Research on Risk Assessment and Prevention Countermeasures of Internet Finance

Starting with the systematic risks and non‑systematic risks of internet finance, this paper analyses the causes and manifestations of these two types of risks respectively, and puts forward specific prevention and control measures for internet financial risks from 39 aspects.

Keywords: Internet; Finance; Risk; Prevention

Internet finance covers forms including third‑party payment, P2P micro‑credit, crowdfunding financing, e‑commerce micro‑loans, virtual currencies, and other online financial service platforms. Both the internet and finance are high‑risk industries, and internet finance formed by their integration bears even greater risks. According to statistics, more than 500 online lending platforms were launched in 2013. Behind its unregulated rapid expansion, however, the P2P online lending sector suffered a wave of platform closures. Data from Wangdai Zhijia shows that as of November 29, 2013, a total of 64 P2P online lending platforms encountered withdrawal difficulties, closures or fund absconding. Therefore, effective risk prevention and control is the top priority for the sound development of internet finance.

Systematic Risks

Causes

1. Lack of a clear industrial model;

2. Absence of supporting derivative services;

3. Shortage of a lender of last resort;

4. No ultimate risk underwriter;

5. Lack of are‑insurer;

6. Vacancy of the central‑bank‑like role in the internet finance industry.

Manifestations

1. Risk of system paralysis;

2. Risk of bad‑debt losses;

3. Risk of deterioration of the general market environment.

Non‑systematic Risks

Legal Risks

1. No legal norms for market access standards, capital flow and exit rules of internet financial enterprises;

2. Lack of legal provisions defining rights and obligations in internet financial transactions;

3. Absence of legal protection for the rights and interests of internet financial consumers;

4. Insufficient severe legal punishment for customer privacy information leakage;

5. Legal loopholes in illegal money‑laundering processes and methods;

6. Lack of specific legal anti‑money‑laundering measures;

7. Absence of legal notarization for trader identity authentication;

8. Shortage of legal guarantee for confirming the validity and legality of electronic contracts;

9. No legal basis for the legality of operational modes of internet financial enterprises;

10. Chaos of illegal public deposit absorption and illegal fund‑raising caused by legal deficiencies, blind spots, conflicts and dilemmas;

11. Lack of a unified legal supervision system for internet financial transactions;

12. Absence of legal provisions on verifying transaction evidence.

Manifestations

1. Criminal legal risks: crime of illegal absorption of public deposits.

2. Administrative legal risks: (a) securities‑related administrative illegal acts; (b) illegal fund‑raising‑related administrative illegal acts; (c) false advertising administrative illegal acts; (d) illegal business administrative illegal acts;

3. Civil legal risks: (a) contract breach disputes; (b)equity disputes; (c)exit disputes.

4. Procedural legal risks in civil litigation: (a) determination of litigation subject qualification;(b) class‑action issues; (c) identification of electronic evidence; (d) standards for loss determination; (e) procedural issues including criminal‑civil cross cases and incidental civil actions to criminal cases.

Technical Risks

Causes

1. Damage to network systems;

2. Attacks by network assassins;

3. Invasion of network viruses;

4. Technical defects of online platforms;

5. Instability of network systems;

6. Server failures;

7. Severe security vulnerabilities;

8. Low security of IP protocol key technology;

9. Poor firewall security;

10. Errors in technology selection.

Manifestations

1. Risk of electronic theft;

2. Risk of online fraud;

3. Risk of hacker attacks;

4. Risk of network assassin attacks;

5. Risk of network viruses;

6. Risk of information pollution.

Operational Risks

Causes

1. Major defects in internet financial security systems;

2. Termination of services by relied‑on external technologies;

3. System failures caused by hacker intrusions;

4. Hacker tampering with service programs;

5. Forgery of internet currencies;

6. Employee embezzlement of customer data for venture investment;

7. Negligence of internet financial customers;

8. Design defects of internet financial products;

9. Human operational errors;

10. Scattered customer groups;

11. Diversified communication methods;

12. Insufficient understanding of operational norms and requirements of internet finance by transaction participants.

Manifestations

1. Risk of authorized account use;

2. Risk of system management;

3. Risk of customer information leakage;

4. Risk of identifying genuine and fake electronic currencies;

5. Risk of payment and settlement interruption;

6. Risk of operational errors;

7. Risk of customer interest losses caused by black‑box operations;

8. Risk of account losses triggered by non‑standard operational procedures.

Operational Risks

Causes

1. Opaque and non‑standardized customer risk assessment procedures;

2. Lack of effective industrial risk control from customer information authentication to socialized credit assessment introduction;

3. Lack of transparency in risk assessment of individual companies;

4. Inadequate supervision over industrial credit risks;

5. Difficulty in quantifying specific risk factors of the whole industry and the effectiveness of risk assessment;

6. The internet finance industry is in a “three‑no” state: no access thresholds, no standards and no supervision;

7. Mixed quality of participants in the internet finance sector;

8. Impetuous mentality of practitioners.

Manifestations

1. Risk of financial fraud;

2. Risk of account theft;

3. Risk of capital losses;

4. Risk of maturity mismatch of wealth management products;

5. Risk of data information leakage and abuse.

Operational Risks

Causes

1. Weakened risk control and information review by operating enterprises;

2. Lack of supervision over internal review and risk control procedures.

Manifestations

1. Risk of single‑minded profit pursuit;

2. Risk of deteriorated business ecology;

3. Risk of increased capital leverage ratio;

4. Risk of capital chain rupture;

5. Risk of mixed operation caused risk payment.

Moral Risks

Causes

1. Information asymmetry between both parties in online transactions;

2. Difficulty in identifying customers’ risk levels online;

3. Inability to verify the authenticity of information provided by final borrowers;

4. Absence of independent third‑party risk control;

5. Inability to prevent self‑theft by internet financ

6. Shortage of professional risk control teams.

Manifestations

1. Risk of wrong decisions by internet financial enterprises;

2. Risk of corporate interest losses due to customers’ information concealment;

3. Risk of adverse selection against high‑quality internet financial enterprises;

4. Risk of losing customers and capital sources for online financial enterprises due to negative public evaluations.

Credit Risks

Causes

1. Virtual nature of online financial service modes;

2. Online‑based transactions and payments;

3. Difficulty in verifying the authenticity of traders’ identities;

4. Difficulty in verifying transaction authenticity;

5. Asymmetric credit evaluation information;

6. Lack of a social credit reporting system;

7. Sharp increase in shadow banking risks;

8. Poor reliability of data mining and analysis;

9. Selective bias and systematic deviation in credit risk measurement.

Manifestations

1. Risk of credit default;

2. Risk of credit expansion;

3. Risk of asset bubble burst.

Reputational Risks

Causes

1. Poor operation of institutions themselves;

2. Technical failures of non‑subject participants in financial transactions;

3. Financial fraud acts;

4. Network failures;

5. Malicious hacker attacks.

Manifestations

1. Risk of loss of public commercial confidence in online finance;

2. Risk of a run crisis in payment systems;

3. Risk of unsaleable virtual financial service products.

Market Risks

Causes

1. Interest rate fluctuations;

2. Exchange rate fluctuations;

3. Stock price fluctuations;

4. Futures price fluctuations;

5. Bond price fluctuations;

6. Underlying asset price fluctuations.

Manifestations

1. Interest rate risk;

2. Exchange rate risk;

3. Stock price fluctuation risk;

4. Futures price fluctuation risk;

5. Bond price fluctuation risk;

6. Underlying asset price fluctuation risk.

Liquidity Risks

Causes

1. Maturity mismatch;

2. Real‑time capital redemption;

3. High efficiency of payment;

4. Concentrated capital redemptions during festivals.

Manifestations

1. Risk of bank runs;

2. Risk of capital embezzlement;

3. Risk of financial product default.

Virtual Currency Risks

Causes

1. Q‑coin;

2. Bitcoin;

3. Litecoin;

4. Freicoin;

5. Ripple;

6. Amazon Coins;

7. Baidu Coin;

8. U‑Coin & Mi‑Ticket.

Manifestations

1. Risk of impacting fiat currencies;

2. Risk of amplified money multiplier;

3. Risk of disrupting central bank monetary policies;

4. Risk of out‑of‑control shadow banking.

Online Lending Risks

Causes

1. Unclear subject of guarantee rights;

2. High correlation among guarantee companies;

3. Formalistic risk reserve funds;

4. Poor guarantee qualifications of companies;

5. Extremely high capital leverage.

Manifestations

1. Risk of withdrawal difficulties;

2. Risk of online lending platform closures;

3. Risk of credit review for borrowers’ quota and qualifications;

4. Liquidity risk and deposited capital risk caused by loan splitting;

5. Intermediate account risks brought by recharges and withdrawals.

(1) Moderate Supervision

(2) Classified Supervision

Risk Supervision Over the Chaos of P2P Online Lending

Establish a joint fund of the P2P online lending industry association for risk prevention

Build a big‑data‑based supervision model

Construct a data‑driven risk control model. Adopt big data to screen and analyse the repayment capacity of individuals and enterprises, extract users’ basic personal features, consumption behaviour characteristics, credit records, risk preferences and other information, objectively evaluate their creditworthiness, and judge their repayment capacity and fraud risks. Analyse borrowers’ default costs through multi‑dimensional data collection, and formulate corresponding loan quotas and risk pricing. Big‑data mining can predict users’ cross‑platform transactions and serve as a pre‑risk control measure for users’ over‑indebtedness. Platform irregularities that trigger massive platform closures, including loan splitting, fake loans, flash loans, high interest rates and platform self‑financing, will be exposed under big‑data monitoring.q

Develop a new P2B model for P2P platforms

Cooperation between P2P online lending companies and factoring companies to build a new P2B model represents the future development direction. Factoring companies specialize in accounts receivable and supply‑chain finance, which is highly effective for strengthening risk control.

De‑guarantee for P2P platforms

P2P platforms should return to their nature as intermediaries, with risk management and control as the core. Borrowing projects shall have sufficient collateral, and platforms shall build robust internal risk control systems, so as to reduce reliance on platform guarantees and truly realize de‑guarantee.

Elimination of capital pools for P2P platforms

Capital pools are the primary cause of P2P platform fund absconding incidents in China. To fundamentally avoid P2P risks, capital pools must be eliminated fundamentally by adopting the P2P + third‑party payment model: both borrowers and lenders open accounts on third‑party payment platforms, and borrowers transfer funds to lenders’ capital accounts through such platforms. In this way, P2P platforms only act as intermediaries rather than pooling and allocating funds via capital pools, fundamentally preventing fund absconding incidents.

Differentiated product layout for P2P platforms

Faced with fierce competition and mixed‑quality participants, the P2P industry must carry out market segmentation, with refined and specialized product layout featuring differentiated development based on respective advantages.

Protection of investors’ rights and interests

Conduct investment risk education for investors, severely punish runaway and fraudulent platforms in accordance with the law, and set up legal aid funds to effectively protect investors’ legitimate rights and interests.

Alliance establishment between P2P online lending platforms and other institutions

There are 1,438 P2P online lending platforms in China, with dozens closing down monthly and several new ones emerging daily. These platforms are generally weak with poor risk control capacity. It is necessary to establish alliance platforms and carry out cooperation with commercial banks, factoring companies, guarantee companies, micro‑loan companies and e‑commerce platforms.

Business model transformation of P2P online lending platforms P2P online lending platforms must shift from full‑industrial‑chain platforms to pure transaction platforms. The full‑industrial‑chain model, where platforms undertake platform construction, capital raising, customer acquisition, loan review and disbursement, and loan guarantee, suffers from numerous drawbacks including high operating costs and high risks of moral hazard. The pure transaction platform model only requires platform construction and investor expansion, without providing guarantees. Loan reviews are undertaken by guarantors, loan terms are determined by both fund parties, and customers are introduced through external cooperation.

Internal risk control measures for P2P online lending platforms

(a) Set up risk guarantee funds; (b) Adopt small‑sum and diversified lending by dispersing one sum of capital across multiple borrowing targets;(c) Introduce guarantees from third parties such as guarantee companies and micro‑loan companies, which bear due diligence and compensation costs.

1. Dynamic Supervision;

2. Target‑Oriented Supervision;

3. Rule‑Based Supervision;

4. Fair Supervision;

5. Data‑Driven Supervision;

6. Tracking Supervision;

7. Self‑Regulatory Supervision;

8. Security‑Oriented Supervision;

9. Cooperative Supervision;

10. Coordinated Supervision;

11. Institutional Supervision;

12. Legal Supervision;

13. Technical Supervision;

14. Information Supervision;

15. Credit Reporting Supervision;

16. Market Supervision;

17. Accountability‑Oriented Supervision;

18. Platform Supervision Social Supervision;

19. Internal Control Supervision;

20. Real‑Name Supervision;

21. Qualification Supervision;

22. Cross‑Border Supervision;

23. Policy‑Oriented Supervision;

24. Vulnerability Supervision;

25. Network Supervision;

26. Virtual Currency Supervision;

27. Access Supervision;

28. Financing Supervision;

29. Online Lending Supervision;

30. Product Supervision;

31. Channel Supervision;

32. Industrial Supervision;

33. Complaint Supervision;

34. Fraud Supervision;

35. Procedural Supervision;

36. License Supervision.

Zhang Yunqing, male, Han ethnicity, born in Shangcai County, Henan Province, is an Associate Professor at the School of Marxism, Chongqing University. He has presided over nearly 20 provincial‑ministerial and horizontal research projects and published more than 20 academic papers. He has independently offered undergraduate courses for full‑time students of Chongqing University, including Academic Thoughts of Nobel Laureate Economists, Contemporary Western Economic Trends, History of Western Economic Thoughts, Introduction to Finance, Marxist Political Economy, and An Introduction to Mao Zedong Thought and the Theoretical System of Socialism with Chinese Characteristics. He has also taught courses for continuing education and self‑taught students, such as Public Relations and Marketing.

His main research fields include: (1) Studies on Fuxi culture, Liao culture, Hefu culture and Miao culture; (2) Studies on the evolution of Luoshu; (3) Studies on ancient Chinese military thoughts; (4) Studies on Chinese and Western history and culture; (5) Studies on Taoism, Confucianism and Yi‑ology; (6) Studies on Sinicized Marxist theories; (7) Studies on the history of Western economics and finance; (8) Studies on cutting‑edge theories of contemporary Western economics and finance; (9) Studies on divination systems including Qimen Dunjia, Ziwei Doushu, Da Liuren and Taiyi Shenshu.