Pictures of the Future Spring 2008
Digital Assistants – Financial Sector
Tracking Transactions
Siemens Financial Services utilizes IT solutions it developed itself for in-house banking processes and the assessment of credit and stock market risks. These systems keep finance specialists up to date on all financial movements
Huge financial flows, such as those that move daily on the Frankfurt Stock Exchange, cannot be managed without computers. Siemens employs a central IT solution for its global financial activities
Every once in a while you’ll hear someone say that Siemens is really a bank with a small electrical and electronics division. Although this little joke has always been far off the mark, there is an element of truth to it. After all, managing annual sales of more than €70 billion in 190 countries and millions of accounting transactions for customers requires a sophisticated financial system.
One system used by Siemens is "finavigate," an Internet-based, in-house banking solution that centrally manages all financial movements and internal and external payments. The result is company-wide, up-to-date transparency regarding sales development, currency positions, cash flow, and all payables and receivables. finavigate was developed by Siemens Financial Services (SFS) and is used by Siemens and six other corporations. "Siemens alone processes nearly ten million external payments each year," says Willibald Schmeiser, head of Treasury Solutions & Consulting at SFS.
All Siemens companies are linked to finavigate, as are banks that the company does business with. The system thus serves as an in-house hub and an interface between internal and external financial worlds. "More than 7,000 users worldwide access the system around 100,000 times a day," says Schmeiser. "In addition, the system is capable of generating a monthly balance statement within 30 minutes." Ultimately, finavigate ensures Siemens’ ability to make payments at any time, as its exact knowledge of scheduled payables and receivables enables it to determine liquidity in real time. "That also allows us to invest available capital at the best possible conditions and organize needed capital at an early stage and at favorable conditions," says Schmeiser.
In-House Bank. SFS acts somewhat like an in-house bank for Siemens, providing all the usual financing instruments, including venture capital and insurance solutions. The company’s approximately 1,800 employees generated revenues of €329 million last fiscal year while managing a balance sheet total of nearly €9 billion. SFS also provides risk management services, among other things by taking on all accounts payable to Siemens from customers who have bought the company’s products—whether computer tomographs, video-monitoring systems, or letter-sorting machines. This removes most of the default risk from the operating business and transfers it to SFS.
"We calculate the default risk for this huge portfolio of credit in order to determine the optimal level of capital needed to cover it," says Bernd Walter, head of Risk Methods at SFS. Because the level of default can fluctuate, Siemens needs to insure itself against non-payments and maintain a certain level of capital to ensure that the company itself remains solvent. With this in mind, Walter and his seven-member team have developed software that assesses every instance of credit in terms of risk costs. Outstanding payments of several hundred million euros can, for example, be practically default-proof if the debtor has an excellent credit rating, as do most government authorities. On the other hand, small payments totaling just a few million euros can harbor high risk costs if the customer is a start-up that may not make a profit for some time.
Digital Risk Assessment. "Human beings are simply not capable of carrying out evaluations of around 150,000 debtors, some of whom owe money to, and do business with, third parties," says Walter. SFS’s computer model, on the other hand, can identify the biggest risks. "The model saved us from losing around €20 million when automotive supplier Delphi nearly went bankrupt," Walter reports. Even before Delphi was downgraded to the lowest possible credit rating by agencies in April 2005, the model had already identified the company as high risk, after which all of Siemens’ receivables from Delphi were insured. As a result, there was no default, despite the fact that Delphi sought protection against creditors.
"The model is fed with variables such as the creditworthiness of individual debtors, which we determine from customer data that includes key financial figures, company age, number of employees, the company’s economic sector, and company payment history," Walter reports. He and his team have also used a similar model to significantly reduce Siemens’ insurance premiums. SFS arranges protection for all insurance risks, including everything from property damage and transport damage to major project insurance.
"Our computer-supported tools also provide answers as to which risks we should outsource and which ones we should assume responsibility for ourselves," says Walter. "Most importantly, however, they tell us whether the premium being offered is justified." The premium must be as low as possible, of course, in order to keep pressure off profit margins. "For our premium assessment, we fed a lot of data on past insurance claims into a model, which then used a simulation to generate hundreds of thousands of possible future damage scenarios," Walter explains.
"These scenarios enabled us to identify the maximum damage to be expected and also determine the probability of specific damage costs and the average overall damage that might occur." Ultimately, Walter’s project succeeded in more fairly distributing the insurance premiums paid to SFS throughout Siemens and, more importantly, significantly reduced the transfer premium paid to the actual insurance company.
Click for Decision-Making Assistance. Securities analysts at SFS manage nearly €20 billion in capital, including the Siemens pension funds. In this connection, digital assistants help specialists maintain an overview of developments on stock, bond, and currency markets. "Our decisions are based on forecast models that we developed ourselves," says Dr. Christoph Ulschmid, who is responsible for Bonds and Currencies. The parameters they examine include changes in interest rates, which can have an enormous impact on future economic developments. "What’s important here are short-term forecasts that predict developments over the next month," says Ulschmid. To obtain these forecasts, Ulschmid uses models that calculate technical indicators and analyze interest rate curves. Also of great importance are fundamental predictions regarding inflation and economic growth.
Ulschmid’s colleague Rainer Hackl, who heads Stocks at SFS Treasury and Investment Management, utilizes models that in some cases employ analysis instruments like those of the U.S. Federal Reserve. "We have special tools," says Hackl. "These instruments provide decision-making assistance in determining which regions, countries and companies will offer above-average returns." Analyses are followed by the creation of a portfolio, and possibly its rearrangement, should control mechanisms indicate the necessity of such a measure. SFS experts generally keeps stocks for two years and hold onto bonds for around four years. "A manager ultimately decides whether a stock is to be purchased or sold, of course," says Hackl, who nevertheless finds it amazing "that a computer helps us select undervalued stocks, even though it knows absolutely nothing about shares."
Norbert Aschenbrenner
How to Quantify Critical Risks
Siemens Corporate Technology (CT) has developed a method known as sira that helps manage risks in major projects. "We get everyone together who is involved in a project at a meeting in which we identify existing technical and contractual risks," says Oliver Mäckel, head of Technical Risk Management at CT. The best technique for depicting such risks has proved to be the use of balls whose color, size, and position indicate both the probability of a given risk and the financial consequences of its occurrence. "We then combine the analysis results with the subjective perceptions of planners," Mäckel explains, "after which it’s immediately clear which risks the project team is adequately aware of and which ones it may have underestimated. These days, we evaluate our graphs the way experienced doctors examining x-ray images." Mäckel and his team have carried out about 70 such risk analyses to date. Their work here was particularly helpful in a subway project in Oslo, Norway, where a new brake developed by Siemens’ Mobility Division was used for the first time. Correspondingly, the risk potential was high. For example, a need for additional testing could have resulted in delayed delivery of the component. However, everything went well—in part thanks to the support of CT experts, who helped the project team optimally balance potential changes relating to the brake’s mechanical, hardware, and software systems. The reputation enjoyed by CT’s risk analysts at the Fossil Power Generation division is now so outstanding that they’re routinely called in to examine technically complex, large-scale projects.