High Net Worth Individuals
High net worth (HNW) individual monitoring requires contextual analysis of high-value transactions and lifestyle patterns to distinguish legitimate activity from suspicious behavior. This use case addresses reducing false positives from high-value purchases, understanding income sources and investment patterns, analyzing counterparty relationships, identifying money laundering networks, tracking behavioral changes over time, and enabling holistic multi-dimensional analysis that connects income sources, countries, investments, companies, and familial links.
The Challenge¶
Financial institutions face significant challenges in monitoring HNW individuals:
- Lifestyle complexity — With top end handbags often costing in excess of £20,000, the alerts holistically triggered run the risk of simply creating noise rather than information
- Lack of context — A traditional transaction monitoring platform does not provide any context to customer behavior
- Behavioral changes — Has the customer's behaviour profile changed since the last review?
- Insufficient analysis — Simply looking at income and outgoings for a customer is not enough—it maybe exactly as the customer has said (say $4MM income $3.8MM expenditure)—so is an alert for a $20,000 handbag what KYC should really be looking for?
- Multi-dimensional analysis — What the organization really needs to do is to look at the sources of the income; the countries, investments, companies of familial links
- Transaction context — The nature of the expenditure also need to be what has been brought, where and how? The nature of these transactions need to be reviewed holistically, perhaps a customer bought a company in a previous year and then continues funnelling money to this investment
- Network complexity — Most large scale money laundering tends to involve networks of individuals and organizations with a controlling force
Why EKG is Required¶
Enterprise Knowledge Graphs provide powerful capabilities for HNW monitoring:
- Holistic view — It is only through using a holistic view that you can get analysis data to give you the context to knowing something different has happened in regard to entities and individuals concerned
- Counterparty analysis — A holistic view enables you to connect these counter parties to see if these financial interactions make sense
- Contextual monitoring — The ability to monitor activity in context of a holistic view enables the organization to have valuable insights on what these individuals are doing
- Network identification — The EKG enables the easier identification of all networks (bank accounts, transactions and customers) which in turn allows for swift analysis of alerts
- Alert clustering — A cluster of automatic alerts all in a given network identified by the EKG can be swiftly escalated for review (this is detailed further in the use case on AML)
- Multi-dimensional analysis — Connect income sources, countries, investments, companies, and familial links
- Temporal analysis — Track how customer behavior and financial patterns evolve over time
This is an important lower level analysis task that knowledge graph excels at because as most large scale money laundering tends to involve networks of individuals and organizations with a controlling force.
Business Value¶
- Enhanced risk assessment — This information can in turn be used to more effectively assess an individual for AML issues and risk
- Reduced false positives — Contextual analysis reduces noise from legitimate high-value transactions
- Proactive monitoring — Detect changes in customer behavior and financial patterns early
- Network insights — Understand HNW customer networks and relationships for risk assessment
- Operational efficiency — Automate alert clustering and prioritization for HNW customers
- Regulatory compliance — Meet enhanced due diligence requirements for HNW customers
- Customer experience — Minimize disruption to legitimate HNW customers while maintaining security