Private equity investment impact in developing markets : a study of FMO investments in financial institutions

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Private Equity investment impact in

Developing markets

A study of FMO investments in Financial Institutions

Supervisor: Jens Martin

Student: Trang Huynh

Student ID: 10007016

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Abbreviations

CAGR Compounded Annual Growth Rate

CG Corporate Governance

CtI Cost to Income ratio

EBITDA Earnings before Interests, Tax, Depreciation and Amortization

FI Financial Institutions

FMO Nederlandse Financierings-Maatschappij voor Ontwikkelingslanden N.V.

GP General Partners

LBO Leveraged Buyout

LP Limited Partners

NBFI Non-Bank Financial Institutions

PE Private Equity

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4 1. Introduction

The evolvement of portfolio companies under PE owners has always been the center of heated discussions and debates in the academic world. Despite being a relatively new player in the capital markets (since 1980s), PE plays a vital role in providing firms with access to capital and enhancing the value creation to investee companies. PE outpaced other asset classes in terms of asset growth in the past decade. The CAGR between 2005 and 2015 reached 13.7%, compared to 7.7% of open-ended mutual funds and 7.5% of hedge funds. In the same period, total capital raised has grown 4.6% per annum, dry powder 9.2% growth and unrealized value of portfolio companies 16.7% growth. In light of these developments, the global PE assets has exceeded USD 2.8 trillion worth of assets held by its comparable alternative investment hedge funds, standing at USD 3.65 trillion in 2015. Global buyout deal value is USD 252 billion, and freshly committed dry power mounted to a record level of USD 1.2 trillion1_{. PE indeed shares a}

sizeable chunk of the capital markets and thus its impact on the world economy is immense.

Academic researchers mostly seek out to understand the determinants of value creation in portfolio companies, and whether PE owners really enhance their performance. Research papers have suggested that PE owners have indeed created value in investee firms during the first wave of LBO in the 1980s, and the financial gains are primarily attributed to improvement in operating performance (Kaplan, 1989; Smart & Waldfogel, 1994). However, when it comes to the second wave, there have been mixed conclusions. Some conclude that improvement in operating performance and profitability is observed in the second wave. On the contrary, (Leslie & Oyer, 2008) argue that PE firms hardly add value to its investees. Inconsistent research outcomes indicate that PE firms possibly take advantage of market pricing arbitrage, information asymmetry (Kaplan & Strömberg, 2009) and gaps in taxation to create value.

Moreover, over the past 30 years, the role of PE firms in portfolio companies have shifted from being rigorous outside plunderer to sitting in the boards of its investees. The shift is indeed ascribed to the increasing competition in the PE industry as it develops along the way (Heel & Kehoe, 2005). While first wave is characterized by financial engineering strategies, such as, reorganizing firms’ capital structure by taking on leverage and improving sources of financing; the second wave involves broader and more complicated strategies, including financial engineering,

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5 governance engineering and operational engineering (Kaplan & Strömberg, 2009). This shift in role amplifies the pervasive influence of PE firms in radical reorganization of portfolio companies. Hence, there are room for research on the existence and the determinants value creation since the second wave. It is critical to understand the determinants of value creation and the effects that those factors have on portfolio companies. Value creation strategies chosen by PE firms can affect investees’ financial flexibility, performance, growth; which consequently determine the value of the exit.

This is thesis is an empirical study about how FMO, a Dutch development bank, created value in its PE investments in FI and NBFIs in emerging and frontier markets. What this paper adds to the current researches is that it focuses on private equity in emerging and frontier markets, where few researchers have attended to. The murkiness nature of the industry, which has no obligations for public disclosure, in combination with the underdevelopment of PE in these markets, makes academic research challenging. Furthermore, studies on PE investments in banks are limited, there is hardly any research focusing on the financial sector, which differs to a large extent from other sectors, due to the its peculiar nature of operation and systemic influence in the economy. Last but not least, the data source used for this thesis is verified and thus highly reliable. The data are obtained from internal documentation at deal level, including legal agreements, finance proposals, financial statements, exit memorandums and cash transactions. This reduces noise in the dataset and lead to more meaningful outcomes.

So why is it interesting to research PE in emerging and frontier markets? Although PE activities these markets are not as whopping as in developed market, opportunities are huge and is becoming more robust. While 2015 characterized a challenging year for emerging markets with the burst of commodity cycle leading to market-wide economic slowdown, and the inherent geopolitical volatility; the fundamentals remain strong with favorable demographics and high growth potentials. In 2015, the number of buyout deals reached a record of 430 deals announced or completed amounting to USD 53.4 billion. Interests from big PE players remain strong. The Carlyle Group has been back with fund raising for the fifth Asian growth fund, while KKR has reserved USD 100 million for investments in Africa2_{. FMO, Rabo Development (Rabobank) and}

Norfund (Norwegian impact investor) have in August this year joined forces in establishing a USD 1 billion investment firm, named Arise, focusing on financial sector in Africa3_{. These developments}

2_{Preqin Special Report: Private Equity in Emerging Markets, June 2016} 3_{Arise B.V. Press release, August 2016}

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6 highlight the strong appeal of emerging markets to PE investors. So far there is no academic paper available in English studying the transformation of investee FIs and NBFIs under PE owners in emerging and frontier markets. Therefore, I believe, this paper would add interesting outcomes to the current literature.

2. Literature review and theoretical framework 2.1. Literature review

Main question: How does PE unit of the Dutch development bank FMO create value in FIs and NBFIs in emerging and frontier markets?

Sub questions:

1. What are the factors influencing the return of PE investments in FIs and NBFIs? 2. To what extent are those factors important?

3. What are the implications / lessons learned for FMO?

PE business of FMO

Private Equity (PE) refers to illiquid investments or securities that are not publicly traded on stock exchange. Investments made by PE department, FI team, take various forms, including Direct Investments (70%), Co-investments (20%) and PE Fund investments (10%). Compared to public equity, PE investments are illiquid, ownership is concentrated, valuation is difficult, intermediaries tend to be small, financing is accompanied by control and mentoring. A typical time span of a direct investment is 5-7 years, including investment period and realization period (exit). The timeline is usually extended for 2 years in some investments due to uncertainties of exit negotiations. Possible exit routes are Initial Public Offering (IPO) – which offers a delayed exit due to lock up period, Trade sale – sale of the company to strategic investor, Secondary buyout (SBO) – sale of the company to another financial investor, Recapitalization (partial exit) – refinancing equity with new debt and payment of special dividends, Liquidation.

Measuring Value Creation in PE investments

In the “Leverage Buyout and Private Equity” paper published in 2009, Kaplan and Strömberg categorized three techniques that PE firms use to create value in investee companies, including Financial Engineering, Governance Engineering and Operational Engineering. For a development bank such as FMO, the term “engineering” is, however, less applicable. Rather, the goal is to create impact by being a value-add strategic minority investor with more control and optimizing use of (human) capital. In financial terms, this takes form of equity investments sufficiently

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7 significant to support the capitalization of banks or NBFIs. In terms of corporate governance, active participation in the board and the supervisory of the management team. Active participation can be having a seat in the board or laying off managers. In terms of operation, PE unit contributes resources, such as, industry and operational expertise, connections and experiences. This is relevant because with expertise, investment officers can do a better job in making strategic decisions that can create value for firms, including savings from cost cutting, monopoly gains through mergers and acquisitions, efficiency gaining through productivity improvements4_{. Exit}

strategy also play a key role in realizing the return. Last but not least, macro factors contribute substantially to the final return. These factors are mainly country risk and financial sector growth. This thesis will base on the three strategy pillars and other external factors to collect data, conduct hypotheses and draw conclusion.

Relevant Literature:

Literature Data set Variables Outcomes

Kaplan & Stromberg (2009)

Debt level, Financing source, Management ownership, Management incentive, Board size, Capital expenditure, Working capital, Profit margin

Financial, Operational, Governance engineering are the three factors driving the return of PE investments. Acharya, Hahn, Kehoe (2008) 66 PE deals in the UK during 1996-2004

(Table 11): Management change in 1st_{100 days, Value creation}

initiatives in 1st_{100 days, Value}

creation plan adjustments, Management support, Strong incentives, Effective board, External support.

the abnormal return on portfolio companies is attributed to PE firms’ active ownership and the corporate governance activities they are involved in.

Achleitner, Braun, Engel, Figge & Tappeiner (2010)

206 buy-out transactions in 20 different countries during 1991-2005

EV at entry, Holding period, Sales at entry, EBITDA at entry, EV/EBITDA at entry, D/E at entry, D/E at exit.

two-third of the returns are driven by operational risks, while one-third of them are driven by financial risks.

Cohn, Mills & Towery (2013)

317 LBOs in the US during 1995-2007

(Appendix A) amongst others: Net income, Pre-interest income, Interest deduction, Prior profit, Sales, interest ROA, Pre-interest ROS, Pre-Pre-interest EVA.

there is little operational improvement in target firms post-LBO.

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Gompers, Kaplan & Mukharlyamov (2015)

Surveyed 79 PE firms

IPO, Strategic sale, Financial sale, other exit routes, achievement of operational plans set out to achieve, capital market conditions, competitive considerations, Hit IRR or ROI target, LP’s pressure to return capital, Management’s opinion.

exit strategies of PE firms add new insights to what PE firms actually do to generate returns. The exit timing is another important factor to consider, which PE firms consider as important as the achievement of expected operational plan.

Acharya, Hahn, Kehoe (2008) working paper reveals that the abnormal return on portfolio companies is attributed to PE firms’ active ownership and the corporate governance activities they are involved in. The data set consists of 66 PE deals in the UK during the period between 1996 and 2004. The authors conducted interviews with the GPs who are involved in 48 out of 66 deals, and derived seven practices employed by categorizing the answers. Those are 1) due diligence, 2) Drafting of 100-day value creation plan, 3) Early management changes, 4) Substantially incentivizing management, 5) Time spent upfront with the management, 6) Putting in place an effective board, 7) Deploying external supports related to operational activities. For each practice, three actions were identified (so 21 actions in total) as most crucial and given a score of 100 (active). Any other actions were scored 0 (inactive). The outcomes suggested that active ownership indicated by the deployment of external resources and the amount of time spent upfront; and corporate governance, indicated by the incentives given to the management, which reduces the agency problem, result in alpha for a third of all deals.

Achleitner, Braun, Engel, Figge & Tappeiner (2010) research aims at decomposing the returns attributed to operational risks and to financial risks by unlevering the returns. Unlevering allows for quantifying the returns that are solely credited to financial risks. The unlevering returns are driven by three value-creation factors, including 1) EBITDA growth (revenue growth and EBITDA margin change), 2) Free cash flow effect and 3) Multiple effect. The data set consists of 206 buyout transactions from 27 PE firms in 20 different countries during the period 1991 to 2005. The outcomes suggest that two-third of the returns are driven by operational risks, while one-third of them are driven by financial risks, indicating that operational performance is more important than financial leverage. And the deals size is positively correlated to the leverage level, meaning that larger deals rely more on leverage than smaller deals.

Cohn, Mills, Towery (2013) reveals that there is little operational improvement in target firms post-LBO. Data set consists of 317 LBOs during the period between 1995 and 2007 in the US.

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9 The authors had access to the corporate tax return data of the US government which are not public, making it an exclusive data set. The result appears contradictory to previous researches that LBOs are followed by operational improvement. Another finding is firms with public financial reports do show significant improvement in operational performance. One possible explanation is that only good companies can access the public debt market and thus publish financial information. The inconsistency in operational improvement between the two sub-groups (available / unavailable public financial statements) makes it difficult to formulize the changes in operating performance of LBO deals.

Gompers, Kaplan & Mukharlyamov (2015) surveyed 79 PE firms, amounting to USD 750 bln AUM about their attributes and activities in value creation in their portfolio companies, including capital structure, corporate governance, operational enhancement and exit strategy. While their findings regarding financial, operational and governance aspects of value creation are in line with the papers of Acharya, Hahn, Kehoe (2008) and Achleitner, Braun, Engel, Figge & Tappeiner (2010), the exit strategies of PE firms add new insights to what PE firms actually do to generate returns. PE firms target Strategic sale exit route for more than half of the deals, followed by Secondary sale to another financial player or PE firm, while expect an IPO for 18.8% of the total deals. Other exit routes, such as put option on or swap agreement with the holding (parent) company, recapitalization, liquidation, account for less than 1% of the total deals. The exit timing is another important factor to consider, which PE firms consider as important as the achievement of expected operational plan.

2.2. Theoretical framework

In order to examine whether PE owners create value for their portfolio companies in terms of financial, governance and operation, it is important to measure their financial position and performance. In this research, the following measurements will be applied:

Financial indicators Leverage

Financial institutions are amongst the highest leveraged business worldwide. Leverage directly determine how much a bank can lend, and how much profit it can derive from lending activities. Thus for financial institution leverage is an important financial metric. As a company is leveraged, its management is under pressure to curb wasteful spending (overinvestment), and the company also enjoys interest tax shields benefit. Yet excessively high leverage can reduce the flexibility to make payments and the affordability to talk on new profitable investments (underinvestment). In

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10 turn, not sufficient leverage might result in suboptimal capital structure that is costly for investors. Leverage can be measured by Equity multiplier ratio as such:

Equity multiplier = Total Assets

Total Equity

Governance indicators: Corporate governance

Assisting investee companies to improve their corporate governance is a part of FMO’s value add approach towards its investee companies. If an investee company is not open at all to or is not at all willing to discuss (the improvement of) its corporate governance structure, it will be difficult to achieve anything. Having the right to nominate a Board member is the first step to preserve FMO’s strategic position. FMO’s nominee director should make sure that FMO can influence management’s decision making. In addition to the board representation, there are other CG attributes that indicate the level of CG quality. FMO’s internal scorecard measure five areas of CG. Please refer to Annex 1 for detailed explanations of the attributes.

Management quality

The quality of the management of the financial institution is highly correlated to its performance5_.

It is therefore important to understand their background, proven track record of management in times of crisis, as well as be aware of any changes in management or the dominance of one of the managers very dominant?

Shareholder constitution (Ownership structure)

Assess the quality of the shareholders. To what extent can the financial institution fall back on its shareholders? A good shareholder base is as important as good corporate governance. The alignment of shareholders as well as their support in financial and operational activities partialy determine the return of an investment6_.

Operational indicators: Profitability

Return on average equity = Net profit

(Total Equity in year n+Total Equity in year n+1)/ 2

Efficiency

5_{Granatelli & Martin, Financial Analysts Journal (1984)} 6_{Kaplan & Schoar (2005)}

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11 Cost to income ratio = Operating expenses

Operating income

Operating expenses include salaries and other personnel costs + administrative costs, overhead

+ depreciation (but excluding provisioning) / interest income -/- interest expenses + other operational income (preferably only fees and excluding volatile items like capital gains, forex earnings).

Market position (0-100)

Financial institution with a leading market position has a stronger credit profile. The scorecard lays out the scale to measure the positioning of the bank/NBFI, from Very good to Below par.

3. Methodology and Hypotheses

Methodology: Multi-variable Linear Regression Equation:

IRR = β1 Status + β2 Stake + β3 EquityMultiplier + β4 Board + β5 CG +β6 Management + β7

Ownership + β8 ROAE + β9 CtI + β10 MarketPosition + β11 SectorGrowth + β12 CountryRisk + β13

Swap/Put +β14 Strategic/Trade + β15 Secondary + β16 OnExchange + β17 IPO +ε

Variables: operational and financial variables reflect the status at exit, because the final status of the bank or NBFI determines our decision to exit.

 Dependent variable: IRR

 Independent variables: Status (dummy) Stake (%), Equity Multiplier (Leverage), Board representation (dummy), Corporate Governance quality, Management quality,

Shareholder Constitution, ROAE (%), CtI ratio (%), Market Position, Financial Sector Growth, Reversed Country Risk Rating, Swap/Put Option exit (dummy), Strategic/Trade Sale (dummy), Secondary Sale (dummy), Sale on stock exchange (dummy), IPO

(dummy)

Variables Dummy Quantitative

Status Direct investment (1), Co-investment (0)

Board Representation Yes (1), No (0)

Corporate Governance 0 (below par) – 100 (very good), in

interval of 25

Management Quality 0 (below par) – 100 (very good), in

interval of 33

Ownership Structure 1 (below par) – 4 (very good), in

interval of 1

Market Position 0 (below par) – 100 (very good), in

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Cost-to-income (%) Operating costs/Operating income, is a

measurement of efficiency. Is measured at the exit year.

ROAE (%) Is a measurement of profitability.

Is measured at the exit year.

Equity Multiplier Total Assets/Equity, is an indicator of

leverage (= Equity Multiplier – 1). Is measured at the exit year.

Final Stake (%) Stake at exit year

Reversed Country Risk 1 (most risky) – 21 (least risky), in

interval of 1

Financial Sector Growth Is measured by the growth of domestic

credit provided by the banking sector during the investment period.

Swap/Put Option Yes (1), No (0)

Strategic/Trade Sale Yes (1), No (0)

Secondary Sale Yes (1), No (0)

Sale on exchange Yes (1), No (0)

IPO Yes (1), No (0)

Explanation:

IRR: is calculated from the cash flows registered on FIA, an internal transaction reporting system. These cash flows include subscriptions, dividends and sale proceeds.

Status: Direct investment or Co-investment Board representation: yes or no

Corporate governance7_(0-100)

 Commitment to Corporate Governance / Family Governance (CG documentation, code of conduct or ethics / separation between family and business matters, succession planning)  Structure and Functioning of the Board of Directors (composition, skill-set, independence,

committees, strategic advice, succession planning, working procedures)

 Control Environment and Processes (audit committee and internal audit, risk governance, internal controls, MIS and compliance)

 Transparency and Disclosure (information dissemination, disclosure level on website / annual report)

 Shareholder Rights (related party/intra-group transactions, classes of shares, voting, changes in control rights)

Management quality (0-100)

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13  Very good (100): Management has more than sufficient (foreign) knowledge and relevant banking experience. Management has managed earlier downturns with good results. There is a balanced management team, CEO has no dominant position.

 Good (66): Management has sufficient knowledge and experience. Management has experience in more developed countries. Or: knowledge input from abroad, consultancy firm or twinning with foreign financial institution.

 Intermediate (33): Management has sufficient knowledge, but not enough experience. Management has no proven experience in crisis-situations. Many changes and/or dominant leadership.

 Below par (0): Either one of the following arguments: Management has insufficient knowledge and experience or management obtained its position because of (family) relationships. Many changes or dominant leadership.

Shareholder constitution (1-4)

 Very good (4): Strong financial and operational support – Financial institution is part of a financial conglomerate, or in the hands of one shareholder, which has proven to be prepared and capable to support the institution financially.

 Good (3): Strong financial and limited operational support – Committed shareholders, which have proven to be prepared to support the financial institution in difficult times. However, shareholders provide limited operational support and knowledge transfer.  Intermediate (2): Moderate financial and strong operational support – Moderately

committed or able shareholders in terms of financial support but prepared and capable to provide (evidenced) operational support and knowledge transfer.

 Below par (1): Weak financial and limited operational support – Shareholders with (potential) opposite interests. It is not clear whether they are capable of strengthening the capital base of the financial institution in times of distress.

Market position (0-100)

 Very good (100): The financial institution has a leading market position and is innovative enough to maintain this position or has a leading position in a niche market.

 Good (66): The financial institution has a good market position (> 8%) and is one of the larger financial institutions of the country or has a significant role in a niche market.  Intermediate (33): The financial institution is small and has a small overall market position

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14  Below par (0): The financial institution is small and has a small overall market position (<

2% of total assets).

Reversed country risk rating (F1-F21)

FMO has an internal country risk rating, which follows a scale of 1 (lowest risk) to 21 (highest risk), which investments in high-risk country have higher probability of failure. This scale is thus reversed in order to align with the ranking of other variables. Please refer to Annex 6 for FMO country risk rating.

Financial sector growth (during the investment horizon): is measured by the growth of domestic credit provided by the banking sector, obtained from World Bank Data Bank.

4. Data and Descriptive statistics

Data source: Macroeconomic data is obtained from World Bank Data and Business Monitor Indicators (BMI). Deal information is obtained from internal documentation, including finance proposals, investee financial and corporate reports, legal agreements such as shareholder agreements or share purchase agreements, exit memorandums. Cash flows used for the calculation of the IRR and TVPI are obtained from FIA, an internal transaction reporting system.

Data set: the data set includes 68 investments in FIs and NBFIs of FMO, excluding 10 investments left out because of insufficient filing. At the point of conducting this research, the data set was not ready in place. The data collection process is labor-intensive, as it requires scanning all documents at deal level and discussions with responsible Investment Officers. In this manner, profound understanding of each deal can be obtained and serves as a starting point to compile data needed for the regression.

5. Results

5.1. Descriptive statistics

On average FMO owns significant stake (12%) in its portfolio companies. The implication is to have significant influence at the board and management level. Nevertheless, corporate governance and management quality score 56, merely above the average level of 50. The mean of cost-to-income is 67%, in line with industry average for banks. Equity multiplier appears rather high, averaging 6.7x. For banks leverage is an important factor that drives returns; however, this is not reflected in the modest average ROAE of 7%. This is an indication of strong effects from other components that are not included as one of the variables in this regression, due to missing reporting data. Those are net margin, risk-weighted asset turnover, asset risk. Weak market position as indicated by the below average score, 46, can be the explanation for low margin and/or

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15 profitability. Country risk is high, averaging 7.7, which according to the original scale is 15-16. The majority of the investments are in frontier market; thus the risk level is relatively high. High risk comes along with high growth in financial sector, averaging 49% per annum. Frontier markets have low banking penetration and low credit to GDP as a percentage, thus the growth of financial sector is most of the time a multiple of GDP growth. Yet despite the high risk taken, the IRR averages only 12%, significantly lower than the 43% reported by Achleitner, Braun, Engel, Figge & Tappeiner (2010) for the period from 1991 to 2005, or 35.5% by Acharya, Hahn, Kehoe (2008) in the years between 1996 and 2004. The difference research period (2004-2016) can be an explanation, and noting that 12% return is material comparing to the low-interest rate environment imposed post the financial crisis in 2008.

5.2. Regression analysis

Multicollinearity check: Including equity multiplier and ROAE in one regression can pose multicollinearity problem, and leverage is one component of the return to equity. Other variables, even though appearing weakly correlated with others, can potentially pose the same problem. Hence, a multicollinearity check is necessary before running the regression. The correlation matrix in Annex 4 shows low correlation (< 0.5) amongst variables, indicating that there is no multicollinearity.

Multiple linear regression (Model 1): 17 variables are included in the linear regression. It is better to have too many variables than having too few, because of the omitted variable bias. Hence it is best to start with a big model. In addition, there are no variables that measure kind of the same thing, thus justifying a big regression model. The significant F is 0.0029, below 1% significant level. It can be concluded that the 17-variable model is a better fit than the intercept-only model. In other words, the model explains the returns. What remains to see is what variables actually drive the IRR. The p-values of ROAE and Strategic/Trade sale exit are 0.9% and 0.2%, respectively, meaning that the corresponding coefficients are significant at 99% confidence level. Secondary sale and IPO exit strategy follow with 2% and 4.6% p-values; their coefficients are significant at 95% confidence level. Other variables that add value to PE FI investments at 90% confidence level include exit through Swap/Put Option (p-value = 6%), FMO’s Board representation (6%) and Financial sector growth (7%). The remaining variables have beta coefficients that are not significantly different from zero, meaning those on average do not add value to the investments.

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16 Expanded regression (Model 2): As one of the findings of Gompers, Kaplan & Mukharlyamov (2015), exit timing is also a very important factor, even as important as the achievement of the operational plan. Hence, the existing regression is expanded with the addition of market timing as a new variable. The exit year dummy variable has been added. Furthermore, some variables such as country risk might not be linear, thus the level of riskiness is categorized into three quartiles: High risk, Medium risk and Low risk. For this regression, only the exited deals are included in the dataset.

IRR = β1 BoardMember + β2 CG + β3 CtI + β4 EquityMultiplier + β5 ex2003+β6 Ex2006 + β7 Ex2007

+ β8 Ex2008 + β9 Ex2009 + β10 Ex2010 + β11 Ex2012 + β12 x2013 + β13 Ex2014+β14 x2015 + β15

FinalStake + β16 FinancialSectorGrowth + β17 IPO + β18 MarketPosition + β19 Mgmt +

β20OnExchange + β21 RiskRatingQuartile + β22 ROAE + β23 ShareholderConstitution + β24 Status

+ β25 StrategicSale + β26 SwapPutOption + ε

The finding is rather interesting, since even though both models are valid and provide better fits than a pure intercept model, apparently the Adjusted R square of Model 2 (0.68) is higher than that of Model 1 (0.29). Model 2 shows that exits in year 2009 and 2011 did indeed create values for the investments. Other variables that are significant in model 1 (Exit strategy, ROAE, Board representation, Financial sector growth) are no longer significant in the extended model.

6. Conclusion

In line with the work of Jensen & Fama (1985), my research shows that active ownership through board representation adds value to the investments, even though several factors around the board remains to be assessed, such as the size of the board or involvement of FMO’s nominee directors in board discussion. In any case, it pays off to be a hands-on investor. Secondly, profitability of investee companies is key to generate return. This finding is similar to the research of Achleitner, Braun, Engel, Figger & Tappeiner (2010), indicating that operational performance contributes largely to the returns of PE investments. In line with the findings of Gompers, Kaplan & Mukharlyamov (2015), exit timing and exit strategy are both important value creators. Last but not least, investments in FI and NBFI have enjoyed the tail wind of strong growth in financial sector, which is most of the case a multiple of GDP growth.

7. Bibliography

[1] Acharya, V. and Hahn, M. and Kehoe, C., 2009, Corporate Governance and Value Creation:

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17 [2] Achleitner, A., Braun, R., Engel, N., Figge, C. & Tappeiner, F., 2010, Value Creation Drivers

in Private Equity: Empirical Evidence form Europe, The Journal of Private Equity.

[3] Cohn, J., Mills, l. & Towery, E., 2013, The evolution of capital structure and operating

performance after leveraged buyouts: Evidence from U.S. corporate tax returns, Journal of

Financial Economics, Vol. 111, pp.469-494.

[4] Gillian, J. and Wright, M., 2014, Private Equity demystified – an explanatory guide, ICAEW Corporate Finance Faculty, Third edition.

[5]Heel, J. and Kehoe, C., 2005, Why some private equity firms do better than others, McKinsey Quarterly. Vol. 1, pp. 24-29.

[6] Kaplan, S., 1989, The effects of management buyouts on operations and value, Journal of Financial Economics, vol. 24, pp. 217–54.

[7] Kaplan, S. and Strömberg, P., 2009, Leveraged Buyouts and Private Equity, Journal of Economic Perspectives, Volume 23, Number 1, Pages 121–146

[8] Jensen, M., Agency Costs of Free Cash Flow, 1986, Corporate Finance, and Takeovers, American Economic Review, Vol. 76, No. 2, pp. 323-329.

[9] Leslie, P. and Oyer, P., 2008, Managerial incentives and value creation: Evidence from Private

Equity, National Bureau of Economic Research, Working paper 14331.

[10]Paul Gompers, P. and Kaplan, S. and Mukharlyamov, V., 2015,What Do Private Equity Firms Say They Do?, Harvard Business School, Working Paper 15-081

[11] Smart, B. and Waldfogel, J., 1994, Measuring the effect of restructuring on corporate

performance: The case of management buyouts, Review of Economics and Statistics, vol. 76, pp.

503–11. .

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Annex 1 Corporate Governance Attributes and Scoring CG Rapid screening

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Annex 3 Descriptive statistics

Variables Mean STDEV Median Minimum Maximum Count

CG 56 18.5 50 0 100 68 Mgmt Quality 56 22.1 50 0 100 68 Ownership Structure 2.6 1.0 3 1 4 68 Market Position 46 26.1 50 0 100 68 CtI % 67% 0.8 66% -305% 271% 68 ROAE % 7% 0.4 14% -125% 239% 68 Stake % 12% 0.1 10% 0% 30% 68 Equity Multiplier 6.7 6.3 5.7 -0.9 38.8 68

Reversed Country Risk 7.7 2.8 7 1 15 68

Financial Sector Growth 49% 0.9 19% -5% 566% 68

IRR 12% 0.3 6% -100% 141% 68

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Annex 7 Country Risk Rating

Moody's

S&P-Fitch Euromoney OECD

FMO F-scale Aaa AAA >90 0 1 Aa1 AA+ 84-89 0 2 Aa2 AA 80-83 1 3 Aa3 AA- 77-79 1 4 A1 A+ 74-76 2 5 A2 A 70-73 2 6 A3 A- 65-69 3 7 Baa1 BBB+ 61-64 3 8 Baa2 BBB 58-60 4 9 Baa3 BBB- 54-57 4 10 Ba1 BB+ 50-53 5 11 Ba2 BB 47-49 5 12 Ba3 BB- 45-46 6 13 B1 B+ 42-44 6 14 B2 B 39-41 6 15 B3 B- 36-38 6 16 Caa1 CCC+ 28-35 7 17 Caa2 CCC 18-27 7 18 Caa3 CCC- 11-17 7 19 Ca CC 6-10 7 20 C C 1-5 7 21 REGIONS XA AFRICA F15 XL LAC F13 XX GLOBAL F14 XY ECA F13 XZ ASIA F13

Private equity investment impact in developing markets : a study of FMO investments in financial institutions