By Shreya Tiwari

Abstract

This article analyses the interaction of technology and anti-money laundering solutions, with a focus on the roles of Artificial Intelligence (AI), regulatory frameworks, Credit Rating Agencies (CRAs), and developing technologies. It explores AI’s role in identifying fraudulent financial activity using machine learning and big data analytics, focusing on its capacity to recognise abnormalities and trends in financial data. Regulatory frameworks such as Know Your Customer (KYC) and Anti-Money Laundering (AML) procedures are being investigated as preventive measures imposed on banking organisations. The article also dives into the problematic procedures of CRAs, emphasising their influence on investor trust and financial stability. The following half focuses on technology as a precursor to new detection measures, including blockchain, biometrics, data analytics, and software protection in the fight against financial crime. In conclusion, it emphasises the importance of international collaboration, openness, harsh sanctions, and addressing the core causes of corruption in order to effectively combat money laundering.

Solutions and Detection – Belling Accountability on the Cat 

The evolution of our society is possible due to the continual improvement in technology and artificial intelligence is the next stepping stone. In the banking sector, AI plays an important role in detecting and preventing the creation of fraudulent financial statements. Using Machine learning, adaptive analytics, and big data programming to evaluate trends and abnormalities in financial data, AI can detect fraudulent financial activity in the data they have collected. These patterns and anomalies may suggest fake transactions or expenses that were not approved.

A variety of Artificial intelligence models have been developed to perform specialized detection techniques to minimize fraud. These specialized AI models can recognize extremely high or low amounts that could be considered odd. Moreover, they would alert the auditors and authorities to carefully check all of the transactions. Using unstructured data analysis techniques, AI models can read content in emails or documents through Natural Language Processing to translate text data into useful insights to be analysed. Following that, the supervisors would be able to easily manage large amounts of data as they can focus their attention on particular fraudulent activities, such as collusion or kickbacks. Also, artificial intelligence has made repetitive tasks like data entry and analysis, for auditors easier. This would result in more accurate audits and the faster discovery of odd or phony financial activity.

The creation of regulations for banks by regulators, emphasizes the importance of following rules as a financial institution and lays down consequences for those that break the rules. As a result, this helps prevent or minimize fraud in the banking industry. The Know Your Customer (KYC) and Anti-Money Laundering (AML) processes are some of the frameworks that banks are required to follow. It is mandatory for a bank to verify customer identities and report any questionable financial activity. Furthermore, banks are also subject to inspections to ensure that they are following the rules and maintaining a high level of security and safety. Through scheduled audits, the finances that are reported by the banks are examined for fraud. Infractions of the rules outlined in regulations can result in regulatory sanctions. When a bank violates any of the laws or regulations, they may be required to pay money, lose their license, and or face prosecution. The regulatory agencies penalize financial institutions that commit fraud and encourage them to improve their internal controls. It is important to have regulations because they help keep banks reliable and stable, as well as maintain the customer’s and investors’ faith in the financial system.

Credit Rating Agencies are companies that assess and evaluate the credit of businesses, and governments through an analysis of their financial history, present financial state, and current economic conditions. They provide credit ratings and assess the ability of a company to repay debt. On this, it is then determined whether shareholders and creditors must invest in a company. These credit agencies are often accused of aiding these corporations, by giving them higher ratings and hence helping them commit fraud. They also help these companies portray that they have better financial positions and positive ratings, in exchange for money or other benefits. Furthermore, these high ratings are given to corporations, to maintain strong relationships with these companies. However, this information that is given is misleading to any investor or creditor and in the larger picture results in a large financial loss. The failure of CRAs to detect or report fraudulent activity within a rated organization can contribute to the problem of corporate fraud. Ratings are based on the financial information that companies voluntarily disclose to CRAs, however, it is possible for them to fail to disclose all the necessary information. Additionally, there is a possibility that CRAs will miss fraud committed through deceptive accounting practices or other techniques. These high ratings and malpractices make creditors and investors susceptible to believing that companies they interact with are financially in better places than they actually are. Two major credit rating agencies in India are Credit Rating Information Services of India Limited (CRISIL) with the majority stake with Standard & Poor’s and Credit Analysis and Research (CARE). The Amtek Auto scandal highlighted the fraudulent methods undertaken by credit rating agencies which led to the highest-bond and security-rated company being suspended from the list of CRAs. Furthermore, problems in rating have led to a rise in the number of non-performing assets (NPAs) especially in India. 

In my opinion, an increase in transparency, on financial information and ratings should be mandated and enforced by regulatory bodies to prevent any conflict. I believe that these issues should also be resolved at the earliest, and there should be adequate punishment and fines that are enforced on these CRAs. Conclusively, CRAs can be held accountable to investors that rely on these ratings and the focus must be on regulation rather than mechanistic rating. 

Technology – Harbinger of New Methods of Detection 

Using technology, people are coming up with innovative solutions to combat financial crime. For instance, AI and Machine Learning have now become an increasingly important part of financial crime detection, being used extensively for the evaluation of data. AI plays a crucial role in identifying trends as mentioned in the former section, as the system can clearly identify out-of-trend or anomalous transactions and it can flag data that doesn’t abide by the general trend. Such capabilities of AI are now being utilized in law enforcement. Blockchain is another technology that is increasing rapidly and becoming a part of the financial sector. Blockchain allows everything to be on one decentralized system, which allows for transparency and security, as once a transaction occurs on the blockchain it can clearly be linked to the owner, and the amount and other identification of the transaction can occur easily. Technology is being increasingly used nowadays to tackle financial crime and via crypto etc., it has entered the financial sector extensively. The importance of identification is further exacerbated when individuals commit identity theft and other misrepresentations and frauds. Therefore, the biometric system is also becoming increasingly crucial, while it is widely used and accepted due to the important role it plays in establishing identity transparency. Therefore, it is a way that serves the dual purpose of tackling fraud and maintaining data uniformity. Another way software is helping in identifying and tackling financial crime is through data analytics, which allows the software to spot fraud and financial crimes. Moreover, to prevent data hacks and breaches more stringent measures of software protection are being put in place such as firewalls, and intrusion detection systems which help companies identify and prevent a data leak.

Conclusion

In conclusion, money laundering via the means of international tax havens and offshore banking is becoming increasingly popular, more so with the use of technology as the web of transactions can occur from a single place making it very difficult for authorities to then link the transaction back to the actual culprit. Now that technology is being integrated into systems by the regulatory authorities for helping and assisting them in detecting such fraud and laundering activities that lead to tax evasion. It is, therefore, critical that this technology be used efficiently and effectively such that the culprits are caught, and tax havens become a futile method of money laundering.  In our opinion, policymakers, and other regulatory bodies in order to tackle this problem must focus on strengthening international cooperation and develop common practices in order to prevent money from being laundered easily. Additionally, these policymakers must increase transparency regarding ownership and implement measures wherein all companies disclose relevant information about their structure of ownership. This we believe would prevent the creation of shell companies and anonymous accounts. Another step we think that should be implemented to tackle this problem is, imposing harsh and strict penalties upon financial institutions such as CRAs, to prevent such actions from being taken. Lastly, we feel that all regulatory bodies must address where the problem stems from. In identifying and assessing corruption, and organized crime and taking action against it, the crime of money laundering will decrease and law enforcement will benefit.

Author’s Bio

Shreya Tiwari is a fourth-year BA-LLB student at Jindal Global Law School with a keen interest in exploring the intricate connections between law, finance, and economics and their profound impact on the global economy. When not engaged in academic pursuits, she enjoys expressing her creativity through painting and sketching. Her curiosity also extends to the captivating realms of corporate law and the intriguing world of white-collar crime studies.

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