For fraud prevention, big data is both an amazing opportunity and an absolute necessity. It’s an opportunity because, if combined with the right technology and human expertise, it allows far greater accuracy than ever before. It’s a necessity because that accuracy means more sales, less fraud, and happier customers.
Retailers who don’t start leveraging big data to the full for fraud prevention will lose out, as faster-moving competitors surge ahead. As Forrester reported in 2015, “legacy fraud management mechanisms fail in today’s economy.” That means upgrading to reflect the latest technology, data and methods – soon.
“Big data” is a loose term, notoriously hard to define, but broadly speaking it refers to the sheer, unprecedented volume, velocity and variety of the data of “the information age.”
It’s easy to see why this is relevant to online fraud prevention: a website has a huge amount of data about each transaction. So much information theoretically makes it far easier to determine accurately whether any given transaction is real or fraudulent.
Putting this tremendous amount of data to good use – so that it both stops fraud and grows sales – is a challenging task, however. It requires machine learning technology and highly trained, experienced analysts adding their human understanding of human behavior.
Machine learning is when machines predict future results based on past data. Machines are great at dealing with a lot of information, and at finding interesting patterns in the data. And they learn with every new transaction, continually adapting and improving.
But, although machines can learn, they can’t think. Human creativity and understanding of how things fit together is needed to see the people behind the transactions, and work out whether appearance matches reality. Analysts can translate their insights into something the machine can understand too, making it more and more sophisticated.
Retailers who shift to a “big data mindset” – an approach that understands the scale of data now available and the opportunity it represents – will be able to turn this into profit for their business.
With big data, machine learning and human expertise, either in-house or through an expert vendor, fraud prevention can finally be fully automated and accurate rather than risk averse. Retailers can accept more orders than before, and they can do it instantly. And without fear of fraud.
