An opportunity for financial software players?

Big data represents an opportunity for the financial software channel, notes Christian Lanng

Everywhere I look, the payment industry is being revolutionised. Think Square, PayPal and Dwolla. Soon consumers will be able to pay anywhere with a mobile, and harness biometric options such as fingerprints.

When the future of money is discussed many people imagine these scenarios. Fundamentally, though, it is still the same common denominator, the same credit card companies shaving two to three per cent off a transaction or a regular credit card sitting inside a Google Wallet or Square CardCase.

This is not the big revolution in finance that we have been waiting for. Often these shiny new products and services gloss over the status quo.

There is something far bigger on the horizon, driven by data. People such as Reid Hoffman, who is behind LinkedIn and PayPal, do not go on tours talking about the disruptive power of big data for nothing.

Money will be transformed and it will happen this year, but most people do not seem to have noticed this coming. And current financial software is broken.

When banks lend money, they expect some security. That generally means a data-backed prediction that they will get their money back because they are holding on to an asset that has value to the recipient of the credit, generally a house or business.

The recipient pays interest, calculated based on what the bank reckons is the risk that their security is insufficient and the bank's share in terms of cost of money or liquidity. The better these predictions are, the lower the risk the bank is taking and the lower the potential cost of money to the end recipient.

But banks do not have a good model for calculating individual risk for small companies. So these businesses, the backbone of innovation in a struggling economy and the breeding ground for tomorrow's FTSE, suffer rejection or very expensive rates of interest.

But financial documents can of course be processed online, in real time. It is now possible to work out the real-time risk of every single transaction a company does. If a small supplier is dealing with a large buyer, the risk is miniscule. If an invoice can be approved in real time, the money is as good as guaranteed within agreed payment terms.

Cloud providers can now create very advanced global data collections, based on, say, millions of invoices. The same algorithmic structure that drives suggestions of who to befriend on Facebook is now having an effect on the cost of money.

Christian Lanng is chief executive and co-founder of Tradeshift