"Unless you are living on a remote planet in a galaxy far, far, away, you have probably used a computer to interact with an algorithm at some point today," writes Lesley Meall for The Treasurer. "You use face-detection algorithms when you tag somebody on your mobile phone; you expand the scope and range of algorithms when you make an online purchase or access a cash machine; you allow algorithms to make decisions on your behalf when you check your email (and don't look at what's been diverted into the spam filter)." Put simply: "An algorithm is any specific method, process or set of rules that can be used to complete a clearly defined task, which could be processing data, solving a problem or achieving a goal."
In the changing world of the corporate treasurer, where timing and best price are more important than ever, algorithms present real opportunities. They offer treasurers an essential means of leveraging computing power and data to maximizing services and/or returns.
Not surprising then that banks and financial institutions with the infrastructure to implement the use of algorithms for high frequency trading are seizing the opportunity to extend such benefits to their large corporate customers. FX is one area where banks are helping corporates explore the benefits.
For example, let's take a US manufacturing company that needs to buy a large amount of AUD to pay for raw materials. Because of the size of the order and the market volatility of the AUD, the trade could have a material impact on the company's P&L. As such the company wants full control over the execution and risk when executing this transaction. With the use the of rule based algorithms and bank infrastructure, the company can: split its currency purchase into small trades; define the start and end time for the strategy and the conditions affecting this; limit the maximum strategy price by setting the frequency and timing of trades; and set the maximum spread to limit the impact of currency volatility and wide spreads on the corporate's average rate.
Developing the complex algorithms to achieve this is a massive undertaking for banks, and there are issues such as the need for back testing, manual oversight and security, but the benefits to the corporate treasurer in terms of order execution and implementing best practice are clear:
- Better strategic execution of orders even in times of low liquidity or and high volatility
- Potential to reduce costs on large orders by slicing and dicing
- Selection of trade timings to realize better average price
- Reduction in human error and time spent in transacting
- Increased time spent on pre-trade analysis and risk management
Further benefits could extend to:
- Better transparency and unambiguous audit trail
- Support with increased regulatory scrutiny and compliance
- Provision of Pre Trade Analytics and Post Trade Transaction Cost Analysis
It's a similar story on the other side of the fence, within the corporate themselves, where the use of algorithms is equally likely to grow to help achieve optimal returns and avoid delays and lost opportunities due to manual processes. Here, an algorithm which could assess liquidity across the group, identify surplus, assess market rates for the instruments under consideration and then identify the best asset class and provider, even suggesting currency conversions where appropriate, would certainly have legs. Take this a step further and introduce machine learning which, given the time of month/year could predict the most optimal trade and, we are in corporate treasury utopia.
However, before we get too carried away, it is still important to remember that the primary concern of the corporate treasurer is managing risk, and the complexity of implementing or even building algorithms, along with the need for highly skilled staff, thorough testing, and the ability to supplement with manual oversight, mean that wider take up is still likely to be slow and cautious.