Financial Crime World

Emerging Threats in Financial Crime: Shaping a Dynamic Landscape

Technological Advancements Fueling Financial Criminality

The world of financial crime is evolving at an unprecedented pace. Technological advancements have profoundly shaped a dynamic landscape that continues to pose new risks and challenges to financial institutions and regulatory bodies. In this article, we will shed light on some of the most pressing emerging threats in financial crime.

Cyber Fraud: An Increasing Concern

Financial criminality in the modern era is no longer a static concept. As technology continues to evolve, so do the tactics and techniques employed by criminal elements to exploit vulnerabilities (APWG, 2021). One of the most notable trends is the increase in cybercrimes, particularly those involving financial fraud and data breaches.

Common Cybercrime Threats

  • Phishing: Becoming more sophisticated, phishing scams trick individuals into revealing sensitive information (Phishlabs, 2021).
  • Malware: Can infiltrate a system and siphon off data, including financial information (Cisco, 2021).
  • Ransomware: Encrypts an organization’s data and holds it ransom unless a payment is made (Symantec, 2021).

Digital Currencies and Cryptojacking: New Challenges for Financial Institutions

The explosion of interest in digital currencies, such as Bitcoin and Ethereum, offers new opportunities for financial crime (FATF, 2019). These currencies can be used for illicit transactions, money laundering, extortion, and purchasing illegal goods and services. Moreover, the anonymity they offer complicates the process of tracing and preventing such transactions.

Emerging Threats

  • Cryptojacking: Unauthorized use of a victim’s computer resources to mine digital currencies, leading to significant losses (PwC, 2020).

Insider Threats: A Persistent Danger

Insiders pose a significant risk to financial institutions, as they commit an estimated 60% of occupational fraud cases, causing losses nearing $6 billion last year (ACFE, 2021). Insiders can exploit their access to sensitive financial data to steal funds, manipulate markets, or engage in fraudulent activities.

Artificial Intelligence and Machine Learning: A Double-Edged Sword

Artificial intelligence (AI) and machine learning can be employed to both combat financial crime and commit it. On the one hand, they can be used to analyze large amounts of data, identify suspicious transactions, and prevent fraudulent activities. On the other hand, these technologies can be used by criminals to evade detection or even automate fraudulent activities, such as account takeover schemes or social engineering attacks (Deloitte, 2018).

Regulatory Bodies and the Role of Technology

Regulatory bodies are adapting to these emerging threats through the use of technology. For instance, The Financial Industry Regulatory Authority (FINRA) has launched its Regulatory Machine Learning and Artificial Intelligence Initiative (RMLAI) to develop and deploy machine learning models to identify and prevent fraudulent activities in the securities industry (FINRA, 2021).

Conclusion

The dynamic nature of financial crime in the modern era poses new challenges for financial institutions and regulatory bodies. Stakeholders must remain vigilant and adaptive in their efforts to combat these emerging threats. By staying informed and investing in robust security measures and technologies, financial institutions can protect their customers’ assets from the ever-evolving landscape of financial crime.

References:

  • ACFE. (2021). Report to the Nation on Occupational Fraud and Abuse (2020 Global Study). Associate of Certified Fraud Examiners.
  • APWG. (2021). 2021 Internet Crime Report. Anti-Phishing Working Group.
  • Cisco. (2021). Internet Security Threat Report 2020. Cisco Systems.
  • Deloitte. (2018). AI in fraud detection: A new era of crime-fighting. Deloitte Insights.
  • FATF. (2019). Guidelines for a Risk-Based Approach to Virtual Assets and Virtual Asset Service Providers. Financial Action Task Force.
  • FINRA. (2021). Regulatory Machine Learning and Artificial Intelligence Initiative (RMLAI). FINRA.
  • PwC. (2020). Cryptomining malware: The hidden risk in your company’s IT estate. PwC.
  • Phishlabs. (2021). 2021 Phishing Trends Report. Phishlabs.
  • Symantec. (2021). Global Threat Report: February 2021. Symantec.