From the June 2012 issue of Treasury & Risk magazine

Harnessing Data More Effectively

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.

The key to smarter, more decisive treasury management may lie in getting not just reports that supply data, but intelligent reports in which data have been aggregated, sorted and analyzed, reports that may even point out the best steps to take to control risk, optimize returns or improve efficiency. While there’s still a gap between the potential and the reality of such reporting, the gap is closing.

For example, if street protests erupted in a foreign capital, threatening the stability of the government, a corporate treasurer with some of today’s best analytical reports could easily determine the company’s investment exposure to that country’s debt, including holdings in money market funds. This represents significant progress from 2008, when treasury investors worried about how much Lehman Brothers paper they were holding indirectly, through money funds. “It was virtually impossible to find out,” recalls consultant Mike Gallanis, a partner at Treasury Strategies.

As the amount of data captured and stored grows exponentially, reports that were once simple logs and lists have become larger and denser, but not necessarily more transparent, notes Paul Higdon, chief technology officer at IT2, a treasury workstation vendor. Reporting technology is crossing new frontiers so that data can be aggregated and summarized, filtered for the most useful information, arranged in graphic displays and packaged into the reports most useful as tactical business intelligence tools. “Automated reporting can do a lot of the numbers crunching for treasury staffs and show them trends and patterns they need to make decisions,” Higdon says.

“But why stop there?” he asks. When decisions are based on established rules, smart reporting can apply those rules and come up with a decision that executives can review and approve. “There are parameters around most decision making,” Higdon explains. “You can program the guidelines people use.”

For example, software could pull together all of the foreign exchange exposures across a large global enterprise, aggregate and net 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 subsidiaries in several countries using many ERP systems, he adds, sophisticated reporting can mean fewer hedges and lower costs with more consistent protection.

Funding by commercial paper (CP) provides another good example, Higdon continues. A 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 Merrill Lynch. 

Traditionally, forecasts were guesses that reflected history and intuition, but now they’re quantitatively derived and more accurate, making treasury staffs more confident about taking action based on those forecasts, adds Daniel Doran, client engagement executive in BofA’s global business solutions group.

Better risk assessment is driving demand for more intelligent reporting so reporting techniques now are focused on counterparty risk. This means treasuries collect and analyze the latest data about the financial performance of their banks, hedging counterparties and trading partners, Colliton says.

Top-of-the-line treasury workstations are providing more powerful portfolio analytic tools that allow treasury staffs to look at how shocks would affect their investment portfolios, an ability that could be valuable when interest rates start to rise, reports Laurie McCulley, another Treasury Strategies partner.

As industry standards progress, more data are subject to analysis and intelligent reporting. That certainly has been true for bank account analysis reports. Software developed by Weiland Financial (now part of Open Solutions) and others makes it fairly simple and cost-effective to capture and analyze reports from multiple banks and flag instances when banks aren’t charging the negotiated fees. Such reporting is spreading, McCulley says. Kyriba, for instance,  added an account analysis module to its latest workstation release.

Bank fee analysis is about to be automated at $4.3 billion Wyndham Worldwide in Parsippany, N.J. This summer, treasury will use Kyriba’s module to receive electronic transmissions from its major banks and flag charges that don’t match what the company negotiated, reports Frank Sassano, director of treasury operations.

Replacing an 800-page printout of bank charges with an analysis of the data will save the company hours of spot-checking and provide a more thorough method for catching billing errors. “Mistakes do happen, but we haven’t been able to see how often they happen to us,” Sassano notes. Wyndham previously used another analysis application, but it was a standalone service. The integrated Kyriba application is more convenient and secure, he explains.

But industrywide conversion to new reporting standards such as electronic bank account management (eBAM) often takes time. Banks have been slow to adopt the standard, Gallanis says, and currently only large global banks are offering eBAM functionality to clients, he notes.

Corporate treasuries also have shown initiative in writing their own filters and analyses to highlight changes in inventory, collection times or payment outflows that affect working capital so they can manage it more tightly, Gallanis says. (For examples of homegrown reports, see “What’s Paying Off.”)

Improving and automating complex processes is one side of intelligent reporting. Another is boiling down complex reports into simple graphics showing the most important decision drivers. One practical application is the use of electronic dashboards to filter huge amounts of data into a few key totals or ratios that decision makers can rely on, Gallanis says. There has been a real focus on making reports more graphic and user-friendly, McCulley notes.

There is still room for progress on business analytics. Several treasury leaders known for their large, sophisticated operations said they had nothing to report. “I can’t really point to any materially better reporting analytics,” one noted. 

That’s not surprising, says Joe Siu, director of financial risk management at Chatham Financial in Kennett Square, Pa. “Intelligent reports can be complex, especially those used for risk management,” he explains. “They often require correlation analysis and Monte Carlo simulations. They are not easy to design and produce. The top banks can do it for their own financial risks, but these robust analytics are just starting to spread to corporations.”

The stumbling block, he says, is that requisite data (e.g., forecasted currency and commodity exposures) are dispersed in an organization and challenging to collect.

Nevertheless, banks are aggressively selling their versions of intelligent reports. One improved product is statistical benchmarking, reports James McKenzie, executive director at the treasury advisory solutions group at J.P. Morgan. “We leverage the data from over 30,000 corporations to provide benchmark reports to clients showing them how they stack up within their industry or peer groups—where they are, what the industry average is, what defines the top 10%.”

To measure accounts payable or accounts receivable working capital performance, the bank buys market data. For other activities, it uses its own aggregated client data without revealing the identity of one client to another, McKenzie explains.

Banks like being agents of change and recognize that making a business case is critical for getting clients to use more services, even though groups like McKenzie’s are “strictly bank-agnostic when it comes to making recommendations,” he insists. J.P. Morgan also provides reports to reduce potential fraud exposures and to identify opportunities for bank account rationalization for clients that provide information on all their accounts.

Fielding such “advisory groups” has expanded as banks jockey to become the primary provider of intelligent, actionable reporting, says Treasury Strategies’ McCulley.

The reports may be what treasury staffs value, but the heavy lifting occurs more in the database. “The challenge is to standardize and clean up the data coming into the data warehouse. Behind the analytical platforms is the enterprise data layer, which feeds all the reports,” notes Hubert J.P. Jolly, managing director for channel and enterprise services at Citigroup. “The big investment is not in designing the report formats, which are readily available from vendors, but in attaching the right transaction codes to the data so that the reporting programs can find exactly what they need.”

One reason reporting about commercial cards is so robust is that card associations like MasterCard and Visa long ago settled on standards and coded all transactions, which “tell you just what was purchased,” Jolly says. Banks have been slower to standardize, although the ISO 20022 standard is gaining acceptance.

Data in Citi’s warehouse mostly reflect transactions with Citi, so most reports are not multibank. The more business a company does with Citi, the more complete its reports will be, making intelligent reports a powerful sales tool, Jolly says.

As reporting systems morph from records to agents, treasurers are using them for more than saving time, notes Dub Newman, head of global treasury services for North America at BofA. “Treasurers want to gain more control over things like payment execution,” he says, “and some of these advanced reporting systems allow them to do that.”


For more on the topic of cutting-edge treasury technology, see Treasurers’ Tech Wish List and Cashing in on Technology.


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