The core business of IKB Deutsche Industriebank is the financing of medium-sized companies operating in the manufacturing, commercial and service sectors. A recognized specialist in the field of medium- and long-term corporate lending, IKB offers customized financing solutions, drawing on public funding programs whenever appropriate. With 1,500 employees and 40 billion euros in assets, IKB is well-poised to meet the needs of its clients.

Pricing Portfolio Loans: A New Challenge
Jörg Günther is the manager of the Structured Products division of IKB, and has responsibility for developing a quantitative analysis tool for the bank’s global business in addition to producing a whole range of modeling tools in various markets. As part of his structured financing duties, Günther was tasked with pricing IKB’s portfolio loans. Portfolio loans are loans that a lender holds onto instead of selling on the secondary market. Lenders pool and sell most loans to the secondary market in order to create money for more loans. But, to keep their in-house assets at a certain level, lenders keep some loans in-house, as part of their “portfolio.” Since portfolio loans don’t have to stick to the rules set by secondary market institutions, they have some appealing qualities, like letting borrowers borrow larger amounts. But, portfolio loans often require sizable down payments, or come with a high interest rate.

On the other hand, lenders who offer portfolio loans usually don’t require a lot of documentation to prove income or assets. The normal method for pricing loans was to analyze three arbitrary scenarios: best case, worst case, and most likely case. However, Günther understood that this method – though steeped in tradition – was inadequate to account for the wild variability in factors ranging from interest rates to borrower cash flows. He realized that pricing portfolio loans would simply not be possible with the standard scenario method. Portfolio loans, with their loosened rules and increased risk, simply had too many different factors at work. 

Monte Carlo Simulation: The Only Solution
He quickly decided to approach the problem stochastically, that is, specifically modeling the uncertainty in interest rates and other factors. This could only be done using Monte Carlo simulation. The power of Monte Carlo simulation lies in the picture of possible outcomes it creates, as it randomly generates values for uncertain variables again and again to simulate a model. 

Günther first turned to Palisade’s @RISK software because of the product’s highly recognized stature in the marketplace. Soon after using @RISK, he knew he had made the right choice. According to Günther, “Using @RISK, we have been able to price our portfolio loans very effectively, knowing we had the best knowledge available to us to make the decisions required.” @RISK distributions successfully modeled variables such as cash flows, interest rates, and equity tranche.

@RISK for All Risks
Günther further tasked @RISK with related duties. He used @RISK’s correlation features to model the interdependencies between the diverse elements within IKB’s loan portfolio. In addition, @RISK helps IKB meet Basel II standards of regulatory compliance. All in all, said Günther, “@RISK helps us judge which risks to take and which ones to avoid.” 

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