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. 

A Comprehensive approach to AML/CTF for Insurance Sector

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  1FinCEN 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

PEP Exposures

Payment Methods

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.

Risk Factors

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.

Automated Detection of Risky behavior

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: 

  • Detection capabilities of the solutions depend on variety, robustness, and quality of data. 
  • Identify and manage relationships between entities like policyholder – nominee, policy holder – claimant, claim -appraiser, appraiser – claim handler, etc.
  • Build and implement automated scenarios that detect behaviors recommended by FATF e.g., structuring, large value transactions, unrelated nominee, frequent transfer of policy, etc.
  • Build and implement trigger-based scenarios. These scenarios are triggered when a specific event occurs. e.g., addition of an unrelated nominee, etc.
  • Periodic review of scenario efficacy and review of scenario parameters.
  • Alert detection and grouping should be performed at entity level ex. All alerts are identified at policyholder level. This provides a 360 view of policyholder behavior.

“Money Laundering schemes are made to make detection difficult.

Complexity is their friend.”

Flexible and Focused Approach to Investigation

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: –

  • triage alerts with respect to Business Unit or type of alerts or  product type or risk score, etc.
  • display alert and entity related information in Alert UI. The UI should have comprehensive and detailed information.
  • display case, alert, and entity related information in Case UI. The UI should have comprehensive and detailed information.
  • BPM tool like workflow which can be used to enforce strict business processes.
  • network display capabilities where all entity relationships are mapped.
  • abilities to execute a search or query without requiring technical skills
  • add / display attachments and comments to case. The investigator should be able to display and read older comments and attachments.
  • display audit trails for all activities performed during an investigation.
  •  ability to assess scenarios on UI.

When you have eliminated all which is possible then whatever remains, however improbable, must be the truth

Leveraging advanced techniques 

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: 

  • Statistical Modelling / Data Science / Machine Learning – Organizations should leverage the power of statistical modelling to identify underlying patterns and dynamic money laundering risk. Statistical models should be leveraged as tools to improve detection capabilities.
  • Network Diagrams – Organizations should leverage network diagrams to identify potential relationships between entities and organized crime networks. Network diagrams should map parameters like address, phone, email, etc., for all entities. This will highlight any underlying relationships like policyholder and nominee  using the same email address.
  • Entity Resolution – Organizations should implement solutions which have the capability to perform entity resolution. This is especially relevant for the insurance sector as documentation / KYC required for different entities like nominee, policy holder, and claimant is quite different. It is easy to conceal the same entity under multiple roles.
  • Entity Segmentation – Organizations should have the ability to create a statistical model powered cluster of entities that display similar empirical behavior. These clusters should be the basis for determining explicit scenario parameters to suit the population. 

You can have data without information, but you cannot have information without data

Features of  the Organizational Journey        


  •  Organization has a large database, but it is implemented in multiple solutions. The integration and interaction between solutions are difficult.
  •  Organizations look to derive value from data, but quality of report and data reconciliation is challenging.
  •  Organization executes AML monitoring using manual or rule-based detection.
  • Investigation team has limited resources for comprehensive investigation.


  • Organization has comprehensive single source data.
  • Organization has a solution implemented for automated alert generation and investigation.
  • Organization can derive value from data but is limited by a large volume of alerts.
  • Investigation team faces challenges in false positive ratio,  alert quality and scenario efficacy.


  •  Organization is able to create value from data.
  • Organization can leverage advanced techniques to improve detection and investigation.
  • The alert quality is dramatically improved, and scenario efficacy is at a higher level.
  •  Organization performs a periodic health check review of the AML solution.

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

4- https://www.sas.com/en_in/software/anti-money-laundering.html


About Zencos

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.


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: –

  1. Zencos AMLaaS solution leverages cohesive, high-performance software platform that combines, cleanses data, and accelerates the analytics life cycle. The solution has inbuilt capabilities to execute data quality analysis, generate data quality reports and identify data quality improvement opportunities.
  2. Zencos AMLaaS solution leverages state of art ability within SAS AML solution to access data existing in external databases and generate global search indexes for external tables. This allows solution users to access external data and perform searches on external data within the solution UI. 
  3. Zencos AMLaaS solution empowers organizations with a sophisticated, end-to-end anti-money laundering platform that provides transaction monitoring, customer due diligence, sanctions and watchlist screening, and regulatory reporting. 
  4. Zencos AMLaaS solution has ingrained IP from Zencos which can enhance the OOTB functionalities, features, and capabilities of AML solution. Some of the enhanced features are as below: –
  5. The solution brings comprehensive and holistic investigator homepage UI which provides visibility to alert queues, investigator performance metrices, Automated task notifications, Manual data entry, Global, Advanced and Entity level searches and access to recently viewed entities.
  6. The solution brings comprehensive, holistic, and enhanced Alert UI which contains Alert summary, Alert activities history (audit report of all the activities performed on the alert by solution users), Alert history (Alerting events, scenario events, transaction details and contributing transaction details), Scoring history for the alert, Customer Information (Comprehensive information associated with the customer), Related Entities and Network visualization.
  7. The solution brings comprehensive, holistic, and enhanced Case UI which contains Case summary, Alerted Entity Information, Case Narrative, Entities Related to the Case, Network Visualization, Automated Case workflow, Ability to add comments and attachments and Case version history with change tracker.
  8. The solution brings comprehensive Audit tracking and reporting mechanism. 
  9. The solution brings comprehensive management report and visual reporting capabilities. The visual reporting capability has ability to leverage templates to build custom reports.
  10. The solution brings capabilities to build and deploy regulatory reports. Regulatory reports can be customized based on changes from regulators. The workflow can also be deployed to automatically generate regulatory report based on investigator feedback.
  11. Zencos AMLaaS solution empowers analysis and investigation of the alerts at an entity level. Entity level investigation allows investigator to view the entity behavior in a holistic and comprehensive level. The entity level investigation also allows investigator to view historical behavior of the alert, alert score, customer score and customer due diligence.