.35 0.40 0.45 0.50 0.55 0.60

Abandon Ship

Three Sheets to

the Wind Smooth Sailing

Loose Cannon

S. Africa Algeria

Ukraine

Morocco

China

Brazil

Turkey

Argentina

Tunisia

Romania

Vietnam

Bulgaria Georgia

Latvia Slovakia

Lithuania

Estonia

Poland

Mexico Czech Rep.

India Russia

Hungary Slovenia

Average

Average

Africa Europe Asia Latin America

Page 21 © CMK KKonsulting Inc.

ANALYSIS

ALL COUNTRIES – ANALYSED TOGETHER


All countries – Analysed Together

Recommendations:

Countries recommended for bank expansion: The results clearly

recommend expansion in four countries:

Estonia

Czech Republic

Poland

Mexico

Slovenia

Hungary

It is interesting that these countries are ranked two to four. The number

one ranked country is China, which has a very high positive ranking, but too

high level of threats to fall into the ‘smooth sailing quadrant.’

Countries recommended avoiding:

Basically, all countries that fall into the ‘Abandon Ship’ quadrant should be

avoided. These are:

S. Africa

Morocco

Ukraine

Algeria

Turkey

These countries have a low level of opportunities and a high level of

threats.

Figure 23 Kiew (source:

skyscrapercity.com)

ANALYSIS

ASIA / EUROPE


Asia

The recommended countries for expansion in Asia are maybe China and

Vietnam. Neither country is in a positive quadrant. China has a very high

level of opportunities, but a high level of threats as well. Vietnam has low

opportunities, but low threats as well.

The PESTEL analysis shows that China is especially strong, as is well known,

in economy and social rankings. This would be extremely beneficial for

expansion, however it has strong negative rankings as well in

environmental and legal, the legal would make the expansion extremely

challenging. For Vietnam the PESTEL analysis does not show any strong

rankings in the positive area and indicates a very weak economy which

would be a challenge for expansion.

The countries with a low ranking that should be avoided in Asia are India

which has a much higher level of threats, while still having opportunities.

The PESTEL analysis for India is extremely interesting with very high

positive and negative rankings almost across the board. Positive high

ranking are for everything except for technology and negative rankings are

extremely high for everything but technology and environmental. This

would make India a huge challenge for a Bank.

Europe

The recommended countries for expansion in Europe are Hungary, Poland,

Estonia and Czech Republic. All are countries with high opportunities and

low threats.

The PESTEL analysis shows that Hungary is strong in technology and legal.

Hungary doesn’t have strong weaknesses, but technology and

environmental. For Poland, moderately strong PESTEL values are across

the board with the highest ranking in social. The most dangerous negative

rankings are technology and environmental. The Czech Republic shows the

highest values in technology and legal and negative values only in

environmental. All of these countries can be strongly recommended.

The countries with a low ranking that should be avoided in Europe are the

Ukraine which not only has a high level of threats and low opportunities, but

now is in the middle of a major crisis.

The PESTEL analysis of the Ukraine backs up the current political instability

with political, economic, social and legal. Obviously, the Ukraine should be

avoided until some stability is reached.

Figure 24 Warsaw (source: immonet.at)

ANALYSIS

LATIN AMERICA / AFRICA


Latin America

The recommended countries for expansion in Latin America are Mexico

which has a high level of opportunities and low threats.

The PESTEL analysis for Mexico shows extremely high ranking for political

and no strong negative rankings.

The countries with a low ranking that should be avoided in Latin America

are Brazil which, in spite of hosting the World Cup, has a high level of

threats while still have some opportunities.

The PESTEL analysis for Brazil shows extremely high ranking for Political,

Economic and Social but many high negative rankings including Political

and Legal. Brazil has some potential, but there would be a long rank.

Africa

The recommended countries for expansion in Africa are perhaps Tunisia

which has low threats and low opportunities.

The PESTEL analysis for Tunisia doesn’t show positive ranking and high

negative rankings Political, Economic and Technology.

The countries with a low ranking that should be avoided in Africa are South

Africa, Morocco and Algeria, all of which have low opportunities and high

threats.

The PESTEL analysis for the low ranking African countries show almost no

positive rankings in any category and many of the number one negative

rankings including the worst environmental score for Algeria, the worst

Economic score for Morocco and the worst Social and Technology scores

for South Africa.

Figure 25 Tallinn (source: visitaretallinn.it)

Figure 25 Tallinn (source: visitaretallinn.it)

ANALYSIS

OPPORTUNITIES FOR FURTHER ANALYSIS


Opportunities for Further Analysis

While this study was limited in scope, there are many more ways that the

country data could be analysed. In particular, an extensive sensitivity

analysis could be performed to determine which factors or groups of

factors have the greatest impact on the results, and provide quick answers

to “what if” questions. As an example, in the accompanying Excel workbook,

there is a sheet called PESTEL which shows how one could compute the

average opportunity and threat scores using an alternative technique:

rather than simply averaging across all of the factors with equal weights,

we recognize that there are, for example, many more political than

technological factors. We therefore compute the average of each PESTEL

group first, and then take the average of the averages to come up with the

final opportunity and threat scores. This provides a balancing out effect,

which results in more tightly clustered data points, and arguably a more

accurate reflection of each country’s strengths and weaknesses. A further

step might be to assign weights to each category, so that the model could

tell us, for example, how the countries would be ranked if we were 1.5 times

as interested in social opportunities as we are concerned about legal

threats.

Further ways to enhance the model may include:

Removing a certain number or percentage of top and bottom values

from the data set for each factor, in order to discount outliers.

Using median rather than mean values as “average” threat and

opportunity scores.

Using more complex statistical techniques, such as second order

analysis, to determine country rankings.

“Drilling down” into each continent, comparing only the countries in

that region with each other.

While CMK Konsulting stands behind the conclusions and recommendations

presented in this paper, we recommend that a second phase of work be

done to provide additional insights into bank expansion options. Our

employees have a great deal of experience doing this type of work, and we

look forward to continuing to collaborate with our valued client, Dr. Tavana,

should he choose to engage us for a Phase II of this project.

Figure 26 Analysis (source: economist.com)

SOURCES

SOURCES


Sources

Bhattacharya, Joydeep: The role of Foreign Banks in Developing Countries:

A survey of the evidence, Department of Economics, Ohio State University

(http://www2.econ.iastate.edu/faculty/bhattacharya/

foreignbankspaper.pdf)

Buch, Claudia M. (1999) : Why Do Banks Go Abroad? - Evidence from

German Data, Kieler Arbeitspapiere, No. 948

(http://www.econstor.eu/bitstream/10419/17810/1/303447842.pdf)

Ernst & Young Publication (2013): Banking in emerging markets seizing

oppurtunities overcoming challenges. EYG Nr. EYG No. EK0145

http://www.ey.com/Publication/vwLUAssets/Banking-in-emerging-markets-

seizing-oppurtunities-overcoming-challenges/$FILE/Banking-in-emerging-

markets-seizing-oppurtunities-overcoming-challenges.pdf

Godfrey, Elli St.George Blog Post: PESTEL Analysis- Snapshot of Your

World, December 6, 2011

(http://www.abilitysuccessgrowth.com/2011/12/pestel-analysis-snapshot-of-

your-world-2/)

Khan, Asim “Deciding to Go International” Business Management Group,

Inc. 2005

(http://www.themanager.org/strategy/Deciding_to_Go_International.pdf) Figure 27 Kapstadt (source: boalingua.de)

LEGAL INFORMATION

LEGAL INFORMATION


Legal Information

This document and its contents are the property of CMK Konsulting or its

subsidiaries. This document contains confidential proprietary information.

The reproduction, distribution, utilisation or the communication of this

document or any part thereof, without express authorization is strictly

prohibited. Offenders will be held liable for the payment of damages

© 2014, CMK Inc. or its subsidiaries. All rights reserved

CMK Konsulting I Jonathan Clay I Erminio Mascetra I Geoff Klein

Figure 28 Delhi

(source: economictimes.com)

Documents

Banking in Emerging Economies - Madjid Tavana in Emerging Economies ... analysis and to consult experts with specific knowledge of bank expansion ... Algeria); Asia (China, India,