Research Note: Data and a National Trust Bank and a Trust Company’s Responsibilities
The question of data ownership, accuracy, and responsibility for conveying that accuracy to clients is complex and can vary depending on the specific roles and relationships involved. However, I can provide a general framework for understanding this issue in the context of trust accounting and portfolio accounting systems:
1. Data Ownership:
a) Trust Accounting Systems:
* The trust company or bank typically owns the data as they are often the custodian of the assets.
* They have primary responsibility for maintaining accurate records of all transactions, holdings, and corporate actions.
b) Portfolio Accounting Systems (for RIAs):
* Data ownership is often shared between the custodian and the RIA.
* The custodian owns the primary transaction and holding data.
* The RIA may own derived data (e.g., performance calculations, custom categorizations).
2. Responsibility for Accuracy:
a) Trust Accounting Systems:
* The trust company bears primary responsibility for data accuracy.
* They are responsible for ensuring correct processing of transactions, corporate actions, and maintaining accurate valuations.
b) Portfolio Accounting Systems:
* The custodian is primarily responsible for the accuracy of core transaction and holding data.
* The RIA is responsible for the accuracy of any data they input or derive (e.g., performance calculations, custom asset allocations).
* The portfolio accounting system vendor is responsible for the accuracy of their calculation methodologies and system functionality.
3. Conveyance of Accuracy to Clients:
a) Trust Accounting Systems
* The trust company is typically responsible for conveying accuracy to clients.
* They often provide detailed statements and have direct client relationships.
b) Portfolio Accounting Systems
* The RIA is usually responsible for conveying accuracy to clients.
* They typically use data from the custodian and portfolio accounting system to create client reports and communications.
4. Regulatory Considerations
* Both trust companies and RIAs have fiduciary responsibilities to their clients, which include providing accurate information.
* Regulations like the SEC's Custody Rule (Rule 206(4)-2) place specific requirements on RIAs regarding the safekeeping and reporting of client assets.
5. Data Discrepancies
* In cases where there are discrepancies between systems (e.g., between a custodian's data and an RIA's portfolio accounting system), there's often a reconciliation process.
* The entity with the direct client relationship (trust company or RIA) typically takes the lead in resolving and explaining any discrepancies to the client.
6. Third-Party Data
* For data sourced from third parties (e.g., market data providers), the responsibility for accuracy often lies with the data provider.
* However, the trust company or RIA may have a duty to perform reasonable checks on this data and to promptly address any identified inaccuracies.
7. Client Agreements
* The specific responsibilities for data accuracy and reporting are often outlined in client agreements or service contracts.
* These agreements may specify the frequency of reporting, the level of detail provided, and the process for addressing any errors.
8. Best Practices
* Regardless of legal responsibilities, best practices involve clear communication with clients about the sources of data, any known limitations, and processes for addressing inaccuracies.
* Many firms implement multiple layers of data validation and reconciliation to ensure accuracy before client reporting.
While the specific responsibilities can vary, the entity with the direct client relationship (trust company or RIA) typically bears the primary responsibility for conveying accuracy to the client. However, this responsibility is underpinned by a complex ecosystem of data providers, custodians, and technology vendors, each with their own responsibilities for maintaining data accuracy within their domains.
The trend in the industry is towards greater transparency and real-time access to data. This is putting increased pressure on all parties to ensure data accuracy and to have robust processes for quickly identifying and correcting any errors. It's also driving the development of more sophisticated data governance and quality assurance processes within wealth management organizations.