AML indeed has been the buzzword for the past 3 decades, but before combating money laundering i.e., going “anti” let’s understand what money laundering is. The origin of the term money laundering takes us back to the years of World War 1 & 2 when the illicit revenue generated by financial crimes was on an extreme rise. Since then and even today, most of us choose to safeguard our money in bank deposits or mutual funds / shares. But storing cash at home in huge amounts is not a viable option neither for a common man nor for a fraudster especially when the source is illegal. Bank is a secure option but comes with many potential risks from a fraudster’s perspective. So soon they started businesses with low capital investment like laundry, carwash, small scale casinos where the cash transactions involved appeared legit. Hence the term “laundering” which simply means involving proceedings of fraud or criminal activities into active financial processes. These financial processes being authentic and regulated yield in “legit” money at the end of the transaction pipeline.
Money Laundering involves 3 stages, Placement, Layering and Integration. Placement involves getting cash which is the outcome of a financial crime into a financial body. Now, one won’t walk with a truckload of money into the bank as large denominations would attract many. Hence such dirty money enters banks in the form of small denominations as cash on bills of restaurants, hotels, bars, casinos, vending machine companies etc. This phase is usually missed by law enforcement bodies as most of the things involved appear as legit. Layering as the second step requires the fraudster to make multiple transactions involving multiple entities on various fronts. Thus, the placed and layered illegal money becomes very complicated to identify as probable proceedings of fraud. In the final stage of Integration, the money enters the economy as white i.e., legit. Someday this money even assimilates as an asset for the launderer himself or for someone else, in any case a success for the black hats involved. In simpler words money laundering is the practice of turning “bad” money into “legitimate” money.
Here’s an example to understand the 3 most usual stages involved in money laundering:
- Placement: Fraudster deposits cash into a bank account, purchases property / goods.
- Layering: Some of it is wire transferred out of the country to run shell companies.
- Integration: Property / goods get sold, profit is wire transferred, retained earnings of companies are wired in and reinvested into something else which is legal.
Due to the complex nature of Wire / Transfer / ACH payment templates, it becomes a nightmare to identify transactions in the above scenario as fraudulent, as by default they tend to appear as legitimate ones. A red flag in this scenario is missing / mismatched information provided by fraudsters at the time customer onboarding / KYC to be done by the bank. The sole purpose of bank accounts involved here is to act as channels to transfer funds.
Money laundering is a global issue hence a unified effort is required to combat it. It poses a risk to the citizens as an increase in taxes, crime rate and monopoly in small businesses. It also comes with other moral, reputational and financial risks like penalties, criminal charges etc. Hence combating money laundering is a three-way handshake between Law Enforcement (DOJ), Regulatory Bodies like SEC (Securities and Exchange Council) and Financial Institutions like FATF (Financial Action Task Force), OFAC, FinCEN. All of these publish content on AML on a regular basis which is publicly available. This content consists of case studies, possible scenarios, and Red Flags! Banks and Credit Unions are expected to have an AML compliance program and work in tandem with these regulatory institutes. These institutes use a format to record fraud which is ‘SAR: Suspicious Activities Report’.
Let’s have a look at a few red flags appeared through case studies collected over years:
- Large number of small-valued transactions i.e. Structuring
- Sudden large activity in dormant account
- Incomplete information submitted / gathered as a part of KYC
- Money mule schemes
- Trade based money laundering
- Shell / Shelf companies
- Exaggerated Donations
- Credit / Debit card payment fraud
- Gold Smuggling
- Money Service Businesses
There are various challenges involved in detecting fraud due to geographical limitations, currency / denomination differences etc. A common challenge is as in a transaction where sender ‘A’ sends $50,000 to receiver ‘B’, if ‘B’ is the customer of bank ‘C’, then in transactional data records of ‘C’ there’s no complete information available of sender ‘A’. Same is the case the other way round. The point here being, insufficient data, data accessibility, variety in sources, data asymmetry and continuously evolving regulations and policies are the few challenges involved in detecting financial fraud.
What is Ellicium banking on, to help financial institutes detect fraud?
- Machine Learning
- Rule based algorithms
- KYC Scorecard
- Outlier Detection
- Red Flags Library
- Prerequisite for SAR
Senior Analytics professional