The deep dive: Big data and AI in financial services

By Puja Sharma

The deep dive’ is our bi-weekly exploration of a relevant topic, hot trend, or new product. For Prime subscribers only.

Finance was one of the first sectors to recognize the potential of big data and the wave of new technology that has accompanied it – including Artificial Intelligence (AI). Artificial intelligence is already being widely used in the financial sector. Businesses must deploy it with sufficient diligence, prudence, and care for it to have a positive impact.

How does it work?

Nearly all banks currently use Artificial intelligence to some extend in order to collect and analyse data, or they plan to use it in the short-to-medium term. Fraud detection is the top application of AI by banks. Other areas that witness heavy use and widespread adoption include optimising IT operations and digital marketing. The top area of future growth includes personalising investment, credit scoring, and portfolio optimisation.

In general, disruptive technologies can improve banks’ ability to achieve four key outcomes: higher profits, at-scale personalisation, omnichannel experiences that stand out, and rapid innovation cycles. The banks that fail to integrate AI into their core strategy and operations-what we call becoming “AI-first”-risk being overtaken by their competitors and abandoned by their customers.

At first glance, incumbent banks face two sets of goals that seem incompatible. The bank needs to achieve the speed, agility, and flexibility inherent in FinTech. In addition, they must maintain the scale, security standards, and regulatory requirements of a traditional financial service company.

Despite billions of dollars spent on change-the-bank technology initiatives each year, few banks have succeeded in diffusing and scaling AI technologies throughout the organization. Among the obstacles hampering banks’ efforts, the most common is the lack of a clear strategy for AI.  Two additional challenges for many banks are, first, weak core technology and data backbone and, second, an outmoded operating model and talent strategy.

Who is under the radar?

Data by IBS Intelligence shows how AI is witnessing widespread adoption in FS. Within the next few years, AI will become mainstream in Financial Services. Incumbents mainly use it to enhance existing products and services while FinTech companies use it more widely to create new ones. FinTechs are implementing Artificial Intelligence in a more product-oriented way, selling its offerings as a service.

On the other hand, incumbents tend to focus more on leveraging AI capabilities within existing product portfolios to foster process innovation. There is a trend toward mass adoption of AI, with half of all AI leaders simultaneously implementing it in several key areas such as revenue generation, process automation, risk management, customer service, and client acquisition. AI Leaders expect to be mass adopters in two years, confirming the hypothesis that applications of Artificial intelligence in financial services will result in significant economies of scale.

Why does it matter now?

In the past few decades, banks have continuously adapted the latest technological innovations to redefine how customers interact with them. With artificial intelligence, companies can boost revenues through enhanced personalisation of services for customers and employees; reduce costs through automation, better resource utilisation and reduced error rates; and discover new and previously unrealized opportunities by improving the ability to analyse and generate insights from vast data stores.