Wealth & asset management (WAM) firms play a crucial role in assisting consumers in managing their assets and achieving their financial goals, and as such, delivering quality customer experience (CX) is high on the priority list. Asset management firms have been mostly preoccupied customer experience and growth but have not proportionately developed adequate financial crime controls, often resorting to short term incident driven approaches. Implementing efficient and digital due diligence processes can create a frictionless customer experience without compromising financial crime compliance obligations.
The recent ‘Dear CEO’ letter from the UK’s Financial Conduct Authority (FCA) underscores the significant financial crime risks and compliance challenges faced by these entities. The scale of consumers involved in this industry, with over 1.8 million portfolios and 14.3 million stockbroking accounts, elevates the sector's risk profile against money laundering concerns.
Many of the firms in this sector operate on manual and siloed processes lacking a holistic view of customer risks and financial crime vulnerabilities. In response to these concerns, wealth management firms are urged to enhance financial crime compliance, with a focus on reducing harm, raising standards, and improving the industry's reputation.
Efficient customer relationship monitoring
The asset and wealth management business model relies heavily on building close relationships with customers and third parties, making it challenging to implement robust monitoring processes.
Despite regulatory requirements, firms struggle with due diligence implementation, fearing friction in these critical relationships. Transparency in KYC (Know Your Customer) data is essential to prevent reputational damage, and asset management firms need to leverage third-party data from sanctions, Politically Exposed Persons (PEPs), beneficiary ownership and adverse media lists for enriched client information, ensuring visibility across distribution layers. Automating this process provides enables more efficient customer relationship monitoring.
Integrated, enhanced due-diligence systems
Amid regulatory changes, wealth management firms often overlook the importance of robust financial crime frameworks, leading to fragmented systems and processes. By using an automated financial crime compliance software, firms can harmonise customer commercial information, suitability data, and financial crime risk assessments, creating a centralised approach. This not only reduces manual efforts but also ensures a comprehensive understanding of clients, enabling more effective governance frameworks.
Digital KYC data management
Automation allows WAM firms to digitise and streamline KYC processes, making them more efficient and less prone to errors.
Leveraging third-party data lists for client information enrichment enhances transparency and ensures that due diligence is conducted thoroughly. This not only prevents blind spots but also facilitates a smoother experience for investors, who no longer need to repeatedly provide the same documentation across different jurisdictions. Through advanced analytics and machine learning algorithms, firms can identify unusual patterns or behaviours, helping them comply with regulatory requirements without creating unnecessary friction in these critical relationships.
Client screening and risk assessment with artificial intelligence (AI)
AI can streamline the client screening and transaction monitoring processes for wealth and asset management firms by automating risk assessments and enhancing due diligence efforts. AI algorithms can analyse vast amounts of structured and unstructured data from various sources, including PEPs, sanction lists and adverse media lists to provide a comprehensive profile of clients. This level of automation ensures a thorough and up-to-date understanding of clients' backgrounds, business activities, and potential associations with high-risk entities.
By weaving AI into your systems, you can analyse vast amounts of transaction data, learning from historical patterns to detect anomalies in real-time. By setting predefined rules and thresholds, AI can automatically flag transactions that deviate from expected behaviour, indicating potential financial crime risks.
AI can assign risk scores to clients based on various factors, including their transaction history, business relationships, and geopolitical considerations. This automated risk scoring system helps prioritise attention to higher-risk clients, ensuring that compliance resources are allocated efficiently. It also generates automated alerts for compliance teams when a client's risk profile changes significantly or when there are potential red flags. This not only accelerates response times but also aids in creating comprehensive reports for regulatory purposes.
This, a transformative approach to financial crime compliance processes at WAM firms can convert mere regulatory requirements into being strategic business advantages.
Photo by Maxim Hopman on Unsplash
.png)
