The Performance of Private Wealth Management in Indonesia

Abstract

The purpose of this paper is to highlight the impact of the performance of private wealth management (PWM) on the growth of retail banking in Indonesia. The variables used are bank's competitiveness, risk management, performance of private wealth management, and growth of retail banking business. The data were collected from 60 respondents from 32 banks over five months, from October 2018 to March 2019. Using partial least square path modeling, the analysis shows that the performance of private wealth management has an impact on the growth of retail banking sector in Indonesia. Bank competitiveness and risk management affect the performance of personal wealth management and have an impact on the growth of the retail banking business. Bank competitiveness is the variable that most influences the performance of private wealth management in Indonesia. This research found that market share is the most significant indicator of bank competitiveness. For risk management, significant indicators are the level of bank confidence, increased bank competitiveness, and the creation of new products. In the performance of the private wealth management variable, the most significant indicator is the revenue fee-based income. For the growth of retail banking business, a clear indicator is profit growth.

1. Introduction

The growth of banking indicators in terms of assets or profit has become very important to the Indonesian government. In terms of business performance, domestic banking recorded an improved achievement for the last five years, the position of the third-party fund per November 2017 reaching IDR5.182 trillion. This position almost increased 1,5 times compared with the position in 2013, which amounted to IDR3.655 trillion. Wealth management segment, that is the individual segment with tearing portfolio customer more than 500 million, had a larger proportion with positive growth from year to year since 2013.

The average growth of portfolio customer wealth segment (2014-2016) is 11.36% with the highest growth occurring in 2014 (15.51%). Growth nominal third-party fund slightly decreased in 2015 (6.82%); however, it rebound in 2016 (11,75%). Nominal account position per November 2017 showed growth of 10.26%. The average nominal thirdparty fund wealth segment during 2013-2016 accounted for 54.42% of all account individual third-party fund in commercial banks. The portion of portfolio third-party fund wealth segment position per November 2017 is the biggest during five years that is 56.44% of all individual third-party fund in the commercial bank.

The average growth of the number of customer accounts in wealth segment (2014-2016) was 8.62% with the highest growth occurring in 2014 (16.18%). The growth in accounts begun to decline while entering the year 2015, the position per November 2017 showed the growth of account numbers of only 1.81%. The middle portion of wealth account during 2013-2016 controlled only 0.14% of all individual accounts in the general bank. The position of wealth accounts per November 2017 was only 0.11% of all third-party fund individual accounts in the general banks. The average balance per account in wealth segment was IDR16.6 billion, while the average balance per account in the mass segment was IDR18.7 million.

Although the amount of wealth on the accounts was small, however, the nominal amount of wealth segment controlled 56.44% of total third party fund in the general banks. It is shown that the segment has given a positive contribution. It is aligned with the research by Chang and Tsai (2015), using a hybrid approach with five dimensions – service, performance, professionalism, risk control, and trust. The five dimensions were used to measure the performance of Private Wealth Management (PWM), managing the wealth segment.

PWM is one of the individual banking segments with significant potential relating to the increase of fee-based income. PWM services covered investment management, personal financial planning, wealth advisory, taxation planning, and estate planning. The scope of PWM practices had the connotation to be a personal and consultative service by the private bankers. PWN managers are seeking to assist their clients in pursuing their objectives. Moreover, PWM is closely related to investment management, which takes into consideration the individual and family financial situation interactively (Jennings, 2015). In Indonesia, PWM has an important role because many people are trapped in investment fraud (Hidajat et al., 2020) and illegal online loans (Hidajat, 2019).

Wealth segment will generally promote the growth of banking revenue through fee-based income (FBI), although not explicitly expressed by Lepetit et al. (2008) and Hidayat et al. (2012). The same applied to net interest income (NII) where this contribution to the wealth segment is not explicitly expressed by Nguyen (2012). Although it is not something new in Indonesia, PWM has not received much attention. This situation changed at the end of 2016, at the introduction of tax amnesty policy. This taxation policy was introduced in response to the efforts of the Indonesian Government to continue create positive economic growth, which in its course will require fiscal funding in a substantial amount.

PWM business is part of the competition in the banking sector. This research describes the increasing number of banks in Indonesia that provide PWM service. The present competition in the banking industry is interesting to observe. Boyd and De Nicoló (2005) stated that competition in the banking industry involves, not only interest rate and credit business model, but also credit risk, which is part of the risk management model. Academic literature and actual condition in the banking system showed the importance of awareness to implement risk management in the banking sector (Keeley, 1990). The risk management system of a bank is a neutralizing factor of credit expansion, reducing factor of unfair competition, and increased banking stability (Jimenez et al., 2007).

Boyd and De Nicoló (2005) brought about the “riskshifting” paradigm. The argument suggested that risk management may affect the bank’s competitiveness by considering the profitability or performance of a bank. Another research suggested that risk management system is measured by loan-to-asset ratio factor. This factor included bank-specific risk by taking into account the investment risk. Empirically, when measuring bank risk, there may be an unexpected result. Thus, attention should be paid by the bank manager to the result as a warning to minimize more expansive behavior and to be more prudent (Debrah, 2007).

Martínez-Sánchez et al. (2016) suggested that the risks of financial institutions include external frauds, internal frauds, malicious damage on goods and services, technology failure, and other expected losses. Also, financial innovation is related to the risk, which may affect the performance stability of commercial banks, where the risk from financial innovation will have more significant impact compared with systemic risk (Chen and Lai, 2016). Beck et al. (2013) mentioned that competition in the banking sector had a broad impact on the economic stability of a country. Besides, in some aspect, this research suggested that the bank’s competitiveness showed a negative impact in terms of prudence and banking management policy alone. This research concluded that the increased competition in the banking industry resulted in increased risk behavior, increased contribution to liquidity risk of a bank, and increased risk of compliance.

Berger et al. (2009) proved that, in a bank facing increased competition, there is increased risk exposure along with the increased stability of the bank. Also, the research mentioned that the capital increase ratio must directly cover this increased risk exposure. The same was discovered by Mulyaningsih (2014). Further, research on competition in the banking sector mentioned empirical evidence of the increased competition in banking stability (Schaeck et al., 2009). In more detail, this research mentioned that the bank’s competitiveness would even offer increased systemic stability if appropriately executed by the regulator.

In practice, modern banking business is not only dependent on the organic business emphasizing the intermediary function, but oriented to other revenue sources. It is part of the development of marketing theory, which is empirically proven to improve banking performance. Based on Lee et al. (2010), the profitability of financial institutions depends not only of the frequency of financial transaction, but also of the satisfaction level of its customers. Also, research by Ang (2010) suggested that condition of the banking industry in Asia was very fragmented so that a precise segmentation is necessary to the intended market, besides the quality of private bankers, who must have a good reputation.

In the middle of the dynamic potential of the world’s economy, especially in South East Asia, the current transformation of the global banking industry has resulted in increased attractiveness of the industry compared with conventional banking business, which has so far emphasized credit. It is part of the credit risk, which should be taken into account and faced by the banks, despite the improved stability with a decrease in non-performing loans (NPL). However, NPL remains a significant challenge for credit growth (Price Waterhouse Coopers, 2017).

In the dynamic banking industry, regulation by the government ensures that economic stability is maintained. In some countries, including Indonesia, government intervention in the banking industry is taken by enforcing the regulation and circular letters (Hidajat, 2020). In the last five years, the scheme has been implemented by the Financial Services Authority (FSA). This institution is the leading agency of the Indonesian Government, which supervises financial institutions, including banking, to ensure the liquidity, stability and sustainability of financial institutions (World Bank, 2013). Before the establishment of FSA and due to the economic crisis experienced by Indonesia in 1997, the Indonesian Government formulated a concept called Indonesian Banking Architecture (API). The concept was followed by regulation on risk management, as outlined in BASEL II.

In 2010, all banks in Indonesia were required to fulfill the provisions of pillar I, II, and III of BASEL II, requiring a bank to fulfill its minimum obligation 8% of Capital Adequacy Ratio (CAR). The first pillar of BASEL II established the requirement for a bank to add operational risk as weight in capital requirement (Heffernan, 2005). Besides, the Second and Third pillar of BASEL II requires the bank to develop an internal method for asset appraisal and to open the method to calculate CAR (Rosengard & Prasetyantoko, 2011).

It is noted that risk management is a factor closely related to competition and performance in the financial industry, especially banking. The bank as a profit-oriented institution must take into account the policy of risk management. For example, in credit risk, balance is necessary between the expansion and quality of credit in loan portfolio to ensure that NPL is controlled (Jiménez et al., 2007). This study will investigate the factors, which impact on the performance level of PWM, especially in terms of competitiveness and risk management and growth of the retail banking business.

2. Literature Review and Hypotheses

2.1. Bank’s Competitiveness and Performance of Private Wealth Management

Demsetz (1973) developed an efficient structural hypothesis, suggesting that profitability achieved by a bank is generated from efficiency. Therefore, this hypothesis showed that bank with higher efficiency has a higher capability to increase market share and size, which generated a profit surplus. The new indicator has been developed by Boone (2008) to measure the competition of the bank by taking into account the impact of efficiency on the performance relating to profitability and market share. It also considers that the condition of the competition will improve the performance of company efficiency and weaken the performance of an inefficient company. The outcome from the indicator by Boone may have positive or negative value where negative value shows a higher level of competition. In comparison, a more considerable positive value indicated a lower level of competition.

Chang and Tsai (2015) used a hybrid approach with five dimensions, which include service, performance, professionalism, risk control, and trust to measure the performance of PWM. In this scheme, the indicator of financial performance has no separate dimension. Revenue, the capacity of profitability and market share ratio is seen in the performance dimension. On the other hand, risk control dimension comprises a measurement of market risk, financial risk, movement of the business cycle in the industry, customer risk control, and confidentiality of financial and customer data.

According to the presentation by the above researcher, it is suggested that although the financial performance of PWM has no separate dimension, the profitability rests in the performance dimension. The profitability, as suggested by Boone (2008), will be affected by efficiency. Therefore the more efficient the performance of a bank for the existing competitive situation, more positive impact will support the performance of PWM profitability.

2.2. Risk Management and Performance of Private Wealth Management

The decision-making process in private wealth management should consider the risk management standard and should comply with the banking regulation in force. The investor should be supported by information on risk in determining its decision. It is shown in the research by Ferreira et al. (2017) using personal investment portfolio approach called fuzzy multiple-attribute. By analyzing the private wealth management portfolio at central banks in Switzerland with varying services, this research found that risk-free asset has a significant impact on the decisions of the banks managing private wealth management. This research was conducted by Cao et al. (2016) through processing a large amount of data from central banks in Switzerland.

Janssen and Kramer (2015) suggested the implementation of European regulatory sustainability requirement in managing private wealth management and transparency in determining risk management process. This article also discusses how risk management plays a vital role in private wealth management. The research above suggested that risk management has a positive correlation with the performance of private wealth management.

2.3. Bank’s competitiveness and Growth of Retail Banking Business

In measuring the growth of banking business, most measurement of banking business growth is based on the profit level of the bank. Parameters measure banking profit, such as rate of return on equity, rate of return on capital, and rate of return on asset (Debrah, 2007). In the banking industry, the competitiveness of a bank may have an impact on the profit level of the bank as the basis for measurement of business growth. Based on the previous research, conventional business model analysis described that production, marketing, investment, and other measures adopted by the organization create a bank’s competitiveness that is very much oriented toward the revenue increase. Increasing revenue, primary revenue per branch, is an essential feature of the business model analysis in a bank (Froud et al., 2016).

Rhee and Mehra (2006) also researched the strategic impact of bank’s competitiveness on the banking industry retail. In their study of 1000 retail banks in the United States, the researchers showed that operational strategy, marketing, and competitiveness has a significant impact on banking performance. More specifically, they posited that the higher the strategic level selected by a retail bank, the higher the performance of such a bank. Based on the previous research, it may be concluded that the competitiveness of a bank has an impact on the growth of the banking business.

2.4. Risk Management and Growth of Retail Banking Business

The main objective of banking management is to increase shareholder’s return. The objective has frequently resulted in increased cost and risk. It becomes part of the picture that risk management has an important role in minimizing the loss suffered by a bank (Adeusi, 2013). Zubairi and Ahson (2015) examined five banks in Pakistan using descriptive statistics and a regression model to measure the strength of risk management and its impact on the profitability of the banks. The model test was verified with Augmented Test Dickey Fuller. Based on the said research, it was suggested that risk management has an impact on the growth and profitability of a bank.

Adeusi (2013) divided risks in banking into three categories, namely, credit risk, market risk, and liquidity risk. It also suggested that there is a significant impact between the two ; the research shows that there is a significant correlation between the performance of bank and risk management. Risk management will generate better bank performance. Therefore, the research considers as very important for the bank to implement the principle of prudent risk management to maintain the asset bank and protect the interest of the investor.

Research by Apătăchioae (2015) on risk management, banking regulation, and banking growth also found that risk management and banking growth are correlated in accomplishing the objective set by the bank. Risk management is closely related to the expected performance with high-risk high-return correlation. Risk management is considered dependent on the expected performance and its objective in optimizing risk-return.

2.5. Performance of Private Wealth Management and Growth of Retail Banking Business

Performance indicators of PWM used in this research were FBI and NII, while the indicator of retail banking growth used revenue, return on asset (ROA), and market share. Firth et al. (2013) analyzed the correlation between non-interest income represented by non-traditional income ratio variable on the profitability and bank risk, ownership by the government, and change in government policy in 180 financial institutions in China from 1998 until 2007. Concerning the profitability, measured using ROA and ROE, the bank revenue from non-traditional activity has a negative correlation. However, if further analyzed, the portion of revenue from fee and commission even had a positive correlation on profitability. Non-traditional banking activity is not specifically from PWM business.

The research by Nguyen (2012) on the correlation between non-interest income and net interest margin also found a correlation between non-interest income and riskadjusted ROA. From 1997 to 2002, there was a negative correlation between non-interest income and ROA, but the correlation turned positive from 2003 to 2004. Research by Chen and Lai (2016) also discovered that the impact of diversification of bank revenue on ROA was positive and significant in the long term and positive, but insignificant in the short term. Meanwhile, Sufian (2012) proved that non-interest income had a positive impact on the ROA of 77 banks in South Asia.

2.6. Research Hypotheses

Based on the above review, the following hypotheses are formulated:

Figure 1: Research Framework

H1a: Bank’s competitiveness affects the performance of private wealth management.

H1b: Risk management affects the performance of private wealth management.

H2a: Bank’s competitiveness affects the growth of the retail banking business.

H2b: Risk management affects the growth of retail banking business.

H2c: Private wealth management affects the growth of the retail banking business.

H3a: Variable competitiveness affects the growth of the retail banking business through private wealth management.

H3b: Variable risk management affects the growth of the retail banking business through private wealth management.

3. Methodology

We conducted a survey of 32 banks offering in private wealth management. The data were collected from 60 respondents through an online survey and in-depth interview over five months, from October 2018 until March 2019. The majority of respondents are between 40 to 45 years old (51.7%), and are male (68%).

Table 1: Variable and Indicator

This research uses Partial Least Square (PLS) as an analysis tool. PLS is the model, which enables proper measurement to deal with the limitation of sample number (Hair et al. 2017). In this research, there is only a small number of banks in Indonesia engaged in Wealth Management due to the limited sample, thus the PLS model is selected to measure respondents’ questionnaire answers.

4. Results and Discussion

This section used two approaches for reflective model evaluation. First, we calculated the composite reliability, which must be higher than 0.70 or at least not less than 0.60 (Fornell & Larcker, 1981). Second, we analyzed the standardized loading factor to assess the reliability of each item for each indicator. It must be above 0.70 or at least not lesser than 0.40 (Henseler et al., 2009: 299). The results in Table 2 show that all the indicators used are reliable.

Table 2: Measurement Model Statistics

In addition to the internal reliability of the measurement model, it is also necessary to assess bias in the research and construct validity. The method used to evaluate the bias and construct validity was discriminant validity. We used the Fornell-Larcker (1981) criteria based on a simple idea that the indicator must be capable of explaining the dimension of particular research variable. These criteria were verified if the quadratic root of AVE for each research variable is much greater than the correlation of Pearson variable and/or dimension. To ensure the convergent validity of a construct, the AVE should exceed 50, showing that the research variable explained at least 50% of indicator variances (Götz et al., 2009). The result supports the convergent validity and discriminant of each reflective indicator.

R² is used to determine the variance percentage shown by the endogenous latent variable, which predicted the endogenous latent variable. As a size of predictive strength, R² value can be interpreted in the same way as in the multiple regression analysis. The value 0.913 shows a “Very Strong” model (Chin, 1998: 323), verification of the model’s ability to predict the endogenous variable by calculating Q² Stone-Geisser. A positive value of Q² proved that the value observed is reconstructed appropriately and that the model has predictive relevance (Henseler et al., 2009). The value 0.02 shows little predictive ability, value 0.15 shows medium predictive ability, while the value 0.35 shows considerable predictive ability.

To establish the extent to which each predictive variable contributes to the variance explained on the endogenous variable, we evaluate the significance, amount, and sign of individual path coefficient β, which can be interpreted in the same manner with standardized beta from ordinary smallest quadratic regression. Table 4 reports the model structural coefficient β for each inner model path and t-test value and significance. It also provides a summary of support for our set of hypotheses 1 and 2.

Table 4: Path Significance of Inner Model Correlations

The analysis found that bank’s competitiveness and risk management have positive and significant impact on the performance of private wealth management. The variable with the most impact is the bank’s competitiveness. It was found that all bank’s competitiveness, risk management and performance of private wealth management have positive and significant impact on the growth of the retail banking business.

Table 3: Discriminant Validity Test

To examine whether the private wealth management variable intervenes fully or partially, the Sobel test was carried out. Indirect impact test using the Sobel test is illustrated in Table 5.

Table 5: Intervening Impact

The indirect impact test discovered greater t values compared with t value table (2.045); it may be concluded that there is a significant indirect impact of the bank’s competitiveness, and risk management on the growth of retail banking business through the performance of private wealth management.

Bank’s competitiveness and risk management variables have a direct impact on the growth of the retail banking business. Therefore, it may be concluded that the performance of the private wealth management variable is a partial intervening variable.

Below is the recapitulation of direct and indirect impact and total competitiveness and risk management variable and the performance of private wealth management on the growth of the retail banking business.

The analysis found that the variable with the most impact on the growth of retail banking business is risk management. The least impact is the performance of private wealth management since this variable is the intervening variable. Risk management influences wealth management performance and bank business growth. However, this relationship still needs to be studied because there is a positive relationship between bank risk and bank size (Tran, Do, & Nguyen, 2020).

To further improve banks’ performance, good corporate governance is needed. According to Khanifah et al. (2020), corporate governance in the banking system plays a unique role because of the uniqueness of banking organizations. For good governance, good management capabilities are needed (Napitupulu et al., 2020).

5. Conclusion

The results of the analysis indicate that bank competitiveness and risk management have a positive and significant effect on the performance of personal wealth management. The most influential variable is bank competitiveness. Bank competitiveness, risk management, and personal wealth management performance have a positive and significant effect on the growth of the retail banking business. There is a significant indirect effect of bank competitiveness and risk management on the growth of the retail banking business through the performance of personal wealth management. Bank competitiveness and risk management have a direct effect on the growth of the retail banking business. In this case, the performance of the personal wealth management variable becomes an intervening variable. The analysis results also found that the variable that most influences the growth of the retail banking business is risk management, while the least influence is the performance of personal wealth management because this variable is intervening.

Based on the conclusions above, some significant recommendations follow. First, the bank should take into consideration the growth of the portfolio to increase the market share. Second, in the management of a bank, especially retail banking business, risk management is vital, especially for the above three elements. Third, advisory service to the customer and human resource capacity should matter to the relationship manager in providing financial advisory services to the customers. Fourth, retail banking business will grow if the profit growth is positive. Lastly, the research explains that positive change in bank’s competitiveness and risk management will be capable of increasing the performance of wealth management and positively impact on the growth of retail banking business with the intervening variable on the performance of wealth management.