Sales boost
Optimized fund selection
Optimized portfolio
Expanded growth potential
Advisors rebalance portfolios, offering asset managers a chance to suggest better-performing replacements. A global asset management firm sought a holistic, data-driven approach to fund replacement at scale, aiming to provide quantitative, performance-based recommendations to financial advisors.
Key challenges
Ensuring recommendations are performance-based
Need for data-driven fund replacements
Aligning with advisors' client goals
The solution
Framework development
Evaluated fund attractiveness
Scored via extraction
Mapped relevance
Data analysis
Analyzed funds
Scored advisor relevance
Identified replacements
1
Recommendation engine
Built rule-based engine
Ranked funds by appeal
Integrated real-time strategies
2
Advisor integration
Integrated into workflows
Streamlined decision-making
Gathered feedback
3
Optimization
Greater market reach
Updated market data
Expanded market reach
Revenue boost
Unlocked sales
Streamlined fund transitions
Greater audience involvement
Advisor efficiency
Streamlined choice
Data-driven picks
Faster decisions
Market edge
Refined competitive stance
Outperformed rivals
Adjusted portfolio allocations
Expansion
Scale the recommendation engine
Enhancement
Refine models with real-time market data
Optimization
Improve fund scoring for better replacements
