While money is the prime necessity of life, it is also the feeding grain for criminals and terrorist organisations. One term that we hear quite often regarding money-related crimes, is ‘Money Laundering’.
In simple words, 'money laundering' is the unlawful act of deliberately trying to conceal the origins of financial assets, in order to legitimise the financial transactions used for criminal offences.
The money launderers try to mask the trail of their assets by introducing illegal profits in their financial history, which makes the process of money tracing ‘obscure’ for the financial institutions.
The illegal money, which is not traceable, is then used to carry out criminal activities. Money laundering involves criminal activities such as smuggling, involvement in selling arms and drugs, human trafficking, embezzlement, bribery etc.
Money laundering is on the rise and has accounted for 2-5% of the global GDP. It is now imperative to be resolute in fighting against it.
Anti Money Laundering is the process of taking comprehensive actions to control and monitor the widespread money-laundering problem.
Organisations such as financial institutions, fin-tech companies, banks, gaming platforms etc. are mostly the entities that are interested in equipping themselves with efficient AML verification techniques for the prevention of financial crimes.
The concern of rapidly increasing money laundering, brought the international community under the same roof. Governments have taken a rigid stance regarding money laundering, and have enacted stringent anti money laundering laws and regulations, that need to be followed with full responsibility.
This (AML compliance) has put a great deal of pressure on financial institutions and other organisations.
Organisations are now compelled to observe strict practices, to ensure proper AML compliance. Financial watchdogs such as FATF, IMF, and World Bank maintain a sanction list of criminals.
Firms have to continuously screen their customers and check their inclusion in the sanction lists, in order to prevent financial losses and also heavy penalties in case of negligence.
Failing to comply with AML regulations results in penalties that not only incur heavy financial losses for companies, but also take away the trust of their customers.
Initially, organisations resorted to methods that included manual practices to conduct AML checks e.g human resources were involved in extensive investigations of potential fraudsters.
However, these practices, even when conducted with full devotion, still leaves a door open for human error. Moreover, manual AML verification can be a very exhaustive process and requires a lot of time and effort. This asks for swift and efficient AML solutions to be put in place.
The introduction of Artificial Intelligence in AML security is a way forward and offers a solution to the limitations left behind by manual AML screening. According to Livia Benisty, Global Head of Business AML at Banking Circle, AI can serve a key role in AMLs digital transformation and believes that soon financial services will have to incorporate modern AI technology in AML systems, in order to keep up with the competition.
On-going AML monitoring is an AI-based, continuously active, digital monitoring system, in which potential fraudsters/criminals are continuously being monitored. Risk profiles are developed and updated after regular intervals. This offers various advantages over manual AML verification.
1. Staying in competition
Ongoing AML solutions offer an added layer of security and hence prevent penalties from financial institutions that can be damaging for the brand name. Hence a proper AML compliance with ongoing monitoring gains customers' trust and can provide a competitive edge to these firms.
2. Better customer experience
When customers are monitored frequently and are informed about the security protocols being followed, it gives a sense of security to the customers and gains their trust in the credibility of the company. This offers extra value to the customer's experience and saves the organisation from a bad reputation.
3. Removes false positives
Often firms while dealing with customers conduct a thorough investigation of their involvement in crimes. If the investigation detects no fraudulent activity, that particular customer is deemed innocent. However, this can prove to be a false positive, as there lies a possibility that these customers would indulge in criminal activities later on. This can result in dire consequences. If offenders are able to bypass the initial security checks, they feel more confident in attempting criminal activities. AI-based ongoing monitoring systems remove false positives and solidifies the overall security.
4. Strong compliance with AML laws
Companies are under immense pressure to comply with AML laws. Manual checks have been ineffective in preventing money laundering and hence more is demanded from the companies. Watchdogs are in continuous search of companies that are missing out on AML regulations and are not hesitant to place hefty fines (Forbes). On 7th October 2021, investment bank NatWest was handed a £300m penalty for not being able to keep a check over their customers’ fraudulent activity.
5. Effective risk management
Real-time monitoring develops risk profiles of customers and updates the results after frequent intervals. Consistent risk profiling through ongoing monitoring is an effective risk management strategy as it mitigates the chances of onboarding potential criminals and fraudsters.
6. Optimised customer on-boarding
Manual AML screening procedures take time and effort. Real-time AML verification process provides real-time screening that reduces the time taken to conduct necessary security checks to onboard a customer.
7. Reduces cost
AML compliance was not a pocket-friendly option without digital help.
Modern AI technology has reduced human labor in the process of investigating customers and monitoring their activities. Now the computer does the job and has cut the cost significantly.
In a nutshell, ongoing AML monitoring is an effective solution to prevent financial crimes. It leaps ahead of the manual AML screening methods in terms of offering better risk management, compliance with AML regulations, reducing false positives, optimised customer onboarding, and reduction of time and cost.
Organisations that relied on a manual approach didn't have financial losses to bear, but also went under the knife of financial watchdogs, whose policies are becoming more stringent than ever. Hence, in order to avoid these consequences, organisations should switch from manual AML screening methods to more robust solutions like AI-based ongoing AML.