This article was written by Demetri Papacostas, Head of Corporate and Commodity Specialists at Bloomberg.
Over the last two decades, treasury surveys appeared to indicate that this should have happened long ago, fed by the significant increase in corporate FX and interest rate underlying exposure—particularly to emerging markets. The needs arising from increased exposures became more burdensome as corporate treasury departments lost one of their key support pillars: banks. Banks have significantly reduced their consultative services and analytical support to most clients, with only a very small top-tier clientele being offered analytics and many other advisory services.
These changes were expected to make treasury more self-sufficient and hungry for technology that increases efficiency. But when looking at the practices and processes over a long period, very little seems to have changed in how treasury staff, the treasurer and even the CFO do their jobs. The more processes are targeted for evolution, the more they seem to be mired in manual, Excel-based, fragmented workflows. Treasury is still focused in operational activities: managing cash flow, with foreign exchange at the center, access and control of cash operations, understanding exposures and resolving liquidity issues related to emerging markets. Where are the disruptive forces, seen across so many aspects of the business community, reflected in treasury?
The huge increase in sheer computational capacity now available to treasury departments resulting from cloud-based computing, with the commensurate transparency and data analytics, suggests we are on the cusp of transformative, disruptive change in treasury.
The increase in regulatory scrutiny also supports that view. Specifically, ongoing changes to both local and global tax and banking regulations (EMIR reporting, implementation of ASC842, hedge accounting, margin requirements and validation of best execution) are forcing many companies to rethink both the financial instruments they use and past intercompany loan and liquidity management practices.
Treasury is process. Thus, this disruption will initially focus on the many processes and how they are implemented. As processes are automated, the treasurer has more time to focus on more strategic activities. The market’s increased global volatility and uncertainty are creating the demand internally and forcing authorities to increase regulation. Many treasurers are rising to the challenge. With mundane processes automated, more time is available to devote to higher-level strategies — a win-win for the company and the treasury staff. That is why application of technology will revolutionize treasury this time around.
The technologies available are very different from anything in the past. They include the broad use of API, robotic process automation, artificial intelligence and potential infrastructure changes in how treasury interacts with all stakeholders. The technology can take different manifestations, starting with KPIs (Dashboarding) and moving to Robotic Process Automation (e.g., automatic reconciliation of bank statements). Hundreds of small FX trades are now automatically routed to the best price, executed, booked, confirmed and fed into the ERP with not one human touching a keyboard. Meanwhile, algos are used to trade big FX deals at much better prices than having someone speak on the phone with their favorite FX salesperson. At the most sophisticated shops, computers use artificial intelligence to make some cash investment decisions.
But how will these new technologies impact headcount at treasury? As a treasurer working for a company that is aggressively sourcing RPA projects once told me, “We are already doing more with less. No one is being fired, but, instead, we are getting to do more interesting work.” Treasury can now move from process-oriented, data-gathering and data-manipulating activities to analysis, risk management and a higher level of conversation with the C-suite and the board around planning and risk management. There is plenty of work in creating a strategic approach to treasury.
The benefits of getting this right are readily apparent. For example, most corporations have a hedging policy that specifies a certain percent of FX that needs to be hedged. Treasury areas have refined this policy and average into these hedging percent goals gradually, using a layering strategy. The result: a reduction in volatility, and a muted impact of cash flow and sometimes a reduction of volatility of earnings. Essentially, the corporation ends up with an FX rate that reflects the average exchange rate over that period of time. Ask treasurers or boards why they decided on the percent to hedge and they will typically respond with “I don’t know. It’s always been done this way.” There is no compelling theoretical reason to hedge on that basis.
When the discussion is had with the C-suite, they are clearly interested in minimizing earnings-at-risk while providing treasury with needed liquidity. However, that’s not an easy discussion to have because the treasurer does not have this information. To get this information, he/she must move beyond gathering data and move into heavy-duty analytics, creating an optimal frontier between cash-flow-at-risk and earnings-at-risk. He/she needs all the exposures and hedges (ideally gathered with an RPA) and a sophisticated modeling process that can map risk appetite, market correlations and preferences against all possible outcomes.
Change is promoted by outside factors and market demands and, very important, from within treasury itself. As mundane processes are automated, the quality and availability of the data improve and the opportunity to think more strategically arises. A virtuous cycle can then begin. As treasury professionals think more strategically, more processes can be automated and answers can be provided to the company’s critical questions.
This article is reproduced from the Bloomberg’s Professional Services blog, and is licensed by The Association of Corporate Treasurers.
