The financial services industry has undergone a period of rapid digitization over the last decade, with institutions shifting to the cloud and adopting new technologies to unlock vital data insights and enhance operational efficiency.
Analysis from EY, for example, shows that more than three-quarters (83%) of financial services companies have implemented aspects of their IT infrastructure and services within the cloud, whether in a public, private, or hybrid capacity.
The main factors behind this shift have included the need to improve marketplace integration, bolster security capabilities, and to reduce IT complexity, according to EY.
Similarly, with many institutions still on their digital transformation journeys, shifting to the cloud in particular has proven to be a key enabler of innovation.
This period of change has been a prolonged process for financial services companies, however, with many experiencing significant barriers to change along the way.
Overhauling cumbersome legacy IT infrastructure has been particularly challenging, for example, and long-standing technical debt has proven troublesome for many.
Overall, the state of digitization across the financial services sector remains mixed, according to analysis from AutoRek. In a study published in early 2024, AutoRek found almost one-quarter of IT leaders in the banking sector consider the level of digitization at their firm to be “in place and fully matured”.
Around 10% noted they are yet to make any progress on this front, and two-thirds are currently undertaking digitization initiatives, which the study noted has delivered “varying progress”.
“Banking organizations often have a range of systems, with a history of consolidation and old systems carrying over,” the study noted. “The result is a network of different systems and fragmented data flows. Without significant legwork from staff, existing processes are simply incompatible with modern, digital systems.”
Many benefits on the horizon
Three key challenges to digital transformation success were identified by financial services IT leaders, including:
AutoRek noted that these three particular issues “speak to a common issue in the banking industry” - mainly that integrating new systems into a patchwork of legacy networks and applications is a monumental task.
Despite this, IT leaders in the financial services sector remain upbeat about their digital transformation prospects in the years to come - and a key factor here is the emergence of generative AI.
With the advent of generative AI, organizations across a slew of industries globally have begun ramping up adoption to unlock operational efficiencies. The technology is used across a wide variety of business functions - from software development and cybersecurity, to HR and compliance.
In the financial services sector, the situation is no different, with IT leaders in this industry optimistic about the potential gains to be had from AI. Research from McKinsey in early 2024, for example, showed the sector has been an early adopter of generative AI.
Long-term, the technology could create between $200 billion to $340 billion in value each year across the industry, the study found.
This sense of optimism has been reflected in previous studies conducted into the rise of AI in financial services, with leaders acknowledging its potential for several years now.
The AI in Financial Services Global Study, conducted by the Cambridge Centre for Alternative Finance, Judge Business School, World Economic Forum (WEF), and EY, for example, showed 85% of respondents already used some form of AI in their operations.
But leaders in the industry predicted an acceleration in adoption rates, largely due to the need for increased efficiency and the “opportunity for deeper data-driven insights,” according to EY.
“AI is expected to turn into an essential business driver across the Financial Services industry in the short run, with 77% of all respondents anticipating AI to possess high or very high overall importance to their businesses within two years,” the study noted.
“While AI is currently perceived to have reached a higher strategic relevance to FinTechs, Incumbents are aspiring to catch up within two years.”
Notably, AI is being rolled out across a broad array of business functions. Nearly two-thirds of respondents said they plan to deploy the technology to ramp up process automation, improve customer service and acquisition, and bolster risk management capabilities.
Risk management was the business domain identified as having the highest level of AI implementation rates at the time of the survey’s publication, with 56% of respondents having deployed the technology in this capacity.
The use of AI can also help unlock basic process efficiency gains, according to research from analyst firm Gartner. In a study published in June 2024, the consultancy identified the key areas that financial leaders anticipate AI having a profound impact.
The use of AI to improve budget forecasting was the most commonly-cited area in which leaders were excited about the technology, with more than a quarter (26%) identifying this as the most impactful use case.
Other areas of anticipated impact included coding assistance, cited by 11% of respondents; contract and document reviews (13%); financial/regulatory reporting draft creation (7%); and market/competitor research analysis (9%).
Challenges may still lie ahead
While finance sector leaders acknowledge the benefits of AI implementation, they still remain wary of key considerations - especially with regard to regulatory compliance and risk.
Respondents told Gartner that issues around talent, governance, data accuracy, and technical compatibility were all key concerns and had been identified as potential barriers to success.
Concerns over data accuracy in particular have slowed down deployment rates in other industries, such as manufacturing, research shows.
Analysis from Lucidworks in July 2024 showed manufacturers had actively slowed generative AI initiatives due to accuracy-related issues, with 44% of leaders voicing concerns.
The critical nature of this industry means organizations and IT leaders alike cannot afford to fall foul of data security issues and potential regulatory scrutiny.
With this in mind, leaders in the financial services industry likewise must employ a measured, responsible approach to adoption, according to Gartner.
The consultancy says leaders integrating the technology within business processes should “keep an open mind and involve key stakeholders” from across the business. This includes collaboration with finance leadership and IT teams to identify priorities and to curate a realistic expectation of what benefits can be delivered by AI.
“CFOs should audit critical data with respective owners before implementation to decide what modification must be implemented for use by a GenAI model,” Gartner said.
Notably, the survey recommended organizations identify and approach appropriate vendors where applicable to help support and guide adoption projects.
