GOE’s default setting for probability scoring is Dynamic Programming, but it can also be configured using Monte Carlo if your firm prefers that approach.
Bridging the gap between the theory and practice of goals-based wealth management
GOE® uses a proprietary methodology to actively manage a dedicated portfolio for each goal a client has. The GOE approach accommodates goals with different timeframes, different levels of importance, and different funding commitments from the client. Without GOE at the helm, goals-based wealth management can be very difficult to execute at scale.
1
Personalized & Goals-Based
Individualized portfolios are created to pursue specific client goals.
2
Optimized for goal achievement
Proactive allocation changes aim to maximize probability of reaching each goal.
3
Probability Driven
GOE accounts for investor risk tolerance as well as risk capacity.
Custom implementation options
Probability Framework
Portfolio Flexibility
GOE comes with a set of models arrayed across an efficient frontier, ready for use “out of the box.” However, it can also be deployed with any set of models including those already in use at your firm.
Capital Market Expectations
CMEs can be provided by your firm’s home office or by the multi-asset experts within Franklin Templeton Investment Solutions.
Open Architecture
GOE is product agnostic. Portfolios can contain almost any mutual fund or ETF to represent the various asset categories.
Hosted Solution
GOE can be hosted by Franklin Templeton and connected to your tech via an extensive API library. Depending on configuration, it can actively manage the portfolios or simply provide your advisors with a probability-based portfolio recommendation.