Model behaviour

In a recent article in Business Week’s Innovation section, Bruce Nussbaum investigated the impact that poorly executed, inadequately modelled and negligibly stress-tested financial instruments may have had on the ongoing global financial crash and pervading economic climate.Nussbaum captured the concept in a nutshell when he wrote: “Hundreds of hugely complex products based on hugely complex mathematic financial models were created and sold around the world-without first being tested out. There was little or no real-world iterative process… …In short, the innovation process was flawed. New inventions were not stress-tested in a real environment.”

It is obvious to draw parallels between this theory and how much effort our own industry puts into soft-launching and stress-testing online systems before unleashing them live on the wider community. Is it possible that similar attention to modelling by our investment banks and a reduced emphasis on getting to market as quickly as possible to reap the highest theoretical returns, might have avoided much of the mess we are now in?

In our experience, there are no shortcuts that can replace the benefits of thorough modelling and testing. We are experienced, working with financial service organizations and employ a range of financial modelling systems when creating products for that sector, regardless of the type and scale of banking application. We test, and retest with customers, conduct user surveys, and run real-world modelling. We listened to the top decision-makers from all sectors of global society at the annual Economic Forum in Davos back in January when they warned of just such an oversight, and we learned. Why didn’t the finance institutions and regulators do the same? Is it possible that they got ahead of themselves, bending over to product guys in order to reach a perceived sweet market as rapidly as possible, rather than following a risk-averse approach?

We work with high-profile financial clients like Barclays to ensure their online customers are provided with easy-to-use, highly secure, no risk products. Of course we are somewhat fortunate in that internet service modelling is logical and predictive – thanks to artificial server loading techniques we can run scenarios that see services oversubscribed by 100 percent and so on. But we also run pilot schemes, test groups, live tests, plus continuous testing and modelling post launch. We find real users to test products, and we ensure they are able to deposit and withdraw real funds long before products reach a wider market.

It appears that the investment banks we all rely upon simply skipped all these logical steps, going straight to market with poorly thought through products. Take the US public credit situation – if loans to citizens had been thoroughly modelled, it is probable that the disastrous toxic loan situation could have been avoided altogether. It’s important to ask the difficult questions – what if 20 percent of citizens can’t pay their loans back? What happens then?

Perhaps it is true that if organisations take the time to research, and model critical products and services carefully and thoroughly, they might miss out on early financial opportunities from time to time. But surely these steps should be considered vital, if not mandatory, to ensuring a solid, risk adverse financial landscape?