via spreadsheets. FX exposures
were determined by pulling together
spreadsheets from various businesses
and then aggregating and analyzing
that data, much of which originated
in enterprise resource planning (ERP)
systems and other finance and accounting applications.
This approach often raised troubling questions, Gage notes, such as
‘Do we have all the data we need?’
and ‘Is the data we have accurate?’
“Once they retrieved all of that information, treasury people were not
confident that they had the right
data,” he says. Analyses of inaccurate data could distort actual FX
gains and losses.
FX risk management automation
consists of technology tools and platforms that reduce or eliminate manual interventions throughout the end-to-end FX risk management lifecycle.
“There are various tools and platforms
available to potentially automate the
entire currency risk management
lifecycle,” Patri explains. “The most
common components of currency risk
management programs that can be
automated are the upstream exposure
aggregation, netting, and analytics
processes and downstream transaction execution processes,” which
include execution, confirmation, and
settlement.
Gage and Krishnan offer simi-
lar definitions that center on the
automation of most pre-trade pro-
cesses (e.g., exposure analysis and
the automation of workflows) and
post-trade activities (accounting for
a trade in treasury management sys-
tems and accounting applications).
“To me, FX risk management auto-
mation is having a set of automatic
responses to any movement in FX
rates—and this is in both directions
of an FX trade,” Krishnan notes.
“Automated systems should predict
FX risk ahead of the risk itself, and
with predictive analytics, managing
FX risks and outcomes becomes a lot
easier.”
Krishnan lists five functions
these applications support: iden-
tifying FX exposures; recommend-
ing risk-mitigation strategies (e.g.,
hedging approaches); creating
seamless integration to the treasur-
er’s preferred bank(s); equipping
treasury functions with insights on
how to minimize hedging costs; and
leveraging advanced technologies—
including application programming
interfaces (APIs), robotic process
automation (RPA), and machine
learning—to better manage the
end-to-end currency risk manage-
ment process and strengthen deci-
sion-making.
Deloitte’s Patri agrees, noting that
RPA, predictive analytics, and other
advanced technologies are currently driving the evolution of FX risk
management automation solutions
by helping treasury functions more
effectively aggregate, analyze, and
predict FX exposures. “Greater vendor investment in the FX technology space,” he adds, “is driving more
end-to-end automation.”
Triggers and Benefits
The adoption of FX risk manage-
ment automation by treasury func-
tions can be triggered by a range of
factors, including:
The lack of a currency risk
management program.
“We’ve seen companies realize
that they need to build an FX
management program after en-
during a few difficult quarters,”
Gage reports.
FX losses. In other cases, com-
panies with currency risk man-
agement capabilities already
in place may consider automa-
tion after enduring FX losses
or after determining that their
current capabilities require
improvements.
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(continued on page 6)
In addition to mitigating the effects of FX volatility,
automated currency risk management can free up
treasury staff for more value-added activities.