Impact of Treasury Management on Profitability of Selected Rural Banks in Ashanti Region, Ghana

TABLE OF CONTENTS

ABSTRACT

ACKNOWLEDGEMENTs

DEDICATION

TABLE OF CONTENTS

LIST OF TABLES

CHAPTER ONE

INTRODUCTION
Background to the Study
Statement of the Problem
Purpose of the study
Objectives of the Study
Research Questions
Significance of the Study
Scope and limitation of the Study
Organization of the Study

CHAPTER TWO

LITERATURE REVIEW
Introduction
Theories of the relationship between liquidity and profitability
Concept of treasury management
Categories of treasury management
Collections
Disbursements
Information reporting
Capital management
Employee management
Risk management
Responsibilities of a treasury department
Treasury Role-1: Cash forecasting
Treasury Role-2: Working capital management
Treasury Role-4: Investment management
Treasury Role-5: Treasury risk management
Treasury Role-6: Credit rating agency relations
Treasury Role-7: Bank relation
Treasury Role-8: Fund raising
Treasury management tools
E-invoicing and payments
Automated Clearing House (ACH)
Merchant services
Automated receipt and deposit of payments (Retail Lockbox)
Sweep accounts
Commercial cards (Corporate Expense Control)
Liquidity management best practices for banks
Empirical literature review

CHAPTER THREE

RESEARCH METHODS
Introduction
Research design
The target population
Sample size and sampling techniques
Type of data and sources of data
Model specification
Definitions of variables
The dependent variable
Independent variables
Methods of Estimation-Panel data regression model
Fixed effect (FE) panel regression model
Random effect (RE) panel regression model
Data processing, presentation and analysis

CHAPTER FOUR

RESULTS AND DISCUSSIONS
Introduction
Descriptive statistical analysis of variables
Regression diagnostic tests
Analysis of correlation
Normality test
Results of fixed effect (FE) panel regression model
Results of Hausman test
Results of random effect (RE) panel regression model
Impact of treasury management on profitability of rural banks
Research objective two: Influence of cash-deposit ratio (CDR) on profitability
Research objective three: Relationship between loan-deposit ratio (LDR) and profitability
Objective four: Evaluation of the effect of loan-asset ratio (LAR) on profitability
Chapter conclusion

CHAPTER FIVE

SUMMARY, CONCLUSION AND RECOMMENDATIONS
Introduction
Summary of findings
Conclusion
Recommendations
Suggestions for further research

REFERENCES

ABSTRACT

This study was conducted with the core purpose of investigating the impact of treasury management on profitability of rural banks in Ghana. Fifteen rural banks operating in the ashanti Region were selected for the investigations based largely on availability, consistency and accessibility of their annual audited financial reports for the period under study. The study covered a five-year period from 2011 to 2015. Quantitative research design was adopted. Secondary data in the form of treasury management ratios including current ratio, cash to deposit ratio, loan to deposit ratio and loan to asset ratio were extracted. Return on equity (ROE) was used as a proxy for profitability. Data were processed in EVIEWS econometric software and were organized in tables. Random effect panel regression methodologies were relied upon for estimation and analysis of data along with descriptive statistics. The study reports that current ratio has a positive significant influence on profitability while cash-deposit ratio has negative but insignificant effect. Again, loan-deposit ratio related positively with profitability at insignificant levels whereas loan-asset ratio impacted significantly negative on profitability. The study recommended prudent management of current assets. Rural banks should ensure that their current assets are always in excess of current liabilities so that meeting short-term obligations may not pose challenges.

ACKNOWLEDGEMENTs

I wish to express my profound gratitude to my supervisor Dr. Addo Charles, for his superb supervision, learned criticisms and perfect directions, which enabled me to successfully complete this report. Am also grateful to Emmanuel Osie for doing the typing for me.

I am particularly grateful to the board of directors, management and staff of Asante Akyem Rural Bank Limited for their support and cooperation. My sincere appreciation goes to Mr. Atta Gyamfi, General Manager of Asante Akyem Rural Bank Limited. I also thank my elder sister Esther Oduro and other siblings for their financial support.

DEDICATION

To my late mum Madam Cecilia Fordjour

LIST OF TABLES

1 Descriptive statistics

2 Correlation matrix

3 Results of normality test.

4 Fixed effect model with ROE as dependent variable

5 Results of redundant fixed effect test

6 Hausman test results

7 Random effect model with ROE as dependent variable

CHAPTER ONE

INTRODUCTION

Background to the Study

The banking sector is the backbone of the Ghanaian economy and plays an important financial intermediary role. Therefore, its health is very critical to the health of the general economy at large. In the last ten or more years there has been a rapid increase in the activity of foreign banks in Ghana, and this has fostered rapid competitiveness among banks in Ghana (Kakra & Ameyaw, 2010). In our increasing world of business and finance, the task of each bank operating to make more profit is becoming a challenge with each passing day. In order for an organizations like rural banks to operate optimally, it has to be able to manage its finances profitably concerning it inputs and output.

Since the era of the new millennium, Ghana has experienced some great levels of macroeconomic stability, for this reason banks are in a position to efficiently play their primary role as financial intermediaries in the economic growth process, channeling funds from savers to borrowers for investment (Kakra & Ameyaw, 2010). In Ghana, banks are key providers of funds, and their stability is of paramount importance to the financial system. As such, an understanding of the financial management practices and the drivers of banks’ profitability for that matter is essential and crucial to the stability of the economy.

A number of studies have examined bank performance in an effort to isolate the factors that account for interbank differences in profitability. These studies fall generally into several categories. One group has focused broadly on the tie between bank earnings and various aspects of bank operating performance. A second set of studies has focused on the relationship between bank earnings performance and balance sheet structure. Another body of literature has examined the impact of some regulatory, macroeconomic or structural factors on overall banking performance. The term bank structure is frequently used when referring to the characteristics of individual institutions. Individual bank characteristics such as the portfolio composition, and the scale and scope of operations, can affect the costs at which banks produce financial services. Market structure, measured by the relative size and number of firms, can influence the degree of local competition, and by extension the quality, quantity, and price of financial services ultimately available to bank customers (Kakra & Ameyaw, 2010).

Financial institutions play a crucial role in economic development and growth. The existence of bank financial institutions and non-bank financial institutions, supported by efficient money and capital market keeps the financial system complete, while enhancing the overall growth of the economy. Financial institutions play the role of financial intermediation by collecting and mobilizing resources to finance business and development projects that are essential for economic development. An efficient financial system is a prerequisite for proper financial intermediation leading to sustainable private sector investment and the promotion of entrepreneurship. As such, an understanding of the role treasury management plays in the profitability of financial institutions such as the rural banks is essential and crucial to the stability of the economy Kakra & Ameyaw, 2010).

Although the financial system incorporates a broad range of institutions which can be categorized into bank and non-bank financial institutions, the banking system dominates. As at 2008, the banking system in Ghana accounted for 70 percent of the financial sector (Bawumia et al., 2008). This makes the rural banking sector critical to the development of the economy as failure of this sector could have adverse systemic effect on the entire economy.

Treasury management is one of the tasks involved in the current culture of cash management. As such it means assuming a number of responsibilities concerned with the control of monetary flow of organizations and liquidity positions that will lead to improvements in the results of the treasury department and in those of the remaining departments. The tasks entrusted to this department must center on obtaining profits by maximizing short-term profitability obtained through surpluses in liquidity and through cost cuttings in the management of treasury deficits, all of which help to achieve the general objective of maximizing the value of the organization. But effective cash management involves the use of tools and techniques, and also covers developing and maintaining successful bank relationships. The role of the bank is to provide services that include payment lines, overdraft and credit facilities, information flows and investments.

Treasury management thus becomes a highly important part of corporate strategy, as it means implementing the philosophy of cash management at the treasury department. A direct link is established between treasury management and the concepts of liquidity and profitability. The treasury department ceases to be considered merely as a cost center and becomes a profit center, as for other departments, which implies an active, autonomous, independent concept of corporate liquidity management.

Treasurers are generally specialists with expertise in the monetary and credit market who are skilled in managing relations with financial institutions. They are in charge of administering the corporate treasury dynamically, effectively, consistently and prudently. From the conclusions of the study by Iturralde, Maseda & San José (2004) treasury management involves the following tasks: Liquidity monitoring and cash management, management of short-term needs and surpluses, financial risk management and management of relations with financial institutions.

Statement of the Problem

In recent times, treasury risk management has often been in the news especially in situations where things have gone wrong. For example, losses of £150 million in foreign exchange trading by Allied Lyons; US$ 691 at the All First Financial; and AUD 360 million at the National Australian Bank are a result of the weaknesses in the way currency risk is being managed. These losses indicate, therefore, that weaknesses in the commercial bank’s internal controls, especially in currency risk management, can have a very significant impact to the existence and sustainability of banks, both financially and operationally, in the final act this can result to the instability of the whole financial system in the country. Efficiency risk management has become a critical element of banks’ sustainability and growth.

Therefore, any problems in the risk management have an immediate effect on banking industry, financial markets, and financial systems at large; this can indirectly influence the country’s economic system. The other concern is that commercial banks hold larger deposits compared to other financial or noncommercial banking institutions. Thus, efficient management of the risk has an impact on the sustainable growth of the banking industry and the economy at large. The trend of changing economic environment and, hence free and open market operation in the financial market in Ghana compels most commercial banks to determine how they can best adapt to currency trading, position management and currency risk management (within the existing regulatory framework). These efforts of trying to adjust to economic changes via privatization and open market policies are not only inevitable, but also of interest in the performance of the banking industry in light of the reforms.

The banking industry in Ghana is currently going through transformation due to the new products and services being introduced by the banking industry as a result of globalization and the adoption of new technologies. It is therefore imperative that every bank operates at optimum efficiency to keep up with the growing demand. Unfortunately, this primary objective is not fully realized due to weak treasury management capacities especially in the rural and community banks. It is for this reason that the researcher sought to undertake this project to help banking institutions, particularly rural banks to determine how they can efficiently manage their finances to improve on their performance.

Purpose of the study

The main purpose of this study was to investigate the impact of treasury management on profitability of selected rural banks in the Ashanti Region of Ghana.

Objectives of the Study

The specific objectives of the study were:

1. To examine how current ratio influence profitability of selected rural banks.
2. To explore the effect of cash to deposit ratio on profitability of rural banks.
3. To determine the influence of loan to deposit ratio on profitability of rural banks.
4. To evaluate the effect of loan to asset ratio on profitability of rural banks.

Research Questions

The specific questions addressed by this study were as follows:

1. How does current ratio of rural banks influence their profitability?
2. What is the effect of cash to deposit ratio on rural banks’ profitability?
3. What impact does loan to deposit ratio exert on profitability of rural banks?
4. What is the effect of loan to asset ratio on rural banks’ profitability?

Significance of the Study

As an academic exercise, it would afford the researcher the opportunity to contribute to knowledge, improve upon my research experience and provide a basis for further research.

The motivation for this study is to develop a set of recommendations that could prove useful for management decision making and policy objectives in the rural banking sector by examining factors that impact on profitability of rural and community banks and the extent to which profits of the aforementioned banks are influenced by these factors. These recommendations would not only prove useful in Ghana, but also in other medium size economies in the Sub-Saharan Region.

Finally, this research will serve as a guide for management of rural banks towards their treasury management policy and implementation as far as their effort to render better services for their clients are concerned.

Scope and limitation of the Study

This study focused conceptually on the impact of treasury management on profitability of rural banking institutions. Fifteen rural banks were selected from the Ashanti Region of Ghana. The study covered a five-year period from 2011 to 2015. Selection of variables was limited to four main treasury management indicators of current ratio, cash to deposit ratio, loan to deposit ratio and loan to asset ratio. The influence of these ratios on profitability defined the scope of the entire study. Return on equity was used as proxy for profitability.

The main limitation of this study was the availability of data. Usually, questions are raised as to the authenticity and the genuineness of secondary data for such studies. In this particular study, data constraints limited the number of banks to only fifteen. This study is equally limited by omitted variable bias since not all variables that can influence profitability of rural banks could be considered in the model specified; no control variables were also included.

Organization of the Study

This study is organized in chapters. Chapter one dealt with the introduction to the whole work and contains the background of the research and the statement of the problem. The purpose, objectives and research questions are also specified in this chapter. The scope and limitations of the study are highlighted. Chapter two concentrated on literature review. Related theories and concepts on the subject on which this thesis focuses are presented. This chapter gave the theoretical foundation for the study. The third chapter presented the research methods adopted for the study. The fourth chapter of the study presented the results and discussion of data analysis. Chapter five deals with the presentation of the summary of findings of the study, conclusion and recommendations.

CHAPTER TWO

LITERATURE REVIEW

Introduction

The general goal of this chapter is to conduct literature study on the investigation of the impact of treasury management on profitability of rural banking institutions. The chapter presents an examination of scholarly works and theories associated with the subject matter of the study. There are three main sections in this chapter. Section one presents a review of relevant theories associated with the study whilst the second section looks at the conceptual review. The third section presents an overview of previous empirical works related to the present study. The summary section of the chapter is meant for knowledge and research gaps to be filled by the current study.

Theories of the relationship between liquidity and profitability

A number of theories have been put forward which seek to provide insight into the underlying relationship between liquidity and profitability of deposit money banks. The basic question which the underlying theories attempt to answer is how does liquidity affect profitability in banking? Osborne, Fuertes & Milne (2012) postulated that higher liquidity is often costly to banks, implying that higher liquidity reduces profitability. However, according to the trade-off theory, higher liquidity may also reduce a bank’s risk and hence the premium demanded to compensate investors for the costs of bankruptcy. (Osborne, et al. 2012) According to conventional corporate finance theories, a bank in equilibrium will desire to hold a privately optimal level of liquidity that just trades off costs and benefits implying a zero relationship at the margin.

However, capital requirement imposed by monetary authorities, if they are binding, forces banks to hold liquidity in excess of their private optimal level and hence force banks above their internal optimal liquidity level (Miller, 1995, Bussen et al. 1989). Furthermore, since bank’s optimal liquidity level is likely to vary over the business cycle, typically rising when there are higher expected costs of distress, the relationship between liquidity and profitability is likely to be highly cyclical, becoming more positive during the periods of distress as banks that increase their liquidity improve their profitability (Osborne, et al. 2012). Thus, there may be a positive or negative relationship between liquidity and profitability in the short-run depending on whether a bank is above or below its optimal liquidity level.

Flannery and Rangan (2008) assert that indeed if banks are successful in attaining their optimal liquidity level there may in fact be no short-run relationship at all, since the standard first order conditions imply that any change in liquidity has no impact on profitability. However, in the long run, regulatory liquidity requirements may be binding. This implies that higher liquidity only reduces profitability if banks are above their optimal liquidity level, for example due to regulatory requirements or unexpected shock (Flannery & Regan 2008). In corroboration of the above, Osborne, et al. (2012) opined that banks’ optimal liquidity level rises during periods of banking sector distress, since in such conditions the expected cost of bankruptcy rises.

Consequently, it is expected that the average relationship between liquidity and profitability across banks will be cyclical. This is because in a distressed environment banks tend to be below their optimal liquidity level, whereas during normal conditions, banks may either meet their optimal capital level or not, in which case the relationship would be approximately zero, or overshoot, in which case banks can increase profitability by reducing the liquidity level (Osborne, et al. 2012). A bank with a higher liquidity level has more chances of surviving and improving profitability in the future. Allen and Marguez (2011) argued that this may result in large voluntary liquidity buffer in competitive markets, since the higher liquidity is a more effective guarantee of banks’ solvency and therefore allows banks to offer more surplus to borrowers. The effect is to increase bank’s optimal liquidity level.

Agbada and Osuji (2013) captured the relationship between liquidity and profitability rather succinctly. According to them, maximum safety or in simple language we can say liquidity can be attained only if the banks keep high amount of cash against the deposits they hold. But if they do this, this will not bring profit for the banks. Similarly, if they go the other way round that is they only keep investing and trying to increase the profitability factor then they will have illiquidity problem if customers demand for much cash in a given period”. Thus, the authors advocated that a good banker should try to reconcile the twin conflicting objectives by actually working out a good portfolio mix. This can be done by analyzing the situation, studying the objectives and therefore choosing a diversified and balanced asset portfolio.

Concept of treasury management

There is romance to that word “treasury.” It invokes images of subterranean passageways to torch-lit rooms filled with precious coins and objects d’art. No wonder many business decision makers wonder if “treasury management” applies not to them but rather to monarchies and governments. Yet most are surprised to learn that treasury management not only applies to them, but applies in a big way. In business today, treasury refers to a company’s funds. Treasury management refers, quite simply, to making the most of those funds. The term may sound highfalutin, but in fact treasury management can be remarkably simple to implement and sustain. Once in place, a good suite of treasury management services can all but run itself. That means less work and, often, lower cost. “Lower cost,” of course, is another way of saying “higher profits.” Treasury management is no longer the exclusive domain of corporate giants that can afford in-house departments. Even small to midsize companies can have easy, low-cost access to proficient treasury management tools. All it takes is a bank that is forward-thinking enough to provide them. The right mix of treasury management services can help simplify and accelerate the day- to-day financial operations of a business.

Treasury management thus becomes a highly important part of corporate strategy, as it means implementing the philosophy of cash management at the treasury department. A direct link is established between treasury management and the concepts of liquidity and profitability. The treasury department ceases to be considered merely as a cost center and becomes a profit center, as for other departments, which implies an active, autonomous, independent concept of corporate liquidity management Organizations’ treasury departments are tasked with numerous functions including account reconciliation, general ledger posting, foreign exchange (FX) risk management and balance reporting. But beyond conducting these and other daily cash management activities, today’s treasury departments also perform more complex functions such as hedge accounting as well as specialized reporting in response to new and changing government regulations. They use a variety of tools to manage these processes. Among those tools are treasury management systems (TMS), often also referred to as treasury workstations (TWS). They are usually automated systems or software packages that allow companies and their treasury departments to communicate and/or interface with banking partners, vendors and customers in real time. TMS primarily enable treasury departments to operate more effectively and efficiently.

Over the years the functionalities of treasury management systems have improved tremendously in terms of what and how what they are able to deliver. But there have also been challenges. For instance, there has been a trend toward using SaaS/ASP (“software as a service”/application service provider) solutions. Primary reasons behind this trend are the decreasing support from IT departments and the difficulties companies face when outsourcing specialized IT services. SaaS/ASP solutions offer a strong value proposition as long as customization is not necessary and a treasury department is satisfied with their offerings. At the same time, some companies are continuing to utilize home-grown solutions while others are using a combination of Excel and online bank portals.

What drives the decision to use a specific type of TMS and what functionalities are companies looking for in such systems? Complexity and size of a company are two key factors that determine the functionalities needed in a TMS. Larger organizations with more complex operations require their TMS to be equipped with greater functionalities than do smaller ones. Some companies whose IT focus is on enterprise resource planning (ERP) centralization and implementation are using an ERP cash management module.

In order to gauge trends in the use of treasury management systems, the structure of those systems and the complexity of instruments transacted within them, gtnews conducted a survey of its corporate practitioner subscribers in January of 2015. The results, based on the 403 responses received, are presented in this, the 2015 AFP/gtnews Treasury Management System Survey. The survey analysis also assesses the current benefits of TMS, challenges they present and opportunities for improvement. Results were compared across defined regions (based on organization location) and revenue categories.

Concepts of liquidity and profitability

According to Olagunji, et al. (2011) liquidity refers to the ability of a bank to ensure the availability of funds to meet financial commitments or maturing obligations at a reasonable price at all times. Put differently, bank liquidity means banks having money when they need it particularly to satisfy the withdrawal needs of their customers. The survival of deposit money banks depends greatly on how liquid they are, since illiquidity, being a sign of imminent distress, can easily erode the confidence of the public in the banking system and results to run on deposit. Liquid assets should be marketable or transferable. This means, they are expected to be converted to cash easily and promptly, and redeemable prior to maturity. Another quality of liquid assets is price stability. Based on this characteristic, bank deposits and short term securities are more liquid than equity investments due to the fact that the prices of the former are fixed than the prices and value of the later (Richard, 2013).

The issue of profitability is a contentious subject that a bank has to consistently face. Profit is the disparity between expenses and revenue over a period of time, normally one year. As explained by Heibati, Nourani & Dadkhah (2009), a business is organic; it survives and grows. Therefore, it is important that a bank earns profit for its long term survival and growth. It is also necessary that enough profit must be earned to maintain the activities of the business to be able to obtain funds for expansion and growth of the bank.

Agbada and Osuji 2013 argued that corporate profit planning remains one of the most difficult and time consuming aspects of bank management because of the many variables involved in the decision, which are outside the control of the bank. It is even more difficult if the bank operating in a highly competitive economic environment, such as that of Nigeria.

According to Tabari, Ahmadi and Emami (2013) the profitability variable is represented by two alternative measures: the ratio of profits to assets, i.e., the return on assets (ROA) and the returns to equity ratio (ROE). In principle, return on assets ROA reflects the ability of a bank’s asset to generate profit, although it may be biased due to off-balance-sheet activities. ROE indicates the returns to shareholders on their equity and equals ROA times the total assets-to-equity ratio.

Categories of treasury management

Most treasury management services fit within four basic categories: collections, disbursements, information reporting, and capital management. Some banks, aware that today’s business needs run deeper, add employee management and risk management services.

Collections

A large number in the “Receivables” column is a good thing, provided that the funds represented by that number move in a timely fashion to the “Received” column. Treasury management helps simplify and speeds collections by providing an innovative array of convenient ways for customers to pay and offering collection tools that are faster, more convenient, and more reliable than paper invoices. The right mix of treasury management tools will automate creating, sending, and reconciling invoices. That alone lifts a substantial burden.

Disbursements

The manual payment and reconciliation of bills, salaries, and other expenses is time-consuming, and it invites human error. By automating payments and reconciliation, treasury management can save time and labor, and virtually eliminates human error from the disbursement stage. You retain complete control while funds are distributed in an efficient, timely manner.

Information reporting

In an information age, real-time data should be readily accessible to you at all times. Day or night, you should be able to log on to review receivables, payments, balances, and more. The applications that provide this information should be, at a glance, easy to understand, navigate, and use. And, since questions rarely arise when it’s convenient, help should be available 24/7.

Capital management

After funds are collected but before they are disbursed, it only makes sense to put them to work earning a return. “Earning a return” may refer to placing funds in an interest-bearing account, investing them, or using them to pay down a short-term credit line debt to reduce interest expense.

Employee management

Employee benefits fall squarely within the banking realm. A good treasury management suite provides options for 401(k) and other retirement and tax-deferred plans, as well as health plans and worker’s compensation.

Risk management

It is important to safeguard all accounts, but the business arena calls for extra precautions and internal controls. A good treasury management suite includes positive pay, which helps protect from costly internal and external fraud by matching cleared checks and ach transactions with your records. Providers should also offer a protective software application in addition to your current protection software, that helps provide additional protection for online transactions. Rapport by Trusteer, Inc. can do just that. Moreover, an experienced treasury management officer who has been around the block a few times can offer guidance on pitfalls to avoid and help provide solutions to specific challenges.

Responsibilities of a treasury department

Treasury Role-1: Cash forecasting

This is the beginning of all other roles carried on the operation of a treasury department. Dislike the accounting staffs who handle the cash receipt and disbursement activities on daily basis, treasury staffs need to draw all those accounting staffs records (within the organization including its subsidiaries if any), and compile it to generate a cash forecast (short and long-range). The forecast and all its components are needed to: determine if more cash is needed. If that is the case, then they can go on to plan for fund inquiry either through the use of debt or equity. Plan for investment purposes, if the forecast results in surplus and cash excess shows up. Plan its hedging operations by using the information at the individual currency level.

Treasury Role-2: Working capital management

Major usage of company’s cash is in the working capital area. Working capital is a key component of cash forecasting. It involves changes in the levels of current assets and current liabilities in response to a company’s general level of sales. The treasurer should be aware of working capital levels and trends, and advise management on the impact of proposed policy changes on working capital levels.

Treasury Role-3: Cash management

Combining information in the cash forecast and working capital management activities, treasury staff is able to ensure that sufficient cash is available for operational needs.

Treasury Role-4: Investment management

When the forecast shows some excess funds at, the treasury staffs are responsible for the proper investment of it. Three primary goals of the role are: (a) maximum return on investment; (b) matching the maturity dates of investments with a company’s projected cash needs; and most importantly is (c) not putting funds at risk.

Treasury Role-5: Treasury risk management

The treasury staffs are also responsible to create risk management strategies and implement hedging tactics to mitigate the whole company’s risk—particularly in anticipating (a) market’s interest rates may rise and leave the company pays on its debt obligations; and (b) company’s foreign exchange positions that could also be at risk if exchange rates suddenly worsen.

Treasury Role-6: Credit rating agency relations

A company may issue marketable debt. In this case a credit rating agency will review the company’s financial condition and assign a credit rating to the debt. The treasury staff would need to show quick responds to information requests from the credit agency’s review team.

Treasury Role-7: Bank relation

A long-term relationship can lead to some degree of bank cooperation if a company is having financial difficulties, and may sometimes lead to modest reductions in bank fees. The treasurers should therefore, often meet with the representatives of any bank that the company uses to: discuss the company’s financial condition, the bank's fee structure, any debt granted to the company by the bank, and foreign exchange transactions, hedges, wire transfers, cash pooling, and so on.

Treasury Role-8: Fund raising

Maintaining an excellent relation with the investment community for fund raising purposes, is important—from the (a) brokers and investment bankers who sell the company’s debt and equity offerings; to the (b) the investors, pension funds, and other sources of cash, who buy the company’s debt and equity. Other than those main roles, fundamentally the treasury staffs also monitor market conditions constantly, and therefore is an excellent resource for the management team should they want to know about interest rates that the company is likely to pay on new debt offerings, the availability of debt, and probable terms that equity investors will want in exchange for their investment in the company.

If a company engages in mergers and acquisitions on a regular basis, then the treasury staff should have expertise in integrating the treasury systems of acquires into those of the company. Another activity is the maintenance of all types of insurance on behalf of the company.

Treasury management tools

E-invoicing and payments

Manually issuing invoices is a tedious process. So is manually receiving and reconciling payments. For your customers, paying invoices manually is a tedious process, too. With e-Invoicing and Payments, one software application can create an invoice, transmit it as an email, and allow the customer to pay by clicking within the body of the email. Payment may be made from a checking account, by a credit or debit card, over the phone, and via a hosted web page. It is an ideal way to help speed collections, reduce error, and drive down labor costs.

Automated Clearing House (ACH)

In 1972, bankers and other business leaders in California foresaw a need for a safe, secure and reliable means of making direct account-to-account consumer, business, and government payments. The idea led to the creation of an Automated Clearing House (ACH), designed to speed paperless transactions through the Federal Reserve System. When the idea worked, ACHs began appearing throughout the nation. In 1974, many of these were nationally networked. By 2000, over 4.8 billion payments worth more than $12 trillion were processed by ACHs through the Federal Reserve System. Today’s national ACH network connects more than 12,000 financial institutions.

You can rely on the ACH network to efficiently and securely transfer funds from your own accounts. Businesses rely on the ACH for a variety of types of funds transfers, including direct deposit, large transactions, and batches to and from large customer bases.

Merchant services

The near universal use of credit and debit cards makes accepting them for payment a business necessity. Credit and debit card acceptance is a popular feature of treasury management. A bank with a solid program will let you accept Visa, MasterCard, Discover, American Express, Diners Club and JCB and even accommodate reward and loyalty programs.

Thanks to technology, there’s no longer a need to purchase and install an expensive terminal. If you have a smart phone or tablet, there’s an application that will let you swipe, approve, and accept cards.

Automated receipt and deposit of payments (Retail Lockbox)

Opening, recording, and depositing checks arriving daily from large customer bases can be time-consuming, unwieldy, and an invitation for human error. The solution is a lockbox service, where payments are read on high-speed, highly accurate scanners and deposited straight to your account, where they can be available for use the next business day. Using a lockbox service is cost-efficient and can be more economical than having staff spend hours doing what a state-of-the-art scanning equipment can do in minutes. Plus, it eliminates postal delays, speeds deposits, and virtually eliminates human error at the processing end. It is ideal for organizations that receive high-volume check payments (with or without the use of payment coupons), such as utilities, health clubs, medical and dental practices, hospitals, insurers, charitable organizations, newspapers, homeowner’s associations, etc.

Sweep accounts

As noted in the previous pages, it’s a good idea to use funds where they can earn a return between the time they are collected and the time they are disbursed. To move funds manually consumes time and can invite error. A sweep account is a treasury management service that automates moving idle funds to an interest-bearing or investment account, and moving them back again to a checking account when it’s time to disburse them.

Commercial cards (Corporate Expense Control)

The day may come when a company must trust one or more employees to spend on its behalf. That much is good business, but to proceed without controls and safeguards is to invite needless risk. A smart solution is to furnish a corporate card with the flexibility to handle petty cash, purchasing, travel expenses, even fleet management; that lets you set individual spending limits and restrict purchases by merchandise and supplier type; and whose reporting features integrate easily with your accounting system. In fact, such cards exist, and are a feature of a good treasury management suite of services.

Liquidity management best practices for banks

In finance, liquidity management takes one of two forms based on the definition of liquidity. One type of liquidity refers to the ability to trade an asset, such as a stock or bond, at its current price. The other definition of liquidity applies to large organizations, such as financial institutions. Banks are often evaluated on their liquidity, or their ability to meet cash and collateral obligations without incurring substantial losses. In either case, liquidity management describes the effort of investors or managers to reduce liquidity risk exposure. The world of liquidity management is much more complicated than it used to be. The world of cash and liquidity management was once a simpler place. Access to capital was rarely a bottle-neck, even for highly-leveraged corporates, and many had strong, long-standing relationships with a single bank that helped meet most of their funding and cash management needs.

All of that changed with the global financial crisis of 2008-2009. Corporates around the world suddenly faced the backlash of the solvency of banks, the impact on their businesses if a banking provider collapsed, and the reigning in of lending to businesses by banks. These new challenges triggered a radical reshaping of the corporate treasury landscape and the way that corporates interacted with banks.

The crisis ultimately catalyzed corporate treasurers to make a concerted move towards a multi-bank model. This change is now at heart of best practice within the marketplace. While the shift provides ample opportunity for corporate treasury functions to reduce risk and optimize cash, it also presents new challenges. For corporate treasurers, the challenges raised by a multi-bank banking model tend to vary with the size of the business. For the largest and most sophisticated corporates, the main problem is gaining visibility into multiple accounts run by subsidiaries in different countries using a variety of currencies, and then leveraging that visibility to optimize cash and working capital globally. For smaller corporates, the challenge is more around tracking payments being received into multiple banks, and reconciling them against invoices in order to manage cash flow and liquidity. For banks to remain a valued partner to corporate customers, they must set out to navigate today’s reshaped corporate liquidity management landscape. The following outlines eight best practices that banks should bear in mind when developing and offering corporate liquidity solutions. Corporations can opt for a centralized model, to run a single cash and liquidity management solution across countries or regions, or a decentralized model, where the solution focuses on particular markets.

A critical requirement of today’s corporate treasurers is timely, accurate and consolidated information to facilitate cash forecasts. Banks should look to offer cash management solutions that ensure this information is made available centrally to their corporate customers. Comprehensive balance and transaction reporting helps a bank’s corporate customers improve their cash flow management and monitor their payables and receivables more effectively. Banks can now offer corporate customers a wide range of payables and receivables solutions that help them improve the speed, efficiency and effectiveness of their working capital management.

Liquidity optimization solutions will provide banks with the capability to deliver intra-day liquidity information to their corporate customers in real-time, enabling them to manage cash flows, credit facilities and working capital quickly and responsively across multiple accounts and subsidiaries.

Cash management solutions should help corporates manage their financial supply chains by enabling corporates and banks to connect electronically with their trading partners to exchange and share transaction-related documents and information all the way along the supply chain.

There are several advanced techniques for liquidity management that banks can offer as part of their corporate solutions portfolio, including physical balance consolidation and notional balance consolidation. Advances in technology, including integrated electronic banking solutions for cash and liquidity management and mobile and tablet services, present banks with opportunities to offer corporates new services to boost automation and STP.

Corporates now, more than ever, need to maintain visibility across cash at various banks and in multiple accounts, often run by subsidiaries in different countries and denominated in a variety of currencies. They also must be able to optimize and pool liquidity across accounts in order to optimize interest rates and costs while ensuring funds and working capital are available in the right place at the right time. At root, effective and efficient management of liquidity and working capital has become a core capability of all corporates, and now, more than ever, banks need to adapt by prioritizing best practices of liquidity management.

Empirical literature review

In banking literature, the determinants of profitability are empirically well explored although the definition of profitability varies among studies. While some studies focus on the understanding of bank profitability in a particular country, others concentrate their analysis on a panel of countries (Vong & Chan, 2009). Govori (2013) observed that research studies on the determinants of banks profitability focus on returns on assets and equity and the net interest margin as measures of performance. Whether in-country or cross-country studies, Nassreddine, Fatma, and Anis (2013) argue that the determinants of banks performance can be split between those that are internal and those that are external. Internal determinants are also sometimes called microeconomic determinants or inherent performance, while external determinants are variables that reflect economic and legal environment in which the bank operates The internal factors are bank specific variables, which influence the profitability of specific banks. These factors are within the scope of the bank to manipulate and that they differ from bank to bank. These include capital size, size of deposit liabilities, size and composition of credit portfolio, interest rate policy, labour productivity, and state of information technology, risk level, management quality, bank size, and ownership, among others (Ongore & Kusa, 2013). External determinants, otherwise known as macroeconomic variables, on the other hand are variables that reflect economic and legal environment in which the bank operates (Nassreddine et al., 2013).

Macroeconomic conditions may affect banking performance in a number of ways. Firstly, there will be a higher demand for bank credit in times of economic boom than in times of recession. A high aggregate growth rate may strengthen the debt servicing capacity of domestic borrowers, and therefore, contribute to less credit risk (Vong & Chan, 2009). Alternatively, adverse macroeconomic conditions hurt banks by increasing the amount of non-performing loans. Vong and Chan (2009) examined the impact of bank characteristics as well as macroeconomic and financial structure variables on the performance of the Macro banking industry. They found asset quality, as measured by the loan-loss provisions and the loan-to-total assets ratio, to adversely affect the performance of banks. On the contrary, management efficiency as measured by the ratio of equity to total assets was positively related to banks performance. They concluded that, a bank’s performance can be improved if it is well capitalized and borrows less to finance its operations.

With regard to macroeconomic variables, only the rate of inflation exhibits a significant relationship with banks performance. Garza-Garcia (2011) analysed the determinants of bank performance in the Mexican banking sector for 2001-2009. The results of the study indicate that the lagged performance variable is positive and significant, which shows the tendency of bank profits to persist over time. Also, the Herfindahl-Hirschman index (HHI), which is a proxy for market concentration, shows no significance, thus rejecting the SCP hypothesis. The ratio of loan to total assets is negatively related to performance while capital is positive and significantly related to performance. Thus greater capital in banks reduces their funding costs and releases to them more resources to fund profitable investments. Hoffmann (2011) examined the determinants of the profitability of US banks during the period 1995-2007. Contrary to Garza-Garcia (2011), their findings document a negative link between the capital ratio and the profitability, which supports the notion that banks are operating over-cautiously and ignoring potentially profitable trading opportunities. They also find a significant negative relationship between the size of the bank and its profitability. Thus a bank can take advantage of the scale economies at a low asset size level, but these scale economies become exhausted as the bank’s size increases. Ayanda et al. (2013) looked at the determinants of profitability in the Nigerian banking industry from 1980 to 2010. Applying the econometric analysis of co-integration and error correction techniques, they found capital adequacy and credit risk to be statistically significant and negatively related to profitability of loans. Efficiency management – which shows banks’ ability to manage their cost in order to boost their profits – was, however, found to be positively related to net interest margin.

For the external or macroeconomic variables, they found broad money supply growth rate to be a significant driver both in the long run and in the short run. Sarita, Zandi and Shahabi (2012) examined the determinants of bank performance in Indonesia for the period 1994-1999 using pooled cross-sectional time series and dynamic panel data models. They established a negative and significant relationship between capital adequacy ratio, debt-to-total assets and bank performance. The findings, they argued, showed that bank performance was achieved not because of capital from the banks themselves, but from society’s funds. Bank debt as debt-to-total assets also exhibited a negative relationship.

The relationship between bank size and bank performance was positive implying that bank size increases bank performance. Molyneux and Thornton (1992) examined the determinants of bank performance across eighteen European countries and found that state-owned banks generate higher returns on capital than their private sector competitors contrary to the findings in literature. They, however, attributed this to their sample which comprises a much larger proportion of state owned banks. Hassan and Bashir (2003) analysed how bank characteristics affect the performance of Islamic bank utilizing bank level data for 1994-2001, and found an inverse and statistically significant relationship between non-interest earning assets variable and performance measures. They also established significant positive relation of economic growth with performance measures. Ahokpossi (2013) examined the determinants of bank interest margins in sub-Saharan African countries and found market concentration, bank inefficiency, equity and credit risk to be positively associated with interest margins. Liquidity ratio was negatively and significantly related to interest margins.

Macroeconomic variables’ relationship with bank performance in the study however appeared mixed. While inflation was positively related to interest margins, no evidence of significant relationship was found between economic growth and interest margins. From the literature, it is evident that determinants of bank performance are varied both internally and externally and so also the measurement of performance (profitability).

CHAPTER THREE

RESEARCH METHODS

Introduction

The research methods section of the study presents the econometric procedures the author employed to carry out study. The chapter outlines the research design, target population, sample and sampling methods. It also describes type of data and sources of data, data collection and analysis procedures. Further, it provides definitions and measurement of variables used in model specifications and data estimation techniques as well as other necessary statistical tests.

Research design

Quantitative research design was adopted for this study as it involved the collection and analysis of audited financial reports using statistical methods. The choice of this technique was inspired by the literature study conducted. The use of this design stems from the fact that data for the study already exists in financial reports of the banks. This design makes the collection and analysis of pre-existing data devoid of researcher influence or manipulation. The use of statistical modeling enables the researcher to estimate and establishes the existence of statistical relationships between the independent and dependent variables.

The target population

The study targeted licensed rural and community banks operating in the Ashanti Region of Ghana during the period of the study. There were 25 rural banks that had business offices in the Ashanti Region as at the time of the study. These banks constituted the population of the study.

Sample size and sampling techniques

A sample of 15 rural banks was selected based on availability, accessibility and consistency of their annual audited financial reports for the 2011 to 2015 financial years. This provided a panel data of 75 observations.

Type of data and sources of data

Secondary data were used for this study. Data were extracted from audited annual reports of the selected banks. Data for each of the variables of profitability, current ratio, cash to deposit ratio, loan to deposit ratio and loan to asset ratio were computed from audited annual financial statements of the banks understudy. Only the most available and accessible data from annual audited financial reports for the 2011-2015 financial years were considered.

Model specification

This study investigated the influence of treasury management on profitability, the dependent variable, using balanced panel regression. Brooks (2008) asserts that this method helps minimizes the problem of unit heterogeneity. The general structure of panel regression can be written as below … (1)

Where denotes the dependent variable, profitability of a particular bank i at time t; is a constant factor and a vector of specific variables of rural banks; represents the partial effects (coefficients) of ; is a vector of the explanatory variables and is the error term. Adopting equation 1 above from, the multiple regression equation 2 below evolves (2)

From equation (2) : PROFit refers to profitability of bank i at time t; 𝛃0 is a constant term that indicates the value of PROF if all explanatory variables are equal to zero; 𝛃1, 𝛃2, to 𝛃4 are coefficients of the explanatory variables to be estimated; refers to current ratio of bank i at time t; represents cash to deposit ratio of bank i at time t; denotes loan to deposit ratio of bank i at time t; LAR is the loan to asset ratio of bank i at time t. All the variables were computed in natural logarithm. is the error term of bank i at time t, assumed to be normally and independently distributed with zero mean and constant variance. It represents all other explanatory variables which influence profitability of banks but were not captured in the model.

Definitions of variables

The dependent variable

Profitability: This study used return on equity (ROE) as a proxy for profitability of a particular rural bank. It is measured as the ratio of profit after tax to total equity, expressed as a percentage. It shows the rate of return that shareholders receive by investing in the firm. A higher value of ROE signifies the firm’s ability to make cash and profit internally.

Independent variables

Current ratio: This is a liquidity measure that measures a bank’s ability to pay short-term liabilities or obligations as they fall due. It considers the current total assets of a company relative to the current total liabilities. It indicates whether or not a firm has enough resources to meet its short-term obligations. This study computed current ratio by dividing current assets by current liabilities.

Cash-deposit ratio (CDR): This ratio indicates how much of a bank’s core funds are being used for lending. It is the amount of cash balance branches maintain to meet their liabilities. It was computed in this study as total amount of credit extended by banks to borrowers divided by total deposits received from customers, expressed as a percentage.

Loan-deposit ratio (LDR): This ratio draws attention to the ability of a financial institution to manage withdrawals and deposits such that equilibrium is established. It is one of the widely used liquidity measures. It is computed as total loans and advances divided by total deposit and stated as a percentage. A less than one (1) LDR ratio implies that the lender uses less of its deposit to grant loans, without recourse to external borrowing and at low risk and that assets are not being used to generate income but a very high ratio indicates the bank is using more of its deposits to create loans which in turn generates income but with high risk of default.

Loan-asset ratio (LAR): The LAR was computed as the ratio of total loans banks borrowed to finance some assets to total assets, expressed as a percentage. LAR is a capital structure variable and a common indicator of capital adequacy. The composition of liabilities comprises debt obligations owed other partners such as depositors, borrowed funds, accounts payables and other associated obligations while total assets include tangible and intangible.

Methods of Estimation-Panel data regression model

The author estimated fixed effect (FE) and the random effect (RE) models of panel data and appropriate statistical tests performed (Hausman test) to select the best model for analysis.

Fixed effect (FE) panel regression model

Employing the fixed effect least-squares dummy variable (LSDV) approach, the issue of heterogeneity is taken care of by providing different intercepts for every cross-sectional unit (Brooks, 2008). The fixed model can be specified as: …. … (3)

Where i in refers to the cross sectional units representing the intercept values for each cross sectional unit. Substituting the explanatory variables of this study into this model gives equation 4 below.

Random effect (RE) panel regression model

This model assumes that a random variable that does not have linear association with the predictor variables represents the individual specific effect (Wooldridge, 2013). In technical terms, random effects have normal distribution with zero mean and nonzero variance. It uses a mean value of all the cross-sectional intercepts and its variance. It is stated in equation 5. .. (5)

The intercept () of this model is randomly determined (Gujarati, 2009) and can be modified as From (6), represents the error term that has zero mean and variance of. All cross sectional units are represented by a mean intercept and individual variations of cross sectional units from the mean intercept is captured by (Gujarati, 2009) Substituting equation (6) into equation (5) yields equation (7) below … (7)

The addition of and (error term for individual specific effects and the cross-section and time series error term) will give a composite error term, expressed as below Substituting equation (8) into equation (7) yields the random effect model in equation (9) below Where represents the mean intercept value for all cross sections and denotes random differences between the mean intercept value and the individual intercept value.

Now, substituting the independent variables of this study into this model gives the equation below

Data processing, presentation and analysis

According to Brooks, (2008) panel data is one that consists of the features of both time series and cross-section data. Panel data analysis was adopted for this study because of its ability to deal with heterogeneous nature of the banks understudy. In this study , FE and RE panel regression models were used to analyze data while the appropriate estimation technique was determined by the use of Hausman test.

Fixed effect panel regression makes the intercept in the regression vary in cross sectional terms and minimizes time-invariant disparities among the variables thereby making the estimated coefficients of the model unbiased because of omitted time-invariant characteristics (Brooks, 2008). The researcher ensured that the estimated models did not suffer from autocorrelation, multicollinearity and normality problems. Redundant fixed effect test was performed to confirm the appropriateness of the FE modeling. Descriptive statistical analysis of the variables under study was also conducted as has been done in previous studies. This was done in the form of estimation of the mean, maximum and minimum values and standard deviations of the variables of interest. The data processing was done using Eviews software version 9 and presentation was in tables of descriptive and inferential statistics.

CHAPTER FOUR

RESULTS AND DISCUSSIONS

Introduction

This study was undertaken to look into the impact of treasury management on profitability of rural banks in Ashanti Region of Ghana. This chapter presents the analysis and discusses the results of data estimations and empirical tests conducted. In accordance with the objectives and research questions, this chapter is structured as follows. Section one presents the descriptive statistical characteristics of variables of the study. It also presents results of preliminary tests. Sections two through to five respectively present the influence of current ratio (CR), cash to deposit ratio (CDR), loan to deposit ratio (LDR), loan to asset ratio (LAR) on profitability of the selected rural banks.

Descriptive statistical analysis of variables

The statistical properties of the variables used to evaluate the extent to which treasury management affect profitability of rural banks are presented in Table 1. Each variable has total observation of 75 and were measured in their natural logarithms. Measures of central tendency estimated are the mean, median, maximum and minimum whereas measures of dispersion are the standard deviation and the range. The mean is the average of the total values of a specific variable with the maximum and minimum indicating the largest and smallest values respectively and the median representing the middle value. Variability or dispersion around the mean is measured by the standard deviation. A higher standard deviation implies a greater degree of dispersion around the mean and a lower standard deviation implies that the individual observations cluster more around the mean.

The descriptive statistics table shows that the proxy for firms’ profitability, which is the return on equity (ROE) is thirteen percent (13%) with standard deviation of forty-one point six-one percent (41.61%). This shows that ROE deviates approximately forty-two percent from its average value; indicating relative stability, predictability and low volatility. The maximum ROE is thirty-one point eight-four percent (31.84%) while the minimum ROE is fifteen point seven-six percent (15.76%). That shows the firms performed averagely well for the period under study.

The average current ratio is sixteen point three-two percent (16.32%). This means that, on the average the companies have assets to settle its liabilities without being necessarily liquefied. By implication, the average current ratio is good signal of the firms’ performance. This is because of the fact the average transactions are made on cash basis. This is an evidence of good cash to cash management and treasury at large. From the Table, the current ratio (current asset to current liability) of the banks shows some distinctive but similar characteristics in the respective accounting periods. Specifically, the Table reveals that the current ratio of all the five years (2011 – 2015) is greater than 1. This means that the current assets of the banks provide more than 100 % coverage for current liability. While this might be a good liquidity management practice it should also be recognized that it implies tying up of investable funds.

Cash-deposit ratio has a mean of 0.00164 and a standard deviation of 0.0045. The minimum and maximum values stand at 0.1374 and 0.2012 respectively. There appears to be wide dispersion from the mean, implying high level of uncertainty and instability in this ratio. The trend or behavior of this ratio seems to be difficult to predict as volatility appears to be quite high.

The situation of loan-deposit ratio is quite similar. The ratio has a mean value of 1.624 and a deviation of 2.375, moving approximately sixty-eight percent from the mean. This is very high amount of departure from the average. The system is very fragile and unstable making prediction of pattern quite difficult. The minimum and maximum values of this variable are 0.4935 and 0.7123 respectively.

Loan-asset ratio equally exhibit average degree of dispersion from the mean. Its descriptive mean stands at 1.4258 and pulls a standard deviation of 2.6574. The extent of departure from the mean is observed at roughly fifty-four percent (that is 53.65%). The fragility in this variable is moderately lower than that of the loan-deposit ratio. However, the behavior of this variable is still unreliably difficult to predict. The minimum and maximum values of this ratio are 0.3779 and 0.5064 respectively. The essence of conducting descriptive statistical analysis of the variables understudy was to enable the researcher describe the nature and pattern of the variables statistically.

Table 1: Descriptive statistics

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Source: Author’s data estimation from Eviews, 2017

Regression diagnostic tests

To ascertain the robustness of the results emanated from data estimations, the researcher conducted a number of statistical tests. The purpose of this section is to present the outcome of econometric tests performed which were intended to make sure the models meet the required assumptions of classical linear regression modelling so that the regression results do not suffer from bias.

Analysis of correlation

Correlation analysis is conducted so as to avoid a situation where explanatory indicators are correlated. The aim is to stay away from the issue of multicollinearity. Correlation also provides information on the extent to which the dependent and explanatory variables have linear relationship. Donald and Gluaber (2005) provided a practical guide on the correlation between the variables of regression. They assert that the correlation between independent variables should be less than 0.8 to 0.9. The correlations between the variables of this study pass this rule of thumb. Table 2 has it that all the independent variables have weak to moderate correlation. Multicollinearity does not manifest itself in this data set. All the explanatory variables exhibit weak form of association with the dependent variable. The associations between all the independent variables are also weak in positive and negative forms. It can therefore be argued that the data set is free from the problem of multicollinearity.

Table 2: Correlation matrix

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Source: Author’s data estimation from Eviews, 2017

Normality test

Data is said to be normally distributed when the error term clusters around the mean. This is one of the cardinal assumptions underlying normal distribution. To determine that the current data set satisfies this property, the researcher conducted Jarque-Bera (JB) test. The test criterion is that the p-value must be less than 5 percent and the Kurtosis should be plus or minus 3 so that the null hypothesis is not rejected at 5 percent level of significance (Brooks, 2008). Kurtosis measures the combined sizes of the two tails of the distribution. It measures the amount of probability in the tails. If the kurtosis of a dataset is greater than 3, it means that the dataset has heavier tails than the normal distribution but if it is less than 3, it implies that the distribution has lighter tails than a normal distribution. A cursory look at Table 3 shows that the data set is relatively distributed normally.

Table 3: Results of normality test.

Abbildung in dieser Leseprobe nicht enthalten

Source: Author’s data estimation from Eviews, 2017

Results of fixed effect (FE) panel regression model

Results of data estimation using the fixed effect (FE) estimator are captured in Table 4. The results are based on 75 balanced observations from 15 rural banks for five-year period spanning from 2011 to 2015. The dependent variable is profitability, measured as ROE. From the table, it may be observed that current ratio (CR) is positively associated with ROE at one percent significant level. This result meets expectations. Positive but insignificant association is also found between cash to deposit ratio (CDR), loan to deposit ratio (LDR) as well as loan to asset ratio (LAR) and ROE. The results here fail to meet expectations. The approval of these findings for discussion is subject to the result from redundant fixed effect test which was meant to ascertain whether or not serious similarities exist among cross-sectional units. The results of the test are presented in subsequent section.

Table 4: Fixed effect model with ROE as dependent variable

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Source: Author’s data estimation from Eviews, 2017

Results of redundant fixed effect test

The objective of this test was to provide a statistical proof or basis for the acceptance or rejection of the results obtained from the fixed effect estimator. Thus, the appropriateness of the fixed effect model for the current data set is confirmed by the results of this test. This was done by determining whether or not similarities exist among cross-sectional units. The null hypothesis underlying this test states that fixed effects are redundant. Table 5 shows the result of the test performed and one can observe that the p-values of the F-statistic and the Chi-square statistic are smaller than five percent (5%), providing statistical confirmation against the null hypothesis that the fixed effects are all equal to each other. The result obtained appears to propose that there is the presence of unnoticed heterogeneity in the data set and therefore the results of the fixed effect estimation are not statistically suitable for this dataset. The application of the random effect estimator is therefore eminent.

Table 5: Results of redundant fixed effect test

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Source: Author’s data estimation from Eviews, 2017

Results of Hausman test

The random effect model is applied under the assumption that the random effects are uncorrelated with the independent variables. There can otherwise be problem of endogeneity that may cause the estimators to be inconsistent and bias. The researcher carried out Hausman test to check this proposition. To decide between fixed effect and random effect estimation models, the Hausman test was performed. The null hypothesis associated with this test is that the correct or suitable model is random effect whilst the alternate hypothesis states that the fixed effect is rather appropriate for this data set. The test essentially determines whether the unique errors are correlated with the regressors, and the null hypothesis is that they are not. The result of this test is reported in Table 6. The Hausman test fails to reject the null hypothesis for all traditional confidence levels. There is therefore statistical basis that the assumption that the random effect should be uncorrelated with the independent variables is true for this dataset. The random effect estimator is therefore used to estimate the data. Based on these results, the researcher discusses and reports the results of the random effect model as the official findings of the study.

Table 6: Hausman test results

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Source: Author’s own computation from Eviews, 2017

Results of random effect (RE) panel regression model

Given the existence of unobserved heterogeneity in the fixed effect model found in the redundant fixed effect test and the results of the Hausman test, the researcher estimated the data in the random effect model. The model has relatively high predictive power as shown by the R-squared of 0.814081 and confirmed by the adjusted R-squared of 0.792833. This shows that 81% of the variation in the dependent variable is accounted for by the independent variables jointly; hence total variation in profitability, measured as ROE and driven by current ratio (CR), cash to deposit ratio (CDR), loan to deposit ratio (LDR) and loan to asset ratio (LAR). This indicates that the model is well fit and specified and each explanatory variable is appropriately selected and relevant in contributing to explaining the behaviour of ROE in the model. It further suggests that the issue of loss degree of freedom is taken care and the model can reliably be used to report the role of all independent variables in the affairs of the dependent variable. The results of the random effect modeling are reported in Table 7 and discussed in the sections that follow.

Impact of treasury management on profitability of rural banks

The discussion of the influence of treasury management on profitability is made in accordance with the objectives and research questions of the study. The discussion centers on the following four subsections with each section addressing one specific objective.

Objective one: Analysis of the effect of banks’ current ratio (CR) on profitability

The first objective of this study was to examine how current ratio (CR) influences profitability of the selected rural banks. This section of data analysis and discussion of results is devoted to presenting findings regarding the effect of CR on banks’ profitability performance, proxied by return on equity (ROE). Table 7 reports that rural banks’ current ratio has positive influence on their profitability. CR has a coefficient of 0.993787 and a p-value of 0.0000, making the relationship statistically significant at one percent (1%) level. The implication is that given that the effects of all other variables in the model are held constant, a unit change in CR will induce 0.99 unit change in ROE. In other words, a proportionate increase in CR of the banks will engineer almost equal proportionate increase in profitability and by extension their market value or worth. It must be recalled that CR represents the proportion of short-term and long term obligations that covered with current total assets. Current assets like cash, cash equivalents and marketable securities can easily be converted to into cash in the short term. This means that banks with larger amounts of current assets will more easily be to pay off current liabilities as they fall due without having to sell off long term revenue generating assets and by implication being able to sustain profitability performance.

Research objective two: Influence of cash-deposit ratio (CDR) on profitability

This section looks at results of data estimation on the contribution of cash-deposit ratio (CDR) in the profitability performance of rural banks. The researcher computed the CDR of the selected banks to ascertain whether or not it has significant impact on profitability. Results rather indicated a negative but insignificant association between CDR and profitability. Evidence from Table 7 shows that CDR entered into the model with a coefficient of -0.155350 with a p-value of 0.6396. This implies that given that the influence of all other variables in the model are held constant, a percentage change in CDR will adversely induce roughly fifteen point five percentage (15.5%) change in profitability.

Cash ratios are mostly determined by the central bank authorities, the regulators of the banking system and used to dictate how much credit out of deposits banks can create. A very low cash-deposit ratio means that the banks are not making full use of their resources while too high ratio indicates that the banks rely more on deposits for lending and a likely pressure on financial resources which may affect the ability of the banks to cover unforeseen fund requirements, may affect capital adequacy as well as asset liability mismatch. The negative relationship observed here may signal high rates of loan defaults and provisioning for loan losses and thus draws management attention to credit risk policies and management. It may further indicate the growth-dwindling effect of high cash ratios set by the regulator.

Research objective three: Relationship between loan-deposit ratio (LDR) and profitability

This section provides insights into the issue of whether or not firms’ total loans and total deposits have statistical relationship with profitability. Loan-deposit ratio (LDR) is a liquidity indicator usually used to gauge banks’ liquidity position by dividing total loans by total deposits, expressed as a percentage. A positive but insignificant association between LDR is reported in this study. LDR has a coefficient of 0.115095 and a p-value of 0.1606, implying that all else remaining constant, a unit increase in LDR will automatically cause profitability to increase by 0.115095; but the association is statistically meaningless. Since LDR shows how much a bank lends out of deposits it has mobilized, a positive and significant association might have been expected. This is because lending is the main income generating activity in the banking sector; and the more loans are granted, all things equal, the more may be the generation of interest income and to some extent profitability performance. But if credit appraisal systems are weak and less stringent, one can only expect high loan delinquencies and their attendant repercussions on profitability.

Objective four: Evaluation of the effect of loan-asset ratio (LAR) on profitability

The last objective that defined the scope of this study was to evaluate the extent to which loan-asset ratio (LAR) affect profitability of the selected rural banks. LAR expresses the proportion of total assets financed by loans or debt obligations taken as a percentage. Total assets here include all manner of firms’ assets, both liquid or financial and non-financial assets. This ratio is an indicator of financial leverage and paints a picture of the percentage of total assets that were financed by creditors, liabilities and other forms of debt. Debt as used in the computation of this ratio include both short-term and long term while assets include tangible and intangible.

Results of data estimation indicate a negative effect of LAR on profitability. LAR injected a coefficient of -0.185716 into the model and generated a p-value of 0.0000. The impact is statistically significant at one percent (1%) level. The implication of this coefficient is that a unit change in the ratio of loan-to-assets will, all variables held constant, induce a downward influence on profitability by -0.185716. A higher ratio of debt may portray a higher degree of leverage and for that matter, the higher may be the extent of financial risk and so it is not too surprising that a significantly negative association is observed here. This is made against the backdrop of excessively higher average LAR reported by the descriptive statistical analysis of this study. The average bank in the panel made 1.42558 loans to asset ratio. This means that the average LAR ratio stood at approximately one hundred and forty-three percent (143%) or 142.58 percent. This is very high and can only be described as excessive and that the banks appear to have more liabilities than assets, leading to a lower degree of financial flexibility since any sudden rise in interest rate may put companies in a risk of default on their loans.

Table 7: Random effect model with ROE as dependent variable

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Source: Author’s own computation from Eviews, 2017

Chapter conclusion

This chapter of the study was devoted to presentation of results from data estimations and discussion of findings. Four main objectives were outlined at the beginning of the study and results presented. The chapter has provided insights into whether or not the research questions have been answered. It must however be remembered that the analysis conducted in this chapter revealed that the current ratio of the selected banks pulled significant positive influence on profitability whereas loan-asset ratio negatively impacted profitability at statistically significant levels. The ratio of cash to deposit related negatively with profitability but the relationship was not significant just as the ratio of loans to deposits associated positively with profitability but with insignificant effect.

CHAPTER FIVE

SUMMARY, CONCLUSION AND RECOMMENDATIONS

Introduction

The topic for this empirical study is “Impact of treasury management on profitability of selected rural banks in Ashanti Region” The study was undertaken with the central purpose of assessing the effect of treasury management on profitability of the selected banks. The study was underpinned by four main specific objectives and the purpose of this chapter is to present the summary of findings and conclusions of data analysis as well as the presentation of recommendations and suggestions for further research work.

Summary of findings

This study adopted quantitative research design to investigate the impact of treasury management on profitability of rural banking institutions. It adopted panel data modelling as estimation techniques. The topic focused four variables that were used as proxies for treasury management including current ratio, cash to deposit ratio, loan to deposit ratio and loan to asset ratio. Profitability was measured by return on equity. No control variable was used and the analysis of data revealed the following findings. Descriptive statistical analysis of data revealed high level of fluctuation among the variables of loan to asset ratio, loan to deposit ratio and current ratio while cash to deposit ratio exhibited moderately low volatility. In terms of distribution, all variables in the dataset were normally distributed as illustrated by the probabilities of the Jarque-Bera test. Analysis of correlation suggested that there was no problem of multicollinearity as all the explanatory variables exhibited weak form of association with the dependent variable and the associations between all the independent variables were also weak in positive and negative forms.

Findings regarding objectives of the study revealed the following. Analysis of data for objective one which examined how current ratio influence profitability, showed a significantly positive relationship between current ratio and profitability. Current ratio injected a coefficient of 0.993787 into the model and produced a p-value of 0.0000 which is significant at one percent level. For objective two, the study reports that a negative association exists between cash-deposit ratio and rural banks’ profitability. The coefficient for this variable was -0.1155350 with a p-value of 0.6396 which is statistically insignificant. Again, results of data estimation for objective three which sought to determine the influence of loan to deposit ratio on profitability, indicated that loan-deposit ratio affected profitability negatively but the effect is was insignificant. Loan-deposit ratio provided a coefficient of 0.115095 with a p-value of 0.1606. The last objective evaluated the effect of loan to asset ratio on profitability. The study reports that a significantly negative effect was exerted by loan-asset ratio on profitability. The variable inserted a coefficient of -0.185716 into the model and generate a p-value of 0.0000.

Conclusion

The main purpose of the study was to investigate the influence of treasury management on profitability in the rural banking sector in Ghana. Data limitations caused the researcher to confine the study to rural banks operating in the Ashanti Region of Ghana. Fifteen rural banks were thus selected for the investigations. The study was conducted against the backdrop of limited empirical work on treasury management and its effect on profitability in the rural banking sector in Ghana generally and in Ashanti Region in particular. Research attention on the subject appear to focus on commercial banking sector at the neglect of the rural banking industry. Given that the rural banks contribute significantly to socio-economic development of the rural economy through financial intermediation programs and more importantly their role in small and medium enterprises (SMEs) development in the informal sectors of urban areas, the sustainability of these rural financial institutions is critical.

Quantitative research design was adopted for this study and a sample of 15 rural banks was selected based on availability, accessibility and consistency of their annual audited financial reports for the 2011 to 2015 financial years. Secondary data in the form of treasury management ratios was used. Random effect panel regression methodologies were relied upon for estimation and analysis of data. Four treasury management ratios selected are current ratio, cash to deposit ratio, loan to deposit ratio and loan to asset ratio. Return on equity (ROE) was used as a proxy for profitability. Natural logarithm of all these variables was taken so as to ensure standardization of measurement. Random effect panel regression methodologies were relied upon for estimation and analysis of data.

The study reports that current ratio has a positive significant influence on profitability while cash-deposit ratio has negative but insignificant effect. Again, loan-deposit ratio related positively with profitability at insignificant level whereas loan-asset ratio impacted significantly negative on profitability. Implications resulting from these findings indicate that liquidity management systems, credit risk management systems and capital structure management decisions in the rural banking sector require the attention of stakeholders especially managers of these financial institutions. A review of these systems is urgently needed for improved performance and stability.

Recommendations

Evidence gathered by the researcher based on the findings of the study makes the following recommendations eminent.

1. The study found a positive significant impact of current ratio on profitability. This must be consolidated and prudent management of current assets is recommended. Banks should ensure that their current assets are always in excess of current liabilities so that meeting short-term obligations may not pose challenging.
2. The study reported that cash-deposit ratio associated negatively with profitability, although the relationship was not significant. Regulatory institutions are advised to review capital adequacy requirement periodically so that it does not become profitability and sustenance threatening tool for the rural banks.
3. Further, the study revealed that a strongly negative influence on profitability by loan-asset ratio. It is recommended against this finding that capital structure decisions must be made in line with liquidity and credit management policies of the banks in order that debt ratios do not rise excessively as may cause financial risk and rigidities in the banking system.

Suggestions for further research

The following areas are suggested for further research work.

1. The present study covered five-year period from 2011 to 2015 for fifteen selected banks, further studies can replicate the same study by expanding the period and the sample number of banks so as to complement results produced in this study.
2. Further studies can focus on the effects of other variables that can affect profitability performance but which were not included in this study such as credit risk management indicators.
3. The same study can be conducted using data from other financial institutions such as savings and loans companies, credit unions and other microfinance institutions so that studies on treasury management and profitability can be empirically be deepened.
4. Depending on availability of data, purely time series regression methodologies can also be applied in future studies.

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