Why data is often the biggest constraint for financial companies
Financial institutions, whether oriented towards corporates or individuals, arguably have more customer data at their fingertips than any other type of organisation.
That much we know thanks to the rise of fintech, which has transformed the industry by making banking in particular far more accessible to the average consumer.
But we know unlocking insights from this goldmine is often a major obstacle. A recent survey from Yobota found that 73% of financial services firms in the UK are planning to invest in better data analytics solutions in the next 12 months, so it is crucial to have the right building blocks in place to enable this.
Every financial services organisation has had to rethink its market position and business model to deal with the impact of the Coronavirus crisis. Nonetheless, digital transformation strategies that may have been hovering in the background are suddenly top of the business agenda.
Unlocking data for digital transformation success
The access to, validity of, interpretation of and insights from data are the keys to digital transformation success and delivering a better user experience in the so-called “phygital” hybrid reality. However, the skills required to unlock the value of data are hard to come by right now, in one of the most challenging recruitment phases we’ve ever known.
In fact, according to DCMS research, almost half of businesses (46%) said they struggled to recruit for roles requiring data skills. Add to that the fact that financial services organisations are grappling with legacy technology and scalability challenges in their transition to the cloud, and you quickly see why they’re often restricted in what they can do with the data they have.
So how do we keep pace with the complexity and volume of data and empower data teams to make it easier for all areas of the business to tap into data-driven insights? Liberate it from being the reserve of small, centralised data teams, who themselves are already overloaded and hit by the continuing war for talent.
Organisations should democratise data and enable the wider workforce to glean insights directly. Data silos will no longer cut it in financial services, with businesses increasingly using analytics to inform decision-making on anything from compliance to customer experience. It is imperative that every business unit realises the value of the data that both it and the wider business generates.
What this means in practice is using tools that don’t require bespoke coding, and instead enable businesses to access their data wherever it lives, run analytics locally and reveal genuine insights, in real time. By extracting, transforming and loading data in the cloud, agile financial services businesses can convert raw data into actionable, analytics-ready data in minutes for new insights and better business decisions.
Liberate your data team
All too often, talented data teams are bogged down with slow data migration and maintenance. Recent research has revealed that two-thirds (66%) of data professionals believe their organisation is wasting too much time on data preparation.
However, manual integration is increasingly becoming a thing of the past, giving way to more automation and low-code/no-code tools that take away a lot of this pain. They’re making it easier for less technical business users to easily analyse data sets and freeing up valuable time for skilled data engineers to invest in more technically challenging and value-adding tasks.
Rid your organisation of data blind spots
A recent survey found that nearly 40% of data teams don’t fully understand how data is being used in their organisations. On top of that, a further 44% are concerned about the challenge presented by the diversity in the types of data they work with. All of which suggests certain data types are being left behind in many organisations, leaving new, growing information gaps in their data strategies.
Cloud data and IoT data were noted as the most commonly unavailable or unsuitable sources for business intelligence and analytics. Cloud-native solutions like data lakes or lakehouses take on great importance here, by providing a centralised repository for businesses to collect and store data of any scale and format. When managed correctly, such data stores promise to help create a consolidated, single source of data truth, making it easier to govern, manage and transform into an analytics-ready state.
Future-proofing your data strategy
In a landscape permanently adjusted by Covid, financial organisations have a vast amount of data at their disposal, presenting an unprecedented opportunity. Capitalising on this can put them in the strongest position possible, unlocking more informed, real-time decision making across all areas of the business.
Having a holistic, cross-departmental data strategy is the first step, as too often data is siloed, mismanaged or incomplete. Putting the right tools and considered processes in place is a key part of achieving that and will go a long way towards democratising data for the benefit of all employees. Now is the moment to complete a major piece of the digital transformation puzzle and accelerate the modern data journey of financial services organisations all over the world. Don’t let yours be left behind.