Introducing Agentic AI for banking

With the new Intelligence Fabric , Backbase will enable banks to implement Agentic AI capabilities that unlock massive productivity gains across all their critical service and sales operations . Using advanced reasoning and grounded in cross‐bank data through the Backbase platform , banks can now create AI Agents that augment and orchestrate customer journeys in tandem with underlying workflows , integrations , and real-time data interpretation .

Gartner predicts that by 2028 , one third of interactions with GenAI services will invoke action models and autonomous agents for task completion . With unified , real-time access to bank-wide data , knowledge , tools , and workflows on the Engagement Banking Platform , Backbase AI Agents can understand and interpret contextual information to provide personalised responses . They can also execute action plans , from handling small tasks like transaction search or bill payment scheduling to managing entire processes such as customer onboarding . Ultimately , these AI Agents have the potential to reinvent customer journeys

and workflows across the bank . Built-in guardrails will provide robust oversight , allowing banks to implement strict levels of compliance and governance .

Jouk Pleiter , Founder and CEO at Backbase , said : “ We see a future where AI Agents will work autonomously in the background , handling tasks , managing processes and collaborating with customers and employees . The adoption and evolution of these new-gen , super-powerful agents will dramatically reduce internal and external labour spend on overheads such as sales , marketing , customer service and compliance operations .”

AI-driven customer engagement orchestration

Backbase is prioritising the availability of AI-Agent capabilities for the following use cases :

1 . Conversational banking : Leverage large language models ( LLMs ) to handle daily banking tasks like accessing accounts , making payments , checking transaction histories , and managing cards across digital channels .

2 . Customer lifetime orchestration : Create AI-driven product activation and up-sell campaigns that enable the bank to increase the product holding per customer . AI-driven predictive nudges will provide contextual guidance to customers , promoting relevant new products such as credit cards , loans , savings , investing , and insurance , all based on customer behaviour and financial history .

3 . Advanced financial insights : Harness AI and machine learning

Jouk Pleiter , Founder and CEO at Backbase

models to analyse customer data and behaviour , providing actionable insights such as early warning indicators for retail customers , cash-flow forecasting for SMBs , and customer health and viability information for relationship managers .

4 . AI-augmented customer support : Deploys cutting-edge Generative AI models to power customer-facing chatbots that provide safe , accurate , and instant responses , drastically reducing support ticket volume . On the agent side , deploy AI capabilities that analyse customer sentiment , summarise issues , and suggest reply options , equipping support teams with the insights they need to craft personalised , effective responses and enhance the overall service experience . �

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