Money Laundering Challenges Within the Insurance Sector
12/06/2022 by Ravi Chandel
Money laundering is a severe problem for the global economy, with the sums involved variously estimated at between 2 and 5 percent of global GDP. Financial institutions are required by regulators to help combat money laundering and have invested billions of dollars to comply.
Money launderers are using increasingly sophisticated methods to avoid detection, and regulators are pressing for improved efficacy in anti-money laundering (AML) programs.
Advanced technical platforms provide compliance officers the ability to leverage data, analytics, and advanced features to comprehensively review AML/CTF challenges.
As money laundering (ML) and terrorist financing (TF) methods become ever more sophisticated in an increasingly interconnected global financial system, regulators’ expectations continue to evolve. To satisfy their regulatory obligations, financial institutions must go beyond templates and checklists to develop a deeper understanding of the dynamic risks of their markets, products, customer bases and intermediaries.
As per recommendations from FATF 1, FinCEN 2, GFIA
3 and industry standards, following major risk categories and factors have been identified which are applicable across multiple lines.
Risk Challenges faced by Insurance Organizations in 21 Century
|Risk Categories & Factors|
|Customers||Products||Distribution Channels||Geographical Challenges|
|Rapid customer base growthCustomers are difficult to identify
Structures used to conceal beneficial owners.
Unusual circumstances associated with customer’ business relationship or transactions
Origin or ource of funds
Higher risk individuals
|Products with high-risk paymentProducts which allow large funds, transact large sums, or allow high value transactions.
Products which allow anonymous or easy transfer of value
Products which allow early surrender
Products with simple product features
|Use of Non-Face-to-Face sales channelReliance on outsourcing partners
Management of customer payments by third party
Opaque internal structures of third-party partners who manage sales or services of products
Beneficial owners of third-party organizations.
|Geographical risk rating which impacts customer risk ratingGeographical risk rating which impacts implementation of certain products
Geographical risk rating which can impact risk associated with large value transactions.
Geographical risk rating which can impact risk associated with third party partners or distribution channels.
Money laundering and terrorist financing hav been identified as major causes of concern for global financial systems. The perpetrators are becoming increasingly sophisticated. Money launderers are using increasingly sophisticated methods to avoid detection, and regulators are pressing for improved efficacy in anti-money laundering (AML) programs.
Financial organizations must go beyond basic methodologies to understand the dynamic risk associated with their business.
To implement an effective and efficient AML solution, the financial organization should create a program that can interface and leverage information from the Sanctions Screening module, Customer Due Diligence module, and Anti-Money Laundering module. The sharing of information and risk scores across the modules will improve efficacy of the detection. The automated detection process should include the following:
“Money Laundering schemes are made to make detection difficult.
Complexity is their friend.”
In the previous section, we talked about automated detection. In this section, we will discuss a flexible and focused approach to investigating alerts. The compliance officers, investigator and analyst must be provided with a wealth of tools to perform comprehensive investigations.
The AML solutions should provide the following capabilities for investigators: –
When you have eliminated all which is possible then whatever remains, however improbable, must be the truth
In the previous section, we talked about solution capabilities required to assist investigators. In this section,we will discuss the techniques that can be leveraged to go beyond the obvious. The ever changing nature of the insurance industry, the rise of digital policies, real-time KYC, digital distribution channels, etc., requires insurance organizations to leverage advanced techniques to identify and mitigate dynamic money laundering risk. Some of the advance techniques which can be leveraged by insurance organizations are below:
You can have data without information, but you cannot have information without data
In the current challenging and ever changing landscape, insurance organizations are constantly facing challenges of digital policy renewal, digital TPA’s, real-time KYC, fluid sanction environment, enhanced capacity to hide true identity etc. In addition, the regulatory authorities are imposing stringent rules with respect to processes followed within organizations and the quality and accuracy of regulatory reports.
Insurance organizations need to implement solutions which provide the ability to identify and manage risk factors identified by FinCEN / FATF or similar regulatory authorities. They need to have the e ability to implement automated detection of risky behavior, a flexible and focused approach to investigation and the opportunity to leverage advanced techniques in future.
While implementing top-of-the-line solutions, organizations should be conscious that becoming a leader in regulatory compliance is a journey. The organizations need to perform a self-review and self-assessment to identify the status of the their capabilities. The results of an honest self-assessment will become a basis for charting an improvement course. The journey for an organization from Aspirational – Compliant – Inspirational requires a multi-pronged approach leveraging inputs and support from multiple departments like IT, Compliance, product owners, client facing employees, Internal Auditors, External Auditors, Regulators etc. The implementation would require close cooperation, an integrated and phased approach, and expertise from each department.
Leveraging advanced techniques like Data Science, Machine Learning (ML), Network diagrams, Entity resolution, Entity segmentation etc. requires consistent high-quality data and maturity in interpretation of results. The techniques are only as capable as the quality of the inputs and the way the results are used. The advanced techniques can bring forth great benefits for both the detection and investigation side of the anti-money laundering initiative.
1 – https://www.fatf-gafi.org/publications/fatfrecommendations/documents/rba-life-insurance.html
2 – https://www.fincen.gov/news/news-releases/insurance-companies-required-establish-anti-money-laundering-programs-and-file
3 – https://gfiainsurance.org/mediaitem/d3e45eff-af3c-4d76-9b98-251007fde95b/GFIA%20position%20paper%20on%20AML%20and%20general%20insurance.pdf
Zencos is a global consulting firm that delivers deep expertise, objective insights, a tailored approach, and unparalleled collaboration to help financial institutions confidently face the future. Zencos provides a range of (AMLaaS) AML-AS-A-Service offering for wide variety of Financial Institutions that cater to regulatory requirements for multiple jurisdictions.
HOW WE HELP ORGANIZATIONS SUCCEED
Zencos helps insurance organizations address their AML / CTF risk by delivering solutions which help control and mitigate them. The solutions are hybrid of technically advanced SAS AML products , advanced functional features, and easy to implement IP packages which help organizations successfully meet and exceed regulatory requirements. We help the organizations succeed by doing the following: –