Yet to embrace the cloud? The competitive gap is widening

Damien Brophy, ThoughtSpot’s Vice President, EMEA

Driven by the acceleration of modern data architectures, such as those offered by Snowflake and AWS Redshift, the world of enterprise data has been massively transformed in the last decade. So much so it could be said that the economy is now entering the defining decade of data. All the promises made by the business intelligence and analytics analysts are now coming true - with the scale and power of the cloud, modern data architectures, and AI behind it. The UK’s vibrant financial and financial technology market, dominated by digital natives born in the cloud, exemplifies the newly established expectations demanded by the modern frontline analytics user. Not the modern data scientist or data analyst, but the frontline user, interacting with data, even though they are not data specialists and hold no PhD in analytics.

It’s this ability to take determined action based on realistic insight that has propelled successful modern financial brands to disrupt the market. Witness the growth of NeoBanks Monzo, Revolut, or Starling, and Metro Bank - using new technology to take on the high street with the best of both worlds. They leverage insights and push to evolve and disrupt industry models and markets, taking advantage of innovation from across the modern data stack to outcompete their peers at home and internationally.

For institutions offering financial services, perhaps even enterprise banks who are yet to embrace the cloud, here are some pointers to unlocking greater value from existing data.

Understand the environment

Real change starts with an informed position. Legacy technology drag is a bugbear of large institutions. Smaller firms may not be quite as aware when their tech-stack has begun to be an anchor until they begin their journey. Many banks in particular maintain complex, almost Frankenstein’s monster architectures that simply must be kept running. Those environments mean technology leaders must be sure that moving to cloud services will not impact service provision.

By 2025, Gartner estimates that over 95% of new digital workloads will be deployed on cloud-native platforms, up from 30% in 2021. Back in 2016 it estimated that under 10% of data was stored in cloud platforms, and by 2025, it predicts that context-driven analytics

and AI models will replace 60% of existing models built on traditional data. The speed and scale of operations has transformed consumer and business experiences alike. Cloud platforms including Snowflake, DataBricks, Google Big Query, and Azure Synapse provide elastic compute, data sharing, and agility benefits, plus automation. The tedious data ingestion processes have moved ETL (Extract, Transform, Load) to ELT (Extract, Load, Transform). Moving huge data sets to be able to work and transform it in the cloud is no longer a months-long process.

Change stands on tech, but isn’t focussed on it

As financial organisations move to the cloud to build more flexibility and agility, they have two new requirements. They need to extract the intelligence now more accessible from within their data. And, they must push it to the decision makers that need those insights. The new cloud-native, data stack is AI-driven and its front ends have been ‘consumerised’. Arguably, the real opportunity doesn’t come from technology cost reductions or increased speed, it comes from the ability to augment all employees, from the dedicated business analyst to the frontline customer service agent. With search, backed by AI support, users can query and understand insights from data, guided by organisational guardrails to help them troubleshoot, forecast, uncover trends, and get ahead of problems - able to be agents of incremental value creation.

Without the adoption of modern data tool sets based on modern, open data platforms, the gap between the tech-savvy and tech-lagging firms may become unbridgeable. Every problem solved, every smarter and quicker interaction builds brand equity. Therefore a move to the cloud, to fully take advantage and be successful, requires a cultural willingness to open up benefits and responsibility alongside the solutions that empower the workforce.

Financial firms are already investing in AI on top of their data platforms. A survey of 200 business executives and C-suite leaders showed a belief in transformational value. Nearly 40% of financial institutions are measuring AI’s success by its ability to detect and reduce fraud. In the next five years, 34% expected to use AI to significantly reduce operational costs, 27% will leverage it to develop new products and services, 25% will utilise the technology to enter new markets, geographies, and industries.

Again, this comes back to the overall customer experience. Based on agile data, in the cloud, firms that reduce costs, better serve customers, and find new market opportunities, will dominate. This is how cloud-based data-leaders across sectors are winning. Netflix. Amazon. JustEat… They are data leaders, and all leverage the cloud to drive their insight machine.

The potential for other financial services firms to follow the brandname growth stars like Monzo, Revolut, or Starling, is there. But lessons must be learnt from how data leaders gain and keep their edge in the modern data-led world. Technology, data, culture and intelligence are the pillars of the modern, successful business. Each reinforces the other. All build on the cloud, but a financial institution must be open to a culture that prioritises a data-led approach, finding solutions based on fact, and taking measured risks based on those findings.

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https://www.gartner.com/en/newsroom/pressreleases/2021-11-10-gartner-says-cloud-will-be-thecenterpiece-of-new-digital-experiences https://www.gartner.co.uk/en/articles/12-data-and-analyticstrends-to-keep-on-your-radar https://go.thoughtspot.com/e-book-financial-services.html