As businesses drown in piles
of data, reporting methods
are evolving to analyze and
present information more
effectively, and even suggest
what steps to take next.
BY RICHARD GAMBLE
out positions, then report the net exposure.
By applying the company’s hedging policy—
expressed in rules or guidelines—it could
identify potential trades to hedge the exposure most efficiently, as well as the specific
instruments, maturities and dealers involved.
Not only would the software
shorten a usually laborious
process, it could execute the
trades, book them and register
the confirmations. All a person
would have to do is review the
recommendations to ensure that
they are appropriate and execute
them. This is not science fiction,
Higdon insists. It’s happening.
“Artificial intelligence has come
to treasury,” he declares.
For global companies with multiple sub-
sidiaries in several countries using many eRP
systems, he adds, sophisticated reporting can
mean fewer hedges and lower costs with more
reporting program can import and analyze the
cash forecast, which itself may be an intelligent,
software-generated report, and review current
CP outstandings and maturity dates. After the
program applies funding policy and supplies
the amount of CP, maturities and dealers to use,
the responsible party only needs to approve the
transactions. What once took hours (and still
does take hours at many companies)
can be done in seconds, Higdon says.
“All the manual steps can disappear
except for the approval.”
For treasury managers, better
forecasting typically is the goal. The
explosion in captured data has led to
more sophisticated mining tools and
more accurate, longer-range forecasts,
reports Chuck Colliton, treasury
practitioner executive in the global
business solutions group at Bank of America