Perhaps one day a company's dedicated treasury algorithms will identify an impending currency liability by reviewing the balance sheet and cash flow forecasts, and using inputs from a range of economic modelling algorithms, determine the most advantageous method of funding the liability.
Communicating directly with the company's banking partners, treasury algorithms will then trigger the optimum foreign exchange execution algorithm in order to fulfil the particular currency requirements – at the right time and the lowest cost.
Even before it even instigates a real transaction, a treasury algorithm might utilise the immense power of inexpensive cloud computing and spend a few short minutes simulating the whole process a few thousand times in advance to refine the funding strategy and tweak its execution parameters.
ET TU, ROBOTS?
Humans won't be relegated to the sidelines just yet. We will form and manage the relationships between the organisations, determine the strategic objectives and develop the algorithms that deliver them (well, until such time as the algorithms start developing themselves), and will conduct essential governance and control functions too.
In fact, the Automation Paradox says as human involvement reduces, the remaining human roles become increasingly important, principally in order to catch errors and unintended consequences before they replicate and amplify; anybody familiar with the plot of The Terminator will understand.
Ultimately however, nobody quite knows the extent to which algorithmic automation will take over in finance or the forms it will ultimately assume, although there are two things of which we can be certain: the world of finance is not going to become any less automated than it is today, and the next few years will bring an exciting and twisting network of fast lanes, tight turns and dead ends.
Todd Tobias Director of Business Projects at ANZ Global Markets.