Red Flags Identification and Mapping against Loan Frauds Cases in Indian Banks
Introduction to Financial Fraud in Indian banks
Bank fraud involves stealing one’s wealth or else damaging overall performance by deceitful, dishonest, or unlawful methods. This may be accomplished via several means, including fraudulent activity and orders to manage the risks. Lending corruption is defined as any criminal conduct committed with the goal of obtaining monetary gain through credit intermediaries. Financial theft may be reduced, but it cannot be eliminated.
Banking crime’s genesis and communication are two closely related concepts. Gaps in engineering management, governance, nullifying of regulation, connivance with clients and stakeholders, low employee morale, independent oversight, integration of polity, compliance to moral principle and development of the employees, and awareness campaigns program are all elements of the banknote. [1] Among such components are combined factors: technological advancement, managerial negation of regulation, connivance with customers, employees, and distributors, and staff turnover; the remaining four different factors are preventive measures: properly accounted and effectiveness of internal with legislation, moral qualities, and safety training. [2] To prevent a financial gap, administrators should combine these factors. Financial services program managers communicate to avoid fraud after determining the likelihood and landscape.
Loan Frauds
In recent years, the financial sector has faced tax evasion challenges. Due to a surge in the number of committed frauds, financial institutions, particularly State-owned banks, are experiencing growing losses and a spike in NPAs. In several situations, top-level management plays a crucial role in halting banking operations. The sector has suffered because of the similar trial of Nirav Modi, in which a credit was approved for a development task. Allegations of illegalities and dishonesty were made against several of the company’s senior leaders. Internal control and ethics are questioned as a result. The global economic downturn has been blamed on the threat of growing non-performing assets (NPAs).
The stability of a country’s economic banking markets may be gauged by its output and spending levels. For any country, if its monetary sector is riddled with deception and has a significant percentage of non-performing loans, it should be a reason for concern. These problems have been affecting economic growth for a long time. The table below indicates the loan fraud cases doubling in the past years.[2]
Table 1.1: Loan fraud cases in past years
| Year | 2016 | 2017 | 2018 | 2020 |
|---|---|---|---|---|
| Loan Frauds double in past years | 5,076 | 5,919 | 6,801 | 8,200 |
Source: RBI Reports on frauds 2021 [2]. Showing an alarming surge from 5,076 cases in 2016 to 8,200 cases in 2020.
Even though the financial sector is governed by laws such as the Banking Act of 1949, RBI Act, SBI Act, and Bankruptcy Act, fraudsters and unethical behaviour by account holders and personnel continue to plague the industry. [2] Although various restrictions have been put in place to prevent action or activity by persons who use public funds for their gain, business is still going bankrupt because of it. With this, economic markets have several weaknesses and tax loopholes that allow fraudsters to take advantage of customers’ funds. That’s an effort to shed light on the various problems that lead to an increase in non-performing assets (NPAs) and bank failures.[1][2]
Economic strain, chance, and reasoning all play a role in a person’s willingness to pursue deception. It’s very uncommon for downturns to worsen such concerns, since profits are limited and revenue is just a difficulty. According to the research, individuals and interested stakeholders are colluding to defraud people due to a major lack of monitoring by subordinates or supervisory board; a lack of entrepreneurial incentive to fulfil objectives; and collaboration among staff and key organisations. [3]
Red Flags Identifications
The existence of one or maybe more Early Warning Signals (EWS) raises suspicions of fraudulent transactions on a Red Flagged Account (RFA). If the bank notices any of these warning signs in a principal amount, it should be on high alert for possible fraud. Rather than ignoring these early earing signals, an institution should use them as a reason to conduct a thorough examination of any red flag accounts.[5]
The financial institution pointed out that banks’ poor implementation of leading indicators (EWS) and organisational inspections’ failure to identify EWS were also the primary reasons for the delay in uncovering fraudulent activities. These findings support the urgent requirement for banks to put in comprehensive EWS processes that detect red flags in the early phases of fraud. Regulators have issued new guidelines for banks to follow when it comes to red flags. If you see a red light, it means there’s something wrong with your personal or corporate loan account. As of 2015, the RBI has enforced a strict approach to systems and procedures, which includes EWS compliance.[4]
Multiple signals were listed by the banking system and banking sector administration as part of a complete framework for effective EWS systems.[2, 5] The following are some examples of the many types of signals:
- Accountancy Warning Signs: The absence of audited banking statements, inappropriate or unaccountable money transfers, and irresolvable bank account reports are among the accountancy red flags.
- Compliance with corporate rules and regulations concerns: Some instances of corporate governance include exorbitant pay schemes, regulation evasion, poor or non-existent compliance requirements, and excess leadership mobility. These are warning signs.
- Organisation Red Flags: Transactions with unidentified parties, the presence of shell corporations, and historical memory of frauds are all examples of suspicious activity.[5]
- Individuals responsible for red flags: such as unexpected significant purchases, lacking KYC papers, stacking debt, numerous credit lines, and so on, are also included in the general category of red flags.
- Social Media & Mainstream Intelligence: On social media or in the mainstream, any unfavourable remarks about a company or its leadership might be considered a red flag.
Based on our proposed research after analysing multiple loan fraud case studies the following red flags are identified as presented in Table 1.2 which indicates the possible red flags in loan frauds. Detail analysis and major key findings of possible loan frauds tactics, while red flags tactics (RFT) are assigned based on tactics numbers and probability of occurrence are cast-off based on case studies analysis. Red flag tactics numbers are assigned, while probability of occurrence is on low to extreme scale.
Table 1.2: Proposed mapping of red flags tactics (rft) and probability of occurrence
| Tactic | Possible Red Flags | Details | Probability of Occurrence |
|---|---|---|---|
| RFT-1 | Fake KYC documents | Fake documents were created for committing fraud. | High |
| RFT-2 | Forged accounts. | Forged bank accounts were created in the name of servants, family members and other known persons. | Medium |
| RFT-3 | Forged and fake documents produced. | Tampered documents were produced for loan credit | Extreme |
| RFT-4 | Bogus Company | Bogus address was produced with bogus company which exists only in papers. | Low |
| RFT-5 | Fake Invoices | Fake Invoices were created. | Medium |
| RFT-6 | Spoof Bills produced | Spoof bills were produced. | Low |
| RFT-7 | Fake Assets | Fake assets were shown for loan credits. | Extreme |
| RFT-8 | Absence of whistle-blower policy | Whistle-blower policy sometimes work for all major banks. | High |
| RFT-9 | Bank Employees misused his/her duty /job/position. | Mostly bank employees were involved in such frauds. | Medium |
| RFT-10 | Failure of duty segregation. | Failure of duty segregation was seen. | Medium |
| RFT-11 | Lack of employee’s awareness. | Employee’s awareness missing in fraud. | Extreme |
| RFT-12 | Tempting offers to bank employees. (Root cause: [poor appraisal system) | Tempting offers and bribe offers to bank employees because of a poor appraisal system. | Medium |
| RFT-13 | Early red signals Information not disclosed on time. | Bank failed in reporting incident on time. | High |
| RFT-14 | Heavy Loan sanctions. | Heavy loan sanctions without proper verification. | High |
| RFT-15 | Big transactions were not highlighted. | Big transactions were not recorded on time. | Low |
| RFT-16 | Supplementary favoured for specific companies. | Favour done to specific company without proper document verifications | Medium |
| RFT-17 | Suspicious entries not detected. | Suspicious payment/ truncation was not detected/ reported on time | High |
| RFT-18 | Vague borrowing process. | Unclear borrowing process. | Medium |
| RFT-19 | Non-cooperation of borrowers during forensic audits. | No cooperation during forensics audit process. | High |
| RFT-20 | Huge diversification of money. | Money diversified into multiple accounts and also converted into multiple assets. | Medium |
| RFT-21 | Failure of risk management. | Risk Management system was not active and missing. | High |
| RFT-22 | Failure of Risk identification | Risk identification system failed completely. | Medium |
| RFT-23 | Auditor cheated/ auditor training skills | Auditor cheated with tactics and techniques; main reason is audit were not trained to perform such audits. | Medium |
| RFT-24 | Unsuitable Audit process. | Audit process was not done in a systematic manner. | Low |
| RFT-25 | Inconclusive audit reports. | Inconclusive audit reports. | Low |
| RFT-26 | Unsuitable Audit process. | Document analysis was not done in a proper manner and an unstable audit process followed. | Medium |
| RFT-27 | Infrequent audit process. | Infrequent audit process. | Medium |
| RFT-28 | Politician support | Support from politician in borrowing and lending. | Extreme |
| RFT-29 | Cross border transactions | Huge and heavy transactions in cross border accounts. | Low |
| RFT-30 | Overpriced invoices. | Invoices were overpriced and not monitored properly | Medium |
| RFT-31 | Fake email ID created. | Fake email ID was used | Low |
| RFT-32 | MIS used of advanced technology | MIS used of advanced technology in bypassing account details information | Medium |
| RFT-33 | Misuse of fund | Fund misused by banks | Medium |
| RFT-34 | Weak enforcement of law in the country | Weak | Low |
| RFT-35 | Attention to early red signals | No attention was given to early red signals | High |
| RFT-36 | No fear in committing fraud | The long and elaborate judicial process is another major concern. | High |
Risk Matrices: Likelihood, Consequences & Tactic Mapping
Based on the above red flags, Table 1.3 demonstrates consequences and likelihood of occurrence, while colour codes are used for bifurcation purpose. Below Table 1.3 shows sample scale of Red Flags Consequences, Likelihood and occurrence using Risk Matrix.
Table: 1.3: Sample scale: consequences, likelihood and probability of red flags tactics occurrence using risk matrix
| Likelihood | Consequences | ||
|---|---|---|---|
| Minor | Moderate | Significant | |
| Unlikely | Low | Low | Medium |
| Possible | Low | Medium | High |
| Likely | Medium | High | High |
Table 1.4: Mapping of Consequences, Likelihood and Probability of Red Flag’s occurrence using risk matrix
| Likelihood | Consequences | ||||
|---|---|---|---|---|---|
| Insignificant | Minor | Moderate | Major | Critical | |
| Rare | LowRFT-29, RFT-34 | LowRFT-31 | LowRFT-25 | MediumRFT-2 | HighRFT-36 |
| Unlikely | LowRFT-15 | LowRFT-24 | MediumRFT-2, RFT-5 | MediumRFT-9, RFT-10 | HighRFT-35 |
| Possible | LowRFT-4, RFT-6 | MediumRFT-10, RFT-12, RFT-16 | MediumRFT-10, RFT-18, RFT-20 | HighRFT-8 | HighRFT-19 |
| Likely | MediumRFT-2, RFT-5, RFT-9, RFT-10, RFT-32 | MediumRFT-33 | HighRFT-14 | HighRFT-21 | ExtremeRFT-28 |
| Almost Certain | MediumRFT-22, RFT-23, RFT-26 | MediumRFT-27, RFT-30, RFT-32 | HighRFT-1, RFT-13, RFT-17 | HighRFT-3, RFT-7 | HighRFT-11 |
Prevention: Possible Methods for preventing loan frauds
When it comes to fraud protection, the most significant safeguard banking must take is to incorporate developing technology into its legacy infrastructure. Numerous conventional banks in the nation have failed to take advantage of the emerging transformation that is taking place. A mere few years ago, acquiring and presenting fake paperwork was more challenging than it is now, as the number of technologies for those documents has grown dramatically. To avoid fraud, digitised authentication of the paperwork via the use of interconnected technology is required.
Computing and Advanced Analytics-enabled technological tools have become a key differentiator for global companies, and viable banks will only benefit from incorporating these technologies into their operations. An added dimension to the safety precautions that organisations can implement is the examination of the issuers or individual player’s business history and correlations. Tax filings, whether they be ITR or GST filings, are a strong measure of the effectiveness and legitimacy of a company entity’s operations. Invalid ITR information, on the other hand, should raise red flags for every mortgage lender since it may be an indication of improper purpose or activity. Upon receiving this information, the next precautionary action that institutions may take is to examine the organisations for any unfavourable information that may have been released about the respondent over a certain period.
Financial institutions may get crucial data from organisations to determine the legitimacy of applications. The absence of bad news allows one to proceed to a new phase in investigative work; on the other hand, bad publicity raises red flags and prompts a more in-depth investigation into the individual’s economic and corporate safety. Figure 1 indicates the possible methods for loan fraud prevention.
Figure: 1: Possible methods for loan fraud preventions
Organisations need to make use of recent breakthroughs in advanced technologies to anticipate trends and learn from experiences. [7] Incorporating digital into financial transactions without providing useful viewpoints and data analysed through these procedures is indeed an unsatisfactory use of restricted resources in this case. The best thing for bankers to do is to make or use sophisticated models that can predict how likely it is that someone will be dishonest.[8] Risk assessment models can play an important role in all fraud identification and early detection of frauds.
Conclusion
Multiple factors contribute towards fraud, including a faulty legislative framework, negligent personnel, overall shortage of oversight just at the headquarters level, erroneous application of technologies, and often a failure to communicate between customers and staff. It is essential that institutions observe the infrastructure that periodically evaluates or verifies transactions that could be vulnerable to scams to avoid such concerns. To combat this rising problem in banks, authorities have to enact increasingly strict anti-corruption regulations. Financial services, including cross activities, mortgages, withdrawals, and other money transfers, must be much protected.
References
- Impact of Frauds on the Indian Banking Sector Ainsley Granville Andre Jorge Bernard, Brahma Edwin Barreto, Rodney D’Silva
- RBI Reports on frauds 2021.
- Deloitte Survey: Indian Banking Fraud Survey, Business Standard
- Loan frauds https://sdk.finance/detecting-and-preventing-loan-application-fraud-with-ai-powered-online-document-verification/
- Frauds in the Indian Banking Industry - IIMB-WP N0. 505
- Types of banking frauds report https://www.stpaulschambers.com/types-of-banking-fraud/
- Financial fraud aspects detail analysis of financial fraud available at https://www.ukfinance.org.uk/system/files/Fraud%20The%20Facts%202021-%20FINAL.pdf
- Report by Insight partners, available at helpnet security, jan 2022.