- What will banks of the future look like?
- How should AI be orchestrated with banks’ existing technology stacks?
- How can fraud management be bolstered with an AI-powered banking layer?
Artificial intelligence (AI)-powered deep fake tools have exploded in development and utilisation in the last few years. Around the world, banks are losing billions every year as a result of these increasingly sophisticated threats. To address this challenge – while at the same time automating operations, unearthing notable transaction correlations, and proactively blocking suspicious activity – banks of the future are reimagining their technology stacks and placing an AI at the heart of their architectures.
Modern, AI-driven banking architectures often have on the front-end an engagement layer, incorporating capabilities for multi-modal conversational experiences with intelligent products and services. To achieve effective digital engagement, agentic AI is key – serving to streamline the interface with customers, better understand their financial needs, and deliver tailored offerings.
Supporting the middle and back-end elements is an AI-powered decision-making layer. With specialised, smart agents in narrow domains, AI promises to raze historic inefficiencies around fraud management – and deliver enhanced detection, advanced transaction monitoring, and behavioural risk scoring. Underpinning it all is the core infrastructure. This supports enterprise data, storage and processing – all of which can be orchestrated with the AI layers, to enable high levels of automation, explainability, traceability, and transparency.
By making these systemic changes today, banks can prepare for tomorrow – and bolster their security in the process.
Sign up for this Finextra webinar, hosted in association with MongoDB, to hear our panel of experts discuss how AI, at every level of banks’ technology stacks, can supercharge fraud detection.
