Business

What do you need to know about Banking with High profile Customer Risks?

Failures to recognize high-risk customers and place them in the high-risk customer categories could lead to non-compliance issues and hefty fines following the violations of Anti Money Laundering programs.

Know about Banking with High profile Customer Risks?

Unfortunately, most of the institutions rely on manual reviews, old-fashioned rules and simple account opening questionnaires, to recognize and segment high-risk customers, including private businesses, Money Services Businesses (MSBs), and NGOs. But the risk doesn’t remain the same and customer activities changes from time to time. So How do you make sure that your segment high profile customer risks right?

The issue can easily be resolved if the banks devise a category lists of risks and verify every onboarding customer against the identified checklist in each category. A conventional category that is used by many banks globally contains three levels. Starting from low profile customers to medium profile customers and eventually high profile customers. This list provides an overview of the category to which high-risk customers should be placed.

Low Profile Customers Risks:

Financial Institutions place customers or businesses having low money laundering risks in the low-risk client category. The individuals or entities, whose sources of income are easily identifiable, and financial transactions made through the accounts associated with these customers comply with known regulations are placed in the low-risk client category.

The exceptions are that any politically exposed person or a person having a high net worth is not eligible for this category, no matter their sources of income easy to identify or not. The examples of low-risk customers are employees having a well-organized salary structure, customers with low financial transactions, having a low account turnover, and minimal income.

Other than these, accounts of government departments or those entities which are owned by the government. For customers that are eligible for this category, simple identity verification is enough.

Medium Profile Customer Risks:

The banks and financial authorities put individuals or entities possessing the potential to cause more than average risk of money laundering to the bank in medium or high profile customer risk categories. The decision to put the client in either high-risk customer or medium risk customer category depends upon the background information about the client, location of the operations, income sources, and client’s profile. The example of medium profile customers includes clients working in a jurisdiction that has a notorious financial history, or clients with doubtful sources of income.

High Profile Customer Risks:

Simply put, the banks should place those individual or business client having an undoubtful and uncertain source of income, in high-risk customers list. However, there is no hard and fast rule. The decision to put clients on this list varies from customer to customer.

But once a customer is categorized in this list, banking platforms must assure that enhanced due diligence with on-going pnbhrms login AML monitoring is being done for that particular person. Without stringent monitoring of these clients, banks are exposed to a clear violation of AML and KYC regulations and could face hefty fines and even bans. Here is a generalized list of customers that are normally placed under this category:

  • Politically Exposed Persons (PEPs)
  • Non-Resident Clients
  • Charity, Non-Governmental organizations
  • Any organization that receives donations or fundings
  • Firms having undeclared beneficial owners
  • Persons with High Net worth

Creating a realistic money laundering risk profile will serve financial institutions very well. Not only will it help them in AML compliance, but it will also help them avoid organizational fraud, protect their reputation, and reduce liabilities.

Fortunately, for banks, the Fin Tech industry has developed automated screening software, which performs AML screening more accurately and in realtime than their human counterparts.

 

 

 

 

 

 

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