Next-generation technologies are enhancing performance and driving profitability, and AI is a prime example. In 2020, leading firms that adopted these technologies saw a 51% increase in revenue. AI enables predictive analytics, which uses historical data to forecast future events. This involves generating a mathematical model from past data, which is then applied to current data to recommend actions likely to yield optimal outcomes. AI learns from extensive datasets and uncovers trends that would otherwise go unnoticed. Predictive analytics and AI can significantly transform the advisor-client relationship, from speeding up client onboarding to enhancing portfolio management efficiency.
These advanced technologies provide a deeper understanding of investor behavior and preferences, which is crucial for personalizing the client experience. For instance, with the increasing focus on Environmental, Social, and Corporate Governance (ESG), understanding the specific concerns of environmentally and socially conscious investors helps advisors identify the best opportunities for upselling or cross-selling based on product fit. Advisors armed with actionable insights are better positioned to strengthen client loyalty and enhance satisfaction.
Firms in the data-driven industry face intricate challenges as investor expectations evolve rapidly, increasing pressure on advisors to consistently provide exceptional client experiences. The competitive landscape is also shifting, with new threats from startups and established competitors emerging daily, compelling firms to reassess their operating models and workflows. To maintain a competitive edge, wealth firms must innovate, and AI presents a significant opportunity. However, many AI implementation attempts fall short due to the absence of two crucial components: robust data and expertise in data science.
KEY ELEMENTS OF AN EFFECTIVE DATA STRATEGY
Effective AI relies on a large volume of high-quality data, yet accessing the right data remains a significant challenge for firms throughout the wealth industry. Efficient storage and maintenance of data are crucial, but firms often struggle to implement a data strategy that facilitates easy access while maintaining data security.
The difficulty lies in the time-consuming process of organizing massive datasets, training the machine learning models that underpin AI, and ensuring seamless integration with a firm’s existing back-end infrastructure. Most firms find it costly or impractical to allocate the necessary in-house time and talent for AI deployment. Additionally, defining a use case that provides ROI and is feasible based on available data is complex. For successful AI adoption, it’s essential to secure cross-functional buy-in from key stakeholders across the firm.
A THREE-STEP STRATEGY FOR TRANSFORMATIVE AI APPLICATION
Step 1: LEVERAGE YOUR DATA TO OUTPERFORM THE COMPETITION
The “flywheel” effect of AI means the technology becomes more accurate with each new user. As fintechs scale, their competitive edge also grows. However, these data-driven tools and acquisition techniques are no threat to proactive, established firms. By leveraging accurate and accessible data with the right tools and expertise, you can outperform the competition.
For emerging technologies, firms increasingly depend on external providers to handle large volumes of data and network effects. Our research shows that 73% of leaders use external providers for AI implementation. When choosing an external provider, firms should opt for comprehensive solutions rather than a collection of disparate tools and costly consultants. Most importantly, a successful partnership hinges on strong skills and proven experience.
Step 2: Select thoroughly your AI specialists
Industry leaders understand the complexity of AI and recognize their own limitations in terms of time, expertise, and infrastructure. Consequently, few opt to navigate this terrain alone. Leaders predict a nearly 20% increase in spending on next-gen technologies like AI and Blockchain by 2023. To future-proof your growth strategy, partner with the right experts to advance your goals. Effective AI implementation requires identifying the best applications for tangible ROI.
Begin by designating an AI business champion who understands how AI will advance your firm’s unique business objectives and can effectively communicate this vision. It’s also crucial to consider the breadth of the team needed to execute the work, which may include data engineers, data scientists, and product development experts.
To share the costs and risks of technological innovation, industry leaders are increasingly outsourcing expertise and investing in solutions from third-party providers. In fact, 59% of leaders plan to outsource expertise over the next two years, compared to 37% of non-leaders. Identifying the right partner to accelerate your business goals is essential for maintaining competitiveness moving forward.
Step 3: FAST-TRACK FROM PROOF-OF-CONCEPT TO RESULTS
Many firms find it challenging to progress beyond the proof-of-concept stage. To realize business value, they must bridge the gap between desired outcomes and measurable results. Although this can seem daunting, it is possible to conceive and execute within 90 days or less. Success hinges on an effective partnership and proper data preparedness.
Wealth management firms can enhance client engagement and boost their marketing ROI by licensing advisor marketing content from a reputable provider. For instance, Broadridge has trained its engagement model using hundreds of millions of data points to analyze which marketing content, such as articles and newsletters, is most engaging to specific recipients. This model has been successfully employed to increase prospect and client engagement, resulting in a 300% rise in article recipient engagement.
SMART AUTOMATION DRIVES BUSINESS GROWTH
AI continuously adapts and learns from every client interaction, enhancing its understanding of clients’ current positions and the factors influencing their behavior. By integrating AI with predictive analytics, you can be ready to address investor needs at any time. Advisors can easily identify the actions and personalized communications that will enhance client loyalty and execute these automatically.
Firms often rely on a limited selection of data sources to meet investor demands, such as investor profiles or available securities and investment products. However, AI enables more intelligent personalization and prospecting by analyzing thousands of behavioral variables that impact revenue, including:
- Demographics
- Current and past products
- Last contact
- Contact channel
- Transaction data
Recommended actions might include sharing content relevant to client needs, customizing product recommendations, or making essential portfolio adjustments. Equip your team with the knowledge to retain and grow your clientele. Unleash your potential to achieve boundless gains.
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