How Entity Risk Detection Improves AML, Fraud, and Sanctions Operations
By Michael Shearer, Chief Solution Officer at Hawk
For many banks, with older anti-financial crime systems, spotting this type of illegal activity would be a challenge. Customers that are associated with innocuous companies, when viewed in isolation, may appear low risk. However, when shell companies can be identified through reuse of shared attributes such as addresses, telephone numbers and domains this risk can be mitigated sooner.
Entity Risk Detection technology helps banks surface unseen money laundering, fraud, and sanctions risk in their customer attribute data. In this article, we’ll discuss the financial crime risk management problems this technology helps banks solve.
Key Takeaways
- Entity Risk Detection technology helps banks overcome three key financial crime risk hurdles:
- Incomplete understanding of the customer
- Inability to identify suspicious associations between customers
- Manually intensive, lengthy, and disconnected investigations
- Entity Risk Detection technology solves financial crime risk management problems in three key ways:
- Connecting disparate data sources to build customer context
- Detecting suspicious reuse of attributes and identities
- Accelerating investigations
What Problems Does Entity Risk Detection Solve for AML, Sanctions Screening, & Fraud Prevention Teams?
Most banks know that they often have multiple unconnected references to the same person or legal entity across their customer and account records. In many cases, this presents only marketing and other commercial challenges. However, having multiple references to the same entity, and no way of identifying that they concern the same person, can also expose banks to financial crime risk. When customer information sits in disparate silos, that risk goes unseen.
Banks face multiple obstacles preventing them from getting a full view of financial crime risk:
- Incomplete understanding of the customer
- Inability to identify suspicious associations between customers
- Manually intensive, lengthy and disconnected investigations
1. Incomplete Understanding of the Customer
Banks often have multiple references to individuals in various disconnected systems. These disconnected data sources can hamper the efficiency of operations. With data spread across siloed systems, investigators lack a consolidated view of customer activity and relationships.
Without a comprehensive understanding of customers’ activity, transaction history, and relationships, investigators can miss suspicious behavior. This lack of context forces investigators to spend an inordinate amount of time and work gathering information instead of efficiently and effectively mitigating real threats.
2. Inability to Identify Suspicious Associations between Customers
A lack of connected and rich customer data prevents the identification of suspicious associations between customers and the identification of wider financial crime networks. Incomplete or inaccurate data leads to missing connections and overlooked associations, resulting in a failure to reveal the full scope of suspicious activity. Without a comprehensive view of their customer portfolio, investigators will struggle to fully mitigate financial crime risk.
3. Manually Intensive, Lengthy, and Disconnected Investigations
Misaligned data sources, the lack of context, and the lack of rich data features all combine to form one fundamental problem: lengthy and ineffective financial crime investigations. Without access to a clear view of customer risk, investigators must spend time and effort improving that view on their own. Manual and repetitive processes prolong investigations, incurring operational risk that a key line of inquiry is overlooked.
How does Entity Risk Detection Help Financial Institutions Manage Money Laundering, Sanctions, and Fraud Risk?
Entity Risk Detection provides the capability to connect customer and associated/connected party data and analyze it for financial crime risk. Entity Risk Detection technology solves financial crime risk management problems in four key ways:
- Data streamlining and consolidation
- Clear view of customer and associated/connected party risk
- Customer risk visualization
- Faster and more effective investigations
1. Data Streamlining and Consolidation
Entity Risk Detection helps banks overcome the challenges of misaligned data sources by delivering a single customer view. The technology matches pieces of customer data and aggregates them in a comprehensive and up-to-date customer profile. This improves the quality and availability of contextual data, making investigative processes more efficient and effective.
2. Clear View of Customer and Associated/Connected Party Risk
The context provided by Entity Risk Detection allows investigators to better understand the risk associated with customers. With the contextual information made available by Entity Risk Detection, investigators can quickly surmise whether the profile and activity of given customer makes sense as legitimate behavior. As a result, banks can detect more financial crime risk and improve their risk coverage.
3. Customer Risk Visualization
Criminals almost never act alone; they usually act in a network. Banks need the ability to map those networks and establish the extent of the risk exposure so they can better determine their next course of investigative action.
The context provided by Entity Risk Detection helps investigators better visualize networks of high-risk entities. With Entity Risk Detection, banks can look at the links between different customer profiles. This empowers banks to fully leverage network analysis, identifying financial crime collectively—rather than on a one-by-one basis.
4. Reduced Investigation Time and Costs
The single customer view provided by Entity Risk Detection streamlines investigation processes. With all customer information consolidated into a single profile, investigators can quickly gather, analyze, and synthesize the information they need to report on suspicious activity and adjust controls. This enables banks to mitigate financial crime risk sooner and more effectively.
Hawk’s Entity Risk Detection Technology
Hawk’s Entity Risk Detection technology helps banks gain a more comprehensive view of the financial crime risk in their customer portfolio. By consolidating data, resolving entities, and analyzing networks, banks can use Entity Risk Detection to surface unknown risk and act accordingly. Hawk’s Entity Risk Detection technology integrates with a full suite of financial crime risk management tools, including Transaction Monitoring, Customer Screening, Payment Screening, Customer Risk Rating, and Transaction Fraud Monitoring.
To learn more about Hawk’s Entity Risk Detection technology, request a demo.