Fintech CMO reveals how AI-driven GTMOS delivers 10x efficiency with 25% less budget

Jul 31, 2026 · Topline
🎧 PodShort 82 min squeezed to 2 ARMARM Sales Tech New
Episode artwork
Tim Rutten
CMO at Backbase
Sam Jacobs
Host, CEO at Pavilion
Asad Zaman
Co-host, CEO at Sales Talent Agency
AJ Bruno
Co-host, CEO at QuotaPath
Topline
82 min squeezed to 2
Full episode from Topline
Quotable Moments

Workloads are truly either automated, some of them are agentic. You don't even touch the keyboard anymore. So with 25% less budgets, I'm actually still doubling the pipeline.

Tim RuttenCMO at Backbase
00:12

You don't need Fable. It's way too expensive. You don't need that level of intelligence. You could actually probably do better with a small language model which is specifically trained for financial conversations or financial type of transactions.

Tim RuttenCMO at Backbase
02:09:53

The actual operation runs on GTMOS. So the way I would like to work and the framework we have to run the business is running on GTMOS. So there's no other way to work.

Tim RuttenCMO at Backbase
05:31:11
Key Insights
  • Backbase, a €2.5 billion Fintech powering over 120 banks worldwide, is achieving massive, measurable ROI from AI tooling that automates workflows, some of which are 'agentic' (no keyboard interaction).
  • With 25% less budget, Backbase's marketing team is still doubling the pipeline by leveraging AI for automation.
  • The banking industry became open to AI adoption when 'agentic' AI entered the scene (1-1.5 years ago), recognizing opportunities for automating specific workloads.
  • For many AI implementations in banking, large and expensive models like 'Fable' are unnecessary; smaller, specifically trained language models often yield better results at a lower cost.
  • Current AI applications in customer care call centers are demonstrating 90% efficiency gains, indicating a significant potential for cost reduction.
  • The true implementation of AI in banking is predominantly internal (operations, COO functions) due to the low tolerance for errors in highly regulated environments.
  • European financial services are perceived as being more innovative than their American counterparts, with Europe being at least 10 years ahead in digital maturity, as evidenced by earlier adoption of technologies like tap-to-pay and less reliance on traditional methods like checks.
  • AI will eventually become a commodity, akin to electricity, meaning its ubiquity will negate its role as a primary differentiator.
Metrics Mentioned
  • €2.5 billion (Valuation of Backbase)
  • 120 banks (Number of banks Backbase powers worldwide)
  • 25% less budget (Tim Rutten's marketing team operates with this much less budget)
  • 90% efficiency gain (Achieved in customer care call centers using AI)
  • $50 million (Lloyds Banking Group ROI from AI last year)
  • $100-200 million (Lloyds Banking Group projected ROI from AI this year)
  • 3-5% error rate (Typical error rate for reasonable compute in AI)
  • 10x (Teams (AEs, BDM, product marketers) are more efficient with their new GTM OS)

RevBots.ai View:

  • ARM stage orgs like Backbase show AI's real ROI comes from orchestrated systems, not point solutions.
  • SaaS Hoarders waste budget on oversized LLMs when specialized models outperform for specific use cases.
  • AI Sprinkler teams should study Backbase's GTMOS as blueprint for workflow automation at scale.
  • Tab Hoppers in banking can leapfrog stages by adopting Europe's regulated-first AI approach.
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