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Assessing the Computing Challenge

Portfolio analytics is a computationally complex, non-linear problem, requiring the analysis of millions of possibilities that lie in the solution set. It's necessary to simulate a vast number of different portfolio compositions to find the one that maximizes yield or minimizes using exhaustive search methods.

In practice, it is necessary to simulate different weight compositions (e.g., asset allocations), individual assets, asset price movements and holding periods. Increasing the number of parameters significantly increases the simulation time, and running several customer scenarios can take hours or even days on a single computer. A portfolio analysis, based on a customer's yield and risk targets, must compare millions of possible outcomes to determine an optimal solution:

  • Weight compositions (thousands of combinations)
  • Assets (hundreds in more complex portfolios)
  • Asset price paths (millions)
  • Holding periods (several)
Delivering the Solution

In order to shorten the overall simulation time, Protégésoft developed tools that take advantage of high-performance computing (HPC) resources. We developed the Financial Portfolio Builder* (FPB), which features a unique dynamic portfolio rebalancing and monitoring solution. This tool offers FSIs a cost-effective alternative to their outdated legacy system and processes, which often include Microsoft* Excel spreadsheets.

Summary and Metrics

 

The Protégésoft FPB is helping FSIs lower costs, address new market segments and achieve higher returns for customers.

 

1) Improving Workload Productivity

 

FPB is creating cost and time savings for wealth managers to service customer accounts, as shown in Table 1.

 

 

Legacy

systems

Itanium®-based system

Number of accounts per hour

2

58,000

Effort to rebalance and print 100 dealing tickets

9 person days

Straight through processing

(STP)

Training required

6 months

0.5 days

Main Points

Data Integrity Issues, portfolios weren’t optimized

No Human intervention needed, complete automation of portfolio optimization

Table 1. Efficiency Scenarios

 

Along with providing efficiency gains, FPB eliminates data integrity issues associated with human intervention and ensures portfolios are truly optimized.

 

2) Addressing New Markets

 

With the savings achieved through workload productivity improvements (described in #1), FSIs can lower the cost to service customer accounts and create new opportunities to serve previously unprofitable customers.

 

For example, FPB-related productivity improvements allow 2,500 clients with SG$10,000 (Singapore dollars) to generate the same revenue as 100 clients with SG$500,000 investment portfolios.

 

Case 1:

·  Mass affluent individuals

·  Portfolios start at SG$10,000

·  Fees @ 3.0% = SG$300

·  Revenue 2,500 clients = SG$750,000

 

Case 2:

·  High net worth individuals

·  Portfolios start at SG$500,000

·  Fees @ 1.5% = SG$7,500

·  Revenue 100 clients = SG$750,000

 

This revenue model demonstrates how FSIs can expand into new market segments and create new sources of revenue.

 

3) Achieve Higher Returns

 

Protégésoft simulation testing has shown that dynamically rebalanced portfolios deliver 29 percent greater returns than "invest and hold" portfolios over a three year period.

 

4) Manage Risk Dynamically

 

At the click of a button, wealth managers can use FPB to make buy, sell and hold decisions based on 'up to-the minute' market analytics while conforming to the risk preferences of their individual clients. As market conditions and sentiments change, investors are able to address their investment risk promptly.

 

With the FPB solution, portfolios can be easily rebalanced quarterly, yearly or even on an ad-hoc basis, so that investors can enjoy risk adjusted returns on their portfolios.

 

5) Assist in Regulatory Compliance

 

FPB simplifies compliance processes, such as anti-money laundering and anti-product churning activities and enforces proper roles and responsibilities between parties.

 

 


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