Forensic experts of Deloitte on trade-based money laundering
Trade-based Money Laundering (TBML) is a huge challenge for financial services institutions, in part because trade financing still is highly reliant on manual monitoring and screening. According to KV Karthik and Manish Mandhyan from Deloitte, institutions need to ramp up their foundation for monitoring and detecting TBML, leveraging technology in the process.
In 2018, the Financial Intelligence Unit (FIU) India fined Bank of Baroda for alleged TBML schemes in which traders colluded with bank officials to evade duties and taxes, and deficiencies in the Anti-Money Laundering (AML) framework. According to the FIU, the bank failed to have an effective internal system for disposal of 8,692 alerts, detecting and reporting suspicious transactions, failure in carrying out effective customer due diligence for 73 accounts, delayed filing of 8,822 Electronic Funds Transfer (EFT) reports, and failure to file EFT reports for transactions in two separate accounts.
Bank of Baroda is not alone in its challenges. Banks struggle with screening due to data complexities (a lot of the information is unstructured within (SWIFT), making the screening difficult), corporate customers that are reluctant to share relevant information required for adequate due diligence, and the fact that process are labour-intensive and costly.
When developing their TBML controls, financial institutions should consider relevant red flag indicators. Some common red flags include the following:
- The transaction is not commensurate with known customer profile, structure, or business strategy. In a TBML context, this may be where the nature or type of goods shipped is not in line with the business nature of the customer (e.g., a steel company that starts dealing in paper products, or an information technology company that starts dealing in bulk pharmaceuticals), the customer has no experience in the goods in question, the size, or shipments’ frequency appears inconsistent with the scale of the customer’s regular business activities (e.g., a sudden surge in transaction size).
- The shipment locations of the goods, shipping terms, or descriptions of the goods are inconsistent with the Letter of Credit (LC). This may include changes in shipment locations to high-risk countries or changes in the quality of the goods shipped.
- Significant discrepancies appear between the descriptions of the goods on the bill of lading (or invoice) and the actual goods shipped.
- The transaction involves an uncommon or complicated movement of goods and/or third parties without an obvious purpose.
- The commodity is trans-shipped through one or more jurisdictions for no apparent economic or other logistical reason.
- The commodity includes dual-use goods.
- Significant discrepancies appear between the value of the commodity reported on the invoice and the commodity’s fair market value.
One of the first steps to effectively screen trade finance transactions requires accurate data capturing. The volume, variety, and quality of data varies depending on the processes and systems within a financial institution, and an assessment of the availability and quality of data is important. The information typically required for screening for TBML include the following:
- Customer – Name, address, countries, company registration and other details, data on key executives, stakeholders, and beneficial owners
- Type of trade finance – LC, bank guarantee, shipping guarantee, etc., and relationships to other trade finance contracts
- Trade finance events – Life cycle events depending on the type of trade finance, such as issuance, amendments, or cancellation
- Parties to the trade finance – Includes internal and external parties, such as shipping company, insurance company, trade finance broker, etc.
- Goods and services – Details of the individual goods or services involved, information on pricing and quantity of goods, etc.
- Shipment details – Shipment locations, shipping vessel number or identifier
- Payment transactions – Invoice details, payment details, payee information
- SWIFT messages – SWIFT messages associated with the trade finance deal (MT103/202/700/701, etc.)
With the growth of global trade and increased regulatory pressures, it is vital for financial services institutions to establish a strong foundation for mitigating TBML risks using processes, controls, robust data models, and technologies. As companies start leveraging technologies, such as blockchain, electronic bills of lading, and electronic issuance, traditional documentary trade finance will become more efficient.
Institutions need to keep up with the technological advancements and regulatory pressures by adopting tools to automate TBML monitoring and having strong controls around their data quality, Customer Due Diligence (CDD) framework, screening, monitoring, and list management processes.
KV Karthik and Manish Mandhyan are a Partner and Associate Director in Deloitte India’s Forensic practice.
