It isn’t an understatement to say that a day won’t go by when digital transformation isn’t talked about – whether on Twitter, LinkedIN, or in the business press. Whilst too much focus is often put on the technology aspect of a digital transformation or
being digital, a key foundation and enabler for the digital age has to be data. A recent Forbes article
stated “companies that aren’t continuously reinventing their business – with data at the core – will end up watching from the sidelines while their market is disrupted”. A key industry where this statement is true has to be financial services.
When you think about it, financial services organisations hold vast amounts of data about all of us – where we make transactions, who we make them with, how much we are paid, where we invest, what we insure etc. However, whilst this treasure trove of data
has existed within Banks for decades, they have often struggled to bring it together and extract useful insight from it. It is only recently that the true value of the data held has been realised; as an example, HSBC’s
Global CIO speaking at Google NEXT 18, explained “apart from our $2.4t of assets on our balance sheet, we have at the core of the company a massive asset in the form of our data”.
With the birth of Big Data in the enterprise in the mid 2000s, many Banks started to adopt Big Data technologies such as a Hadoop to start to bring together the data they held to try to make sense and drive insight from it. Whilst Big Data has been around
a while, as a recap the characteristics of Big Data are:
- Volume: the amount of data created is vast compared to traditional data approaches
- Variety: data comes from different sources and is now also being created by machines as well as people
- Velocity: data is being generated extremely fast; a process that never stops
- Veracity: Big Data is sourced from many different places
Most, if not all financial services organisations are utilising Big Data and associated concepts and technologies today. Whilst many are on their second, or indeed third cycle of refreshing and evolving their deployments, not many are getting the level
of success they envisaged. Indeed, Gartner speculated that 85% of Big Data projects fail. One of the hurdles to successfully leveraging Big Data, whether in financial services or wider, has always been being able to provision the supporting technologies
in a timely manner, along with being able to scale as and when required. As we move into the hybrid cloud era, being able to deploy across both on-premises and public environments in an easy and seamless manner is now also critical.
With data fuelling so many transformative approaches, whether it be Artificial Intelligence, Machine Learning or Deep Learning, or supporting deeper insight, the ability to deliver an agile platform to underpin the data workloads is key. Focusing back
on financial services, being able to leverage the vast data assets they already hold, in an agile and timely fashion, will start to help the more established players to stand out from the competition, in particular against the challenger entrants. Data certainly
gives them the opportunity to improve or reinvent nearly every aspect of their business model.