Smarter banking experiences: GenAI and semantic search in action
See how Elastic and generative AI are changing banking, from personalized services to context-aware search and smarter customer support.

At the Elastic Financial Services Summit, Tim Brophy, principal solutions architect at Elastic, explained the promise of generative AI in banking. The session tackled four key challenges:
Making transaction searches actually work for customers
Improving chatbot interactions with real-time knowledge
Delivering personalized customer recommendations
Improving operational efficiency.
"Generative AI is not just about efficiency, it's about innovation and deeper customer engagement," explained Brophy. "For financial services, it enables smarter decision-making, more personalized customer interactions, and the ability to uncover insights from vast amounts of data that were previously inaccessible or underutilized."
The GenAI opportunity — and why most banks aren’t ready
According to Deloitte's 2025 banking outlook, AI could drive global banking industry profits to US$2 trillion by 2028, with institutions like J.P. Morgan already reporting 10%–20% increases in product application completion rates through AI-powered customer engagement tools. At the same time, according to the report, only 25% of banking institutions say their data management platforms are adequately prepared for generative AI adoption.
Their outlook confirms that in transaction search, GenAI semantic search capabilities are improving how customers interact with their financial data, with natural language queries and context-aware categorization that traditional banking systems couldn't achieve. For customer engagement, the report notes that banks are deploying AI-powered chatbots that generate answers from real-time knowledge bases instead of static FAQs, while combining transactional and contextual data to deliver personalized recommendations and messaging.
Smarter search, support, and personalization in practice
Brophy demonstrates this transformation through examples of an Elastic-enabled bank. First, he shows how semantic search could understand what customers actually mean when searching transactions — moving beyond exact matches to comprehend context and intent. "Traditional banking systems rely on exact matches," he explains, demonstrating how AI-enhanced search could now understand and categorize transactions intelligently. For customer support, Brophy showcases a chatbot that could pull information from across the bank's knowledge base to answer questions about mortgages, rather than just matching keywords or directing customers through FAQ pages. He demonstrates real-time synthesis of information that makes responses more relevant and natural.
Perhaps most striking is the personalization capability. Using the example of a UK-based wine enthusiast who drives a Porsche, Brophy shows how the system combines transaction history, customer preferences, and available products to make recommendations — from vehicle finance offers to South African wine collection packages.

Customer spotlight: EY
EY built a GenAI solution on Elastic to help financial professionals get answers to natural language questions like, “What’s our forecasted revenue by product line?” or “What changed last quarter?” Using Elastic’s vector search and hybrid ranking, EY delivered 3x faster results than native RAG setups and achieved a 10%–15% improvement in accuracy for data extraction. Elastic ensures responses are both fast and permission-aware — protecting sensitive business insights while delivering context-rich results. Read the full story.
Where GenAI is going next in financial services
Looking ahead, Brophy sees AI in banking becoming more specialized: "What's going to happen is that, per use case, we're going to see specialization emerge." He highlights particular potential in compliance management for failed payments and fraud investigation, where AI can help analysts quickly identify and summarize anomalies.
Watch the full session: From keyword search to context understanding
Watch the webinar to learn how combining semantic search with generative AI helps banks move beyond basic keyword matching to truly understanding the context and meaning of customer needs — whether they're searching transactions, seeking mortgage advice, or looking for personalized services.
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