AI adoption matures as banks transform customer experience
Temenos (SIX: TEMN), the cloud banking platform, today published a report with the Economist Intelligence Unit, “Banking on a game-changer: AI in financial services”. The report finds that the adoption of artificial intelligence (AI) technology is maturing as banks implement it across a range of innovative use cases. But banks are treading carefully, balancing business benefits against regulatory complexity and the need to maintain customers’ trust.
Key findings from the report include:
- 81% of banking IT executives agree that unlocking value from AI will separate winners from losers
- 78% report that incorporating AI into their organization’s products and services will help them achieve their business priorities, 46% say to a great extent
- 62% agree that the complexity and risks associated with handling personal data for AI projects often outweigh the benefits to customer experience
- Banks most heavily use AI in fraud detection (58% use AI heavily and a further 32% use it to at least some extent)
Bankers in the survey identified privacy and security concerns as the most prominent barrier to adopting and incorporating AI technologies. This was particularly pertinent for smaller organizations—those whose parent company’s assets are below US$10bn. Conversely, larger banks are more likely to struggle with regulatory compliance, complexity or uncertainty, or limitations of technology infrastructure.
As a numbers-based, data-driven industry, the banking sector has provided fertile soil for artificial intelligence (AI). As in other sectors, banks have initially found low-risk and incremental benefits in using AI to automate routine tasks. The report finds transformational opportunities for product innovation and new business models are also emerging, making AI a game-changer for banks.
Hani Hagras, chief science officer, Temenos, said: “As AI becomes mainstream, banks need to establish a set of processes that provide transparency into the logic behind the decisions made by machine learning algorithms. For example, AI is used in BNPL to assess applicants’ affordability and risk, both quickly and effectively, analyzing data to perform soft credit checks and affordability assessments. All in real-time, so the user journey is uninterrupted. Temenos has embedded Explainable AI into its BNPL service to provide additional transparency, enabling the customer to understand why a particular flavor of BNPL is recommended to them. This increases trust in the BNPL provider and encourages responsible lending practices.”
According to the report, almost all banks currently use AI to some extent or plan to in the next three years, across practically all business areas, from operations to customer experience. Top areas for future growth include personalizing investments (17% plan to adopt in next 1-3 years), credit scoring (15%), and portfolio optimisation (13%).
