When the Department of Labor’s new fiduciary rule went into effect on June 7, 2016, it signaled changes to the traditional advisory model from commission to fee-based compensation and will substantially change product fees and features. Many within the industry are scrambling to understand which approaches to take, whether they should comply, or just get out of the business. Those that remain have much to consider and address when it comes to the data required to govern and comply with the new law.
Like other regulations, having complete, consistent, timely, and secure data will be critical to providing evidence of compliance and ensuring companies remain compliant on an ongoing basis. Unfortunately, underneath those new applications, laptops, and mobile devices lies an array of data problems and common root causes that retirement planning, wealth advisory, insurance, and brokerages will need to address. Peter Ku, head of Financial Services Data Solutions – Informatica, LLC, identifies a few examples of the coming challenges and offers suggestions on overcoming them:
Verifying and qualifying clients for specific recommendations.
- Lack of a central/authoritative source of customer and client information across systems with current and accurate relationship information between clients and advisers
- Data quality errors across CRM, client onboarding, trading, and marketing systems
- Too many siloed sources of customer, account, and interaction data across the business
- Lack of coordination and governance of customer information across independent business applications
Track, monitor, and ensure fiduciary activities.
- Lack of real-time access and sharing of pricing, quote, and customer interaction information for monitoring and surveillance and/or,
- Existing processes are heavily manual, complex, and difficult to maintain
- Point to point integrations and use of hand coded processes that lack real-time delivery of data across sales, service, and transaction systems
Satisfy disclosure requirements for designated fiduciaries leveraging 3rd party services.
- Exchange of files and data with 3rd party verification and validation services often incomplete, incorrect, and not available when needed most
- Manual exchange, validation, and remediation of data between in-house systems with 3rd party vendors.
Do these data challenges sound familiar? If so, read on for ideas on addressing them.
Make data management a business vs. IT priority and establish a data governance program.
Data is as valuable as other assets and must be managed as such. Determining what data is required, how it’s used and how it impacts the business should be defined by the business, not IT. A data governance program can help organize and facilitate business and IT collaboration on data policies, standards, definitions, and processes to ensure the business knows what data is required, why, by whom, and how it impacts business success.
Establish a single source of customer, client, and product data for enterprise use outside applications and data warehouses.
Customer, product, and adviser information is often created in standalone systems with little to no coordination. When shared data changes in one system, it’s crucial that other systems are in sync.
Replace hand coded data integration and quality processes with proven tools.
Whether it’s sharing data and files with 3rd party vendors or between in-house applications, integrating and dealing with data quality errors by throwing people at the problem won’t scale.
Consult with your technology partners and/or industry experts about your data needs.
Figuring out what’s wrong and how to address them requires knowledge and expertise. Trust your technology partners and/or reach out to companies that specialize in data integration, management, and governance for advice.
To learn more about these challenges and how to overcome them with proven strategies and solutions, join Peter for a live webcast on September 21, 2016 at 11am Eastern. Register here.