Data is the Fuel for AI Innovation in Wealth Management: Is Your Data AI-Ready?
By Joe Stensland
BridgeFT
Over the past several years, AI (AI) and Machine Learning (ML) have transformed the wealth management industry, allowing financial institutions and advisors to reduce human error, facilitate faster decision making, improve efficiency, reduce costs, and empower employees. With the power of AI, firms of all sizes have more bandwidth to both serve their clients and grow their businesses. Meanwhile, wealth management consolidators have powerful new tools to onboard and integrate new firms faster and more efficiently. But for users to actually benefit from AI, they need one critical component: accurate and complete data.
On its own, data provides mission-critical insights that power day-to-day operations. However, historically speaking, many companies in the wealth industry have been plagued with archaic data processes driven by flat files and legacy infrastructure. If firms really want to invest in AI, they must first invest in the means to extract and manage high-quality data. Otherwise it’s garbage in, garbage out for AI algorithms.
A strong data foundation is what positions AI initiatives for success—reliable, scalable data is the fuel AI needs to produce optimal recommendations. Trust-worthy data begins at the source, and requires the ability to track creation, enrichment, processing, and distribution of said data. Total wealth data that includes detailed client and investment account data across liquid and illiquid assets are the essential building blocks to power scalable AI operations in wealth management.
For many firms, the back-office operations serve as a data repository—collecting, enriching, validating, packaging, and distributing large volumes of sensitive data on a daily basis. In recent years, this practice has evolved to include outsourced data warehouses that leverage the value of the cloud to support a System of Record for client, account, securities and transactional data—providing a single source of truth that can be used to feed essential systems and applications. This trend towards working with outsourced data experts also greatly improves the prognosis for AI in wealth management.
When it comes to launching, optimizing, or maintaining AI-powered capabilities, firms should question their data processes and quality first and foremost. Regularly assessing your firm’s data’s “AI readiness” ensures the highest likelihood of success. The key factors to consider include:
1. Accuracy: The foundation of any reliable AI solution is the accuracy of the data. Ensuring that your data is error-free and precisely reflects the real-world scenario is critical for generating trustworthy insights.
2. Completeness: Incomplete data can lead to biased or incorrect AI predictions. It’s essential to have comprehensive datasets that encompass all necessary variables to build robust AI models.
3. Consistency: Consistency across your datasets is vital. Uniform data formats and standardization practices help maintain the integrity of your AI models, leading to more dependable outcomes.
4. Timeliness: AI models thrive on up-to-date information. Ensuring that your data is current and reflects the latest market trends and client behaviors enables your AI solutions to be relevant and actionable.
5. Uniqueness: Differentiation in data can provide a competitive edge. Incorporating unique data sources can enhance the richness of your AI models, offering distinctive insights that set your services apart from the competition.
AI has already powered many wealthtech innovations, including applications for advisor marketing, client onboarding, accounting, and fee billing. And the list of use cases continues to grow as AI proliferates. Ultimately, the widespread use of AI across the wealthtech ecosystem can only help enhance the experience for advisors, asset managers, and their clients. This puts a heightened focus on ensuring the data foundation is the strongest part of the AI equation.
Joe Stensland is CEO of BridgeFT.
Learn more at www.bridgeft.com and LinkedIn.
