First, and arguably the easiest, by fine tuning their investment model inputs. To elaborate with a simple example, simply by increasing the accuracy of manager fee and liquidity terms entered in the system, most analytical models produce better results, thereby enabling you to make better investment decisions, and hence generating better returns. Typically, fees and related terms once entered are never looked at again throughout the life-cycle of the investment.

Technology can, in the simplest form, assign an age to the data and prompt portfolio managers to review the data on a periodic basis. More technologically mature organizations can easily leverage their existing hooks in to the data provider systems and update data in real-time/near real-time. Kicking it up a notch, are the staff who are making investment decisions able to perform scenario and sensitivity analysis with ease? Or do they find themselves in a situation where every time they need to conduct analysis they have to run to someone who can do ‘programming’.

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