Research on audit supervision of internet finance

Liu, Hua; Ge, Sheng Article Research on audit supervision of internet finance International Journal of Financial Studies Provided in Cooperation with: MDPI – Multidisciplinary Digital Publishing Institute, Basel Suggested Citation: Liu, Hua; Ge, Sheng (2020) : Research on audit supervision of internet finance, International Journal of Financial Studies, ISSN 2227-7072, MDPI, Basel, Vol. 8, Iss. 1, pp. 1-15, https://doi.org/10.3390/ijfs8010002 This Version is available at: https://hdl.handle.net/10419/257670 Standard-Nutzungsbedingungen: Die Dokumente auf EconStor dürfen zu eigenen wissenschaftlichen Zwecken und zum Privatgebrauch gespeichert und kopiert werden. Sie dürfen die Dokumente nicht für öffentliche oder kommerzielle Zwecke vervielfältigen, öffentlich ausstellen, öffentlich zugänglich machen, vertreiben oder anderweitig nutzen. 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If the documents have been made available under an Open Content Licence (especially Creative Commons Licences), you may exercise further usage rights as specified in the indicated licence. https://creativecommons.org/licenses/by/4.0/ International Journal of Financial Studies Article Research on Audit Supervision of Internet Finance Hua Liu 1and Sheng Ge 2,* 1School of Finance, Nanjing Audit University, Nanjing 211815, China; [email protected] 2School of International Education, Nanjing Audit University, Nanjing 211815, China *Correspondence: [email protected] Received: 29 September 2019; Accepted: 27 December 2019; Published: 15 January 2020   Abstract: Internet finance is a new form of finance that applies capacities found on the Internet to the traditional financial industry. However, at the present stage, internet finance is faced with many problems, such as overly rapid development and non-standard operation. This paper adopted the evolutionary game theory as the analysis tool to design an evolutionary game model of government audit supervision of Internet finance, and analyzed the evolutionary stability of the strategies used by Internet financial institutions and government financial audit supervision departments. A simulation calculation was carried out by placing the calculation experimental method “Scenario–Coping”, which simulated the initial probability of different strategies adopted by both parties of the game and evaluated the influence of changing the penalty intensity of Internet financial institutions’ violation on the outcome of the evolutionary game. Based on the simulation analysis, the paper provided policy suggestions on strengthening audit supervision and promoting its sustainable development from three aspects: strengthening the construction of the Internet financial credit information system, improving Internet financial laws and regulations, and improving the early warning level of Internet financial credit risk. Keywords: internet finance; government auditing; evolutionary game; system simulation; computing experiment 1. Introduction In recent years, driven by the needs of financial markets, the Internet has developed rapid systems and applications useful to the financial industry. As a result, internet finance has sprung up like bamboo shoots after a rain, and has become an emerging force in China’s financial market. In 2013, the first year of the Internet finance era, Internet thinking swept through traditional forms and structures of finance like the Renaissance. Most traditional financial institutions including banks, securities and fund companies, and insurance companies started to make significant arrangements to retain their competitive edge, while the e-commerce giants such as Alibaba, Tencent, Baidu and Sina began to create their own business models hoping to establish their own Internet empire. With the traditional business models and financial structure being challenged, a financial “New Normal” in the context of “Internet Plus” was being formed. Although all levels of the Chinese government encourage innovative development of Internet finance, great risks still lie ahead since both the Internet and finance are industries with high risks. A combination of both industries poses even higher risks. Internet finance is hence faced with a wide range of risks including systematic risk, liquidity risk, credit risk, technological risk as well as operational risk. Thus, strong government audit supervision is needed to ensure the healthy development of Internet finance. Internet finance is supported by Internet technology and is governed by the market. Higher risks seem inevitable. The rapid development of Internet finance brings about moral hazards and adverse Int. J. Financial Stud. 2020,8, 2; doi:10.3390/ijfs8010002 www.mdpi.com/journal/ijfs Int. J. Financial Stud. 2020,8, 2 2 of 15 selection in information safety. At present, the Internet financial credit information system in China is yet to be perfected and the legal restraint on Internet finance is largely flawed. As a result, problems such as Internet fraud and credit default arise (Hong and Cao 2014). In terms of Internet financial credit risk, Duarte et al. (2010) analyzed the role credit plays in financial transactions and proved that even in countries with sound legal systems, the problem of credit was still unavoidable ( Duarte et al. 2010). Agarwal and Hauswald (2008) contended that online financing platforms played a positive role in helping small and micro-sized enterprises solve financing problems, because small enterprises were unable to obtain loans from commercial banks due to their failure to provide public credit ratings, and they could only turn to the online loan market for help (Agarwal and Hauswald 2008). By virtue of its unique role, the peer-to-peer (P2P) network loan has emerged on a large scale in the world and become a supplement to traditional finance. Economides (2001) pointed out that this new form of borrowing reduced transaction costs and greatly expanded the coverage of financial services (Economides 2001). Empirical research on P2P online lending shows that, in terms of the characteristics of borrowers, the main objects of P2P loans are short-term and small borrowers who are rejected by traditional financial institutions because of the inaccuracy of credit information or the failure to provide sufficient collateral, and most of them are from the working class with poor credit ( Zhuang and Zhou 2015 ). Based on order statistics released “on credit”, so far the average loan amount is about 7371.795 Yuan, borrowing on average to attract investors to participate in the tender number is 19.9148, average borrowing success rate is 0.3252, the duration of the loan is an average of 6.5 months, and most of the P2P borrowers’ loan time limit is in the following 1 year (Guo 2012; Wang and Liao 2014). The top priority in maintaining financial stability is to prevent financial risks. However, the majority of domestic research focuses on introducing various new models of Internet financial loan, whereas financial auditing in China mainly focuses on investigating cases that have violated laws and rules. There have been few in-depth discussions on the early warning of financial risks. At present, the priority of financial auditing is to improve laws and regulations, guarantee the quality of assets, conduct effective internal control, and improve the authenticity of accounting information (Liu 2002,2013). In current research on the early warning of financial risks, the Probit Model, the Sachs-Tornell-Velasco (STV) cross-sectional regression model, and the Kaminsky–Lizondo–Reinhart (KLR) signal approach have been widely accepted (Zhang and Sun 2003). With the development of financial auditing, new approaches such as VaR and Pressure Test have been adopted (Xu and Xu 2010). However, a comprehensive research on the early warning of Internet financial risk is still lacking. In 2017, Liu Hua and Zhang Jie took the P2P online lending platforms as an example and established the P2P online lending credit risk evaluation index system within the framework of their “auditing immune system” analysis. They conducted an empirical study on 10 P2P online lending platforms by combining the entropy weight method and grey correlation integrated evaluation model, and proposed an auditing and governance strategy to prevent Internet financial risk (Liu and Zhang 2017). Computational experiment finance (CEF) is a simulation method that aims to reveal the macro operational law of the financial market by (1) setting up the specific learning modes and behavioral mechanisms of microscopic financial bodies, and (2) including the communication and interaction among microscopic financial bodies under a given financial system and financial market with the aid of modern computer science and technology (Lebaron 2000;Levy et al. 2000). Arthur et al. (2007) pioneered computing experiment finance (Arthur et al. 2007). They conducted research on the stock market by substituting a computer simulation model based on Agent for the original mathematical analytic model, and established the so-called Artificial Stock Market (ASM). Their work marked the birth of a new branch of finance—Computing Experiment Finance Based on Agent. Zhang et al. (2003) was the first Chinese scholar who systematically introduced the theoretical foundation, basic concepts and research areas of Computing Experiment Finance. Zhang explained the modeling approach by using the Santa Fe Institute’s ASM as an example, and explored its relationship with other branches such as the Financial Market Microstructure Theory in Modern Finance and Behavioral Finance Int. J. Financial Stud. 2020,8, 2 3 of 15 ( Zhang et al. 2003 ). Many scholars have since applied the approach of the computing experiment to the field of financial risk supervision. P é rez-Mart í n and Vaca (2017) calculated the credit risk of banks in housing mortgage and the mortgage default rates by using computing experiment, and compared the computational efficiency of different statistical and data-mining methods (P é rez-Mart í n and Vaca 2017). Liu and Chen (2018) adopted evolutionary game theory as the analysis tool to design the evolutionary game model of collaborative governance and auditing of local governments’ debts, and analyzed the evolutionary stability of the strategies of the audit offices and local governments (Liu and Chen 2018). On this basis, the simulation calculation was carried out by using a calculation experimental method “Scenario–Coping”, which simulated the initial probability of different strategies adopted by both parties of the game, and evaluated the influence of the soundness of three sub-mechanisms on the outcome of the evolutionary game. In sum, study abroad of P2P lending not only carried out thorough research in theory ( Mr Stiglitz and Weiss 2016 ), but also from the perspective of empirical analysis of the data model calculation and practical test detection (Yum et al. 2015), the risk of overall lending to P2P networks, and the success rate of the borrower and the lender investment decision problem has received relatively effective research and demonstration (Stiglitz and Weiss 2016;Yum et al. 2015). However, the majority of research on Internet finance focuses on specific problems in actual business operation. Research on the early warning of Internet financial credit risk has started relatively late and focused mostly on interpreting of the concept of Internet financial risk, and summarizing and evaluating western early warning theories. Although many Chinese scholars have optimized the early warning model according to specific national conditions, there a systematic and quantitative analysis is still lacking due to insufficient statistics and materials available regarding the supervision of Internet financial risk. In such a context, we adopted the computing experiment approach, and analyzed the evolutionary game of the government audit supervision of Internet finance. Based on the calculation experimental method “Scenario–Coping”, we extracted correlative factors of both parties of the game, and simulated the initial probability of different strategies adopted by both parties of the game, and evaluated the influence of changing the penalty intensity of Internet financial institutions’ violation on the outcome of the evolutionary game. Our results are meaningful for holding the bottom line of preventing systematic financial risk and improving the healthy development of China’s Internet finance. 2. Materials and Methods 2.1. Behavioral Analysis of the Government Audit Supervision of Internet Finance In the context of “Internet Plus”, Internet mercantile services rapidly integrate with finance, and Internet finance operation modes overlap with traditional finance in many fields. Although it is a combination of finance and Internet technology, Internet finance is still finance by nature and follows the functions of finance. Thus, it runs with not only the typical risks in traditional finance, but also its own unique risks. Banks and other financial institutions pay special attention to systematic risk, liquidity risk, and credit risk. Internet finance institutions should do the same, especially for credit risk, since Internet financial transactions are still based on credit risk pricing. Problems such as information asymmetry and information leakage in traditional finance are still ubiquitous in Internet finance. These risks can be increasing since Internet finance is still in an early stage in China and the related laws and regulations are a work in progress. For example, a P2P online lending platform can face a high credit risk. A typical kind of fraud is the “Ponzi Scheme”, which, in simple terms, is a fraudulent investing scam promising high rates of return with little risk to investors. The Ponzi scheme generates returns for earlier investors by acquiring new investors through creating a false impression that the company actually makes profits. Once there are no new investors, or the funds contributed by the new investors are not sufficient to pay the “interest” of the first investors, the “Ponzi Scheme” will not be able to continue. Int. J. Financial Stud. 2020,8, 2 4 of 15 With the rapid development of Internet finance, many problems arise, such as information asymmetry, lack of information transparency, lack of supervision, and information technology risk. In order to prevent these risks, the China Banking Regulatory Commission has established the principle of “innovative supervision, moderate supervision, classified supervision, collaborative supervision” and “the combination of government supervision and self-regulation”. Even so, the current supervision of Internet finance is inadequate. Some unscrupulous institutions play games with the legal system and exploit the holes in regulations. Some risk-control institutions conduct misleading promotion and illegal financing under the disguise of Internet finance. As a result, Internet finance supervision requires an authoritative, independent, and unified supervision system. Such requirements can only be met by Internet finance auditing. Liu Jiayi, the former Auditor General of the China National Audit Office, once indicated to the National Auditing Conference that “modern government audit is the immune system for the functioning of the economy and society”, from which the theory of the government auditing immune system is derived. The establishment of Internet finance audit supervision system could help avoid the aimlessness in government auditing processes, ensure reasonable allocation of audit resources, and improve the efficiency of auditing to a large extent. In this paper, we aimed to provide a new method for the establishment of an Internet finance audit supervision system by combining the theoretical framework of audit “immune system” and of Internet finance supervision (Figure 1). Int. J. Financial Stud. 2020, 8, x FOR PEER REVIEW 4 of 15 supervision” and “the combination of government supervision and self-regulation”. Even so, the current supervision of Internet finance is inadequate. Some unscrupulous institutions play games with the legal system and exploit the holes in regulations. Some risk-control institutions conduct misleading promotion and illegal financing under the disguise of Internet finance. As a result, Internet finance supervision requires an authoritative, independent, and unified supervision system. Such requirements can only be met by Internet finance auditing. Liu Jiayi, the former Auditor General of the China National Audit Office, once indicated to the National Auditing Conference that “modern government audit is the immune system for the functioning of the economy and society”, from which the theory of the government auditing immune system is derived. The establishment of Internet finance audit supervision system could help avoid the aimlessness in government auditing processes, ensure reasonable allocation of audit resources, and improve the efficiency of auditing to a large extent. In this paper, we aimed to provide a new method for the establishment of an Internet finance audit supervision system by combining the theoretical framework of audit “immune system” and of Internet finance supervision (Figure 1). Figure 1. “Immune System” analysis framework of Internet finance government audit supervision. As Figure 1 shows, the way government auditing acts as an “immune system” is to enhance immunity by discovering problems, solving problems and perfecting mechanisms, with each step closely linked with and mutually dependent on the others. We applied the theory of “immune system” to the process of Internet finance audit supervision. Adopting a problem-oriented approach, we: (1) discovered the problems and risks of Internet finance due to excessive growth and lack of supervision; (2) analyzed the relationship between Internet financial institutions and financial audit offices as two parties of the game as well as their gains and losses through the approach of computing experiment and case study of financial supervisory authorities; (3) revealed different strategies chosen by both parties under different circumstances in order to bring the defense capability of the “immune system” into full play; and, (4) suggested a more targeted policy mix for Internet finance audit supervision so as to give early warning to Internet financial risks. 2.2. Evolutionary Game Analysis of Internet Finance Government Audit Supervision A behavioral analysis of Internet finance government audit supervision shows that there is information asymmetry between Internet financial institutions and financial audit offices. In accordance with the various audit strategies adopted by audit offices, Internet financial institutions choose to, or not to, comply with laws and regulations based on their own situations. The behaviors Figure 1. “Immune System” analysis framework of Internet finance government audit supervision. As Figure 1shows, the way government auditing acts as an “immune system” is to enhance immunity by discovering problems, solving problems and perfecting mechanisms, with each step closely linked with and mutually dependent on the others. We applied the theory of “immune system” to the process of Internet finance audit supervision. Adopting a problem-oriented approach, we: (1) discovered the problems and risks of Internet finance due to excessive growth and lack of supervision; (2) analyzed the relationship between Internet financial institutions and financial audit offices as two parties of the game as well as their gains and losses through the approach of computing experiment and case study of financial supervisory authorities; (3) revealed different strategies chosen by both parties under different circumstances in order to bring the defense capability of the “immune system” into full play; and, (4) suggested a more targeted policy mix for Internet finance audit supervision so as to give early warning to Internet financial risks. Int. J. Financial Stud. 2020,8, 2 5 of 15 2.2. Evolutionary Game Analysis of Internet Finance Government Audit Supervision A behavioral analysis of Internet finance government audit supervision shows that there is information asymmetry between Internet financial institutions and financial audit offices. In accordance with the various audit strategies adopted by audit offices, Internet financial institutions choose to, or not to, comply with laws and regulations based on their own situations. The behaviors of both entities form a bounded rational dynamic game. For the convenience of adopting a game model for analysis, and on the basis of behavioral characteristics of Internet financial institutions and financial audit offices as well as the status quo of Internet finance government audit supervision, we propose the following hypotheses: 1. As an endogenous system of national governance, government auditing plays a crucial role in preventing Internet financial risks and safeguarding national financial security ( Cao and Xiong 2018 ). As one party of the game, “financial audit offices” are national audit departments which carry out auditing and supervision on the other party to the game (Internet financial institutions) on behalf of the public and the central government. The decisions made by government financial audit are in real time, rather than on a regular basis, which means auditors are able to make decisions at any time based on the situations of Internet financial institutions, and carry out audit immediately. This hypothesis guarantees the consistency of the game process. 2. As another party of the game, “Internet financial institutions” are companies involved in providing financial services using Internet technology. The healthy development of Internet finance needs supervision from government audit. Their legitimate business operations help to boost local economic development and enhance the effectiveness of government audit offices (Zhou 2017). If compliance is not emphasized, the subjects of liability will be held accountable and penalized after audit offices conduct audits and discover problems. These financial institutions subsequently will be unable to make profits from business operations and might receive harsh penalties. Based on the above hypotheses, game utility matrix for both parties of the game under different strategy choices is shown in Table 1and the variables therein are set as follows (all the variables used in the evolutionary game matrix are indexed in Appendix Aat the end of the present paper): 1. Suppose the profits made by Internet financial institutions through legitimate business operations are I 1 , their expenditure is C 1 , bonuses, the rewards gained through legitimate business operations are D1, and fines imposed by audit offices due to non-compliance are L. 2. Suppose the expenditure for carrying out audit supervision by the financial audit supervisory departments is C 2 ,and the social economic benefits resulting from the cooperation in audit supervision between Internet financial institutions and financial audit supervisory departments are I 2 . Due to the scarcity of auditing resources, it is impossible for government audit offices to focus solely on Internet financial institutions. The compliance of the latter helps to create a positive environment for financial operations, which in turn reduces the pressure on financial audit departments and generates an opportunistic benefit (D2). 3. Suppose the probability of choosing “compliance” and “noncompliance” by Internet financial institutions in the game is x (where 0 <x<1) and 1 − x, respectively; the probability of carrying out “audit supervision” and not performing this function by the financial audit offices is y (where 0<y<1) and 1-y(respectively). We established the evolutionary game model using the Game Utility Matrix of Internet Finance Government Audit Supervision: Int. J. Financial Stud. 2020,8, 2 6 of 15 Table 1. Game utility matrix of Internet finance government audit supervision. Strategies Chosen by Both Parties of the Game Financial Audit Supervisory Departments Carrying out Audit Supervision y not Carrying out Audit Supervision 1 −y Internet financial institutions compliance x I1−C2+D1, I2−C2I1−C1, D2 noncompliance 1 −x−L, −C20, 0 2.2.1. Utility Model of Internet Financial Institutions When Internet financial institutions choose the strategy of “compliance”, the utility is set as u11; when they choose the strategy of “non-compliance”, the utility is set as u12. Thus, the following equations can be proposed: u11 =y(I1−C1+D1) + (1−y)(I1−C1)(1) u12 =−yL (2) If Internet financial institutions combine both strategies, the average expected utility of both strategies is set as u1. The following equation can be proposed: u1=xu11 + (1−x)u12 (3) 2.2.2. Utility Model of Financial Audit Supervisory Departments When financial audit supervisory departments choose to carry out audit supervision, the utility is set as u 21 ; when they choose not to carry out audit supervision, the utility is set as u 22 . The following equations can be proposed: u21 =x(I2−C2) + (1−x)(−C2)(4) u22 =xD2(5) If financial audit supervisory departments combine both strategies, the average expected utility of both strategies is set as u2. The following equation can be proposed: u2=yu21 + (1−y)u22 (6) 3. Results According to the Malthusian dynamic equation, the dynamic change rate of the probability of Internet financial institutions choosing the strategy of “compliance” is dx dt , the dynamic change rate of the probability of financial audit supervisory departments choosing to carry out audit supervision is dy dt , and the following replicator dynamics equations can be proposed: dx dt =x(u11 −u1) = x(1−x)(yD1+I1−C1+yL)(7) dy dt =y(u21 −u2) = y(1−y)(xI2−C2−xD2)(8) Equations (7) and (8) show the rate and direction of game learning by Internet financial institutions and financial audit supervisory departments. When both replicator dynamics equations equal zero, the Internet finance government audit supervision game achieves a state of relative stability and balance. If F(x) = dx dt = 0, F(y) = dy dt = 0, then x=C2 I2−D2 , y=C1−I1 D1+L (0 ≤C2 I2−D2≤ 1, 0 ≤C1−I1 D1+L≤ 1). According to the utility function of Internet financial institutions and financial audit supervisory departments, the variation trends of xand ycan be described as follows: Int. J. Financial Stud. 2020,8, 2 7 of 15 3.1. Analysis of Internet Financial Institutions Stability 1. When y=C1−I1 D1+L , F(x)≡ 0. Xis the evolutionary stability strategy of Internet financial institutions. 2. When y,C1−I1 D1+L , based on the stability theorem of differential equations and the nature of evolutionary stability strategy, it can be inferred that x∗ is the evolutionary stability strategy if F(x∗)0<0. Thus, when y>C1−I1 D1+L , F(x)0 x=0> 0, F(x)0 x=1< 0, x= 1 is the evolutionary stability strategy of Internet financial institutions; when y<C1−I1 D1+L , F(x)0 x=0< 0, F(x)0 x=1> 0, x= 0 is the evolutionary stability strategy of Internet financial institutions. 3.2. Analysis of Financial Audit Supervisory Departments’ Stability 1. When x=C2 I2−D2 , F(y)≡ 0. Yis the evolutionary stability strategy of financial audit supervisory departments. 2. When x,C2 I2−D2 , based on the stability theorem of differential equation and the nature of evolutionary stability strategy, it can be inferred that y∗ is the evolutionary stability strategy if F(y∗)0<0. Thus, when x>C2 I2−D2 , F(y)0 y=0> 0, F(y)0 y=1< 0, y= 1 is the evolutionary stability strategy of financial audit supervisory departments; when x<C2 I2−D2 , F(y)0 y=0< 0, F(y)0 y=1> 0, y= 0 is the evolutionary stability strategy of financial audit supervisory departments. 3.3. Evolutionary Stability Analysis of Both Parties of the Game Based on the above strategy, evolutionary stability analysis and the replicator dynamics equations of both parties, the following graph can be drawn. From Figure 2, it can be determined that there are five equilibrium points, that is, A(0,1), B(1,1), C(1,0), D(0,0) and E( C2 I2−D2 , C1−I1 D1+L ). Among them, A(0,1) and C(1,0)are unstable equilibrium points, E( C2 I2−D2 , C1−I1 D1+L ) is the saddle point, and B(1,1) and D(0,0) are evolutionarily stable equilibrium points. An analysis of the five equilibrium points shows that when financial audit supervisory departments carry out audit and supervision extensively, Internet financial institutions will choose “compliance” as the optimal strategy after a certain period of time. Meanwhile, if Internet financial institutions choose compliance, it is certain that financial audit supervisory departments are willing to offer audit recommendations so as to enhance risk management of Internet finance and help them to gain more benefits from better governance. Int. J. Financial Stud. 2020, 8, x FOR PEER REVIEW 7 of 15 Thus, when LD IC y+ − > 1 11 , 0)( 0> ′=x xF , 0)( 1< ′=x xF ,1=xis the evolutionary stability strategy of Internet financial institutions; when LD IC y+ − < 1 11 , 0)( 0< ′=x xF , 0)( 1> ′=x xF , 0=xis the evolutionary stability strategy of Internet financial institutions. 3.2. Analysis of Financial Audit Supervisory Departments’ Stability 1. When 22 2 DI C x− =, 0)( ≡yF . Y is the evolutionary stability strategy of financial audit supervisory departments. 2. When 22 2 DI C x− ≠, based on the stability theorem of differential equation and the nature of evolutionary stability strategy, it can be inferred that * y is the evolutionary stability strategy if 0)( *< ′ yF . Thus, when 22 2 DI C x− >, 0)( 0> ′=y yF , 0)( 1< ′=y yF , 1=y is the evolutionary stability strategy of financial audit supervisory departments; when 22 2 DI C x− <, 0)( 0< ′=y yF , 0)( 1> ′=y yF , 0=y is the evolutionary stability strategy of financial audit supervisory departments. 3.3. Evolutionary Stability Analysis of Both Parties of the Game Based on the above strategy, evolutionary stability analysis and the replicator dynamics equations of both parties, the following graph can be drawn. From Figure 2, it can be determined that there are five equilibrium points, that is, A(0,1), B(1,1), C(1,0), D(0,0) and E( 22 2 DI C −,LD IC + − 1 11 ). Among them, A(0,1) and C(1,0)are unstable equilibrium points, E( 22 2 DI C −,LD IC + − 1 11 ) is the saddle point, and B(1,1) and D(0,0) are evolutionarily stable equilibrium points. An analysis of the five equilibrium points shows that when financial audit supervisory departments carry out audit and supervision extensively, Internet financial institutions will choose “compliance” as the optimal strategy after a certain period of time. Meanwhile, if Internet financial institutions choose compliance, it is certain that financial audit supervisory departments are willing to offer audit recommendations so as to enhance risk management of Internet finance and help them to gain more benefits from better governance. LD IC + − 1 11 22 2 DI C − Figure 2. Evolutionary phase diagram of Internet finance government audit supervision game. 3.4. Evolutionary Analysis of Model Parameters Figure 2. Evolutionary phase diagram of Internet finance government audit supervision game. Int. J. Financial Stud. 2020,8, 2 8 of 15 3.4. Evolutionary Analysis of Model Parameters The above analysis shows that the evolution of the gaming system can be driven towards the expected direction by changing the parameters of both parties under different strategy choices, followed by the change of C2 I2−D2 and C1−I1 D1+L , and the areas of Quadrangle ADCE and Quadrangle ABCE. The following explanations of the model are developed by taking cost, benefit and penalty as examples. 1. The parameter of cost. C 1 and C 2 represent the cost of choosing “compliance” by Internet financial institutions and choosing to carry out audit supervision by financial audit supervisory departments. As C 1 decreases, C1−I1 D1+L decreases and point E moves downward. The replicator dynamics phase diagram shows that, under such a condition, the area of Quadrangle ADCE decreases while the area of Quadrangle ABCE increases, which means there is a higher probability that the initial state is in Quadrangle ABCE and a higher probability that the gaming system will evolve to the equilibrium strategy (1,1). Similarly, as C 2 decreases, C2 I2−D2 decreases and point E moves towards the left, resulting in a higher probability that the gaming system will evolve to the equilibrium strategy (1,1). The above analysis shows that in the game of Internet finance government audit supervision, the lower the costs of both parties are, the higher the probability of the system converging to (1,1). 2. The parameters of benefit. I 1 and I 2 represent the benefit of choosing “compliance” by Internet financial institutions and choosing to carry out audit supervision by financial audit supervisory departments. As I 1 increases, C1−I1 D1+L decreases and point E moves downward. There is a higher probability that the gaming system will evolve to the equilibrium strategy (1,1). Similarly, as I 2 increases, C2 I2−D2 decreases and point E moves towards the left, leading to a higher probability that the gaming system will evolve to the equilibrium strategy (1,1). The above analysis shows that in the game of Internet finance government audit supervision, the higher the benefits of both parties are, the higher is the probability of the system converging to (1,1). 3. The parameter of penalty. L represents the penalty imposed on Internet financial institutions when they choose “noncompliance” and financial audit supervisory departments choose to carry out audit supervision. As Lincreases, C1−I1 D1+L decreases, C2 I2−D2 remains the same and point E moves downward, resulting in a higher probability that the gaming system will evolve to the equilibrium strategy (1,1). When financial audit supervisory departments carry out audit supervision and discover non-compliance of Internet financial institutions, the latter will face heavier losses and in turn they will have a stronger motivation to choose compliance so as to reduce losses. As a result, the system converges to (1,1). 4. Discussion To conduct in-depth research on the strategy evolution of both parties of the game and the influence relevant parameters have on the strategies of both parties, the College of Audit Officials of China National Audit Office and Nanjing Audit University collaborated to develop a proposal for Internet finance government audit supervision in June 2018. Field research had been conducted on the current situations of Internet finance government audit supervision in Jiangsu province. The initial value of the game model is set as the preset original data. The financial audit office in this region plans to conduct a special audit on Internet finance and the cost per month is 40,000 RMB. The social economic benefit resulting from the cooperation in audit supervision between Internet financial institutions and financial audit supervisory departments is 40,000 RMB per month. The compliance of the Internet financial institutions helps to create a positive environment for financial operations, which in turn reduces the pressure on financial audit departments and generates an opportunity benefit equal to 20,000 RMB per month. Field research has shown that most Internet financial institutions in this region expand their market and attract new clients by sacrificing profits to increase market share. Suppose the average monthly cost of the Internet financial institutions in this region for legitimate business operation is 50,000 RMB, and the profit they make from legitimate business operations is 40,000 RMB Int. J. 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