Episode summary

 

This episode features Bart Pietruszka, former Chief Data Officer at HSBC and now entrepreneur. With 13 years in banking — and having led data, governance, and AI initiatives across the MENA region — Bart brings a unique perspective on how financial institutions can move from compliance-driven to commercially-driven AI adoption.

 

 

Key Learnings

 

• AI in banking is not theory — it’s practice

  Bart led the development of HSBC’s first AI fraud detection tool. It flagged suspicious activity through red-flags and is now deployed globally. Another initiative was a knowledge management system that used LLMs to answer compliance questions instantly — transforming onboarding and compliance efficiency.

• ROI is non-negotiable

  More than 70% of AI initiatives fail because they lack measurable outcomes. Bart insists that every project must have ROI attached — whether in cost savings, revenue growth, or customer lifetime value. Quick wins and measurable pilots build trust and scale.

• Why projects fail

  It’s rarely the technology — it’s the approach. Too many companies launch AI projects without clear ROI, proper prioritization, or external expertise. Bart stresses: don’t do it alone. Surround yourself with partners and experts who’ve done it before.

• Balancing regulation and innovation

  Banking is heavily regulated, but compliance should not dominate the narrative. Over-regulation — like in Europe — can stifle innovation. In contrast, the Middle East is embracing AI with Chief AI Officers and mandatory AI education in schools — creating fertile ground for experimentation.

• Generative AI and coding

  Beyond banking, Bart highlights how tools like ChatGPT, GitHub Copilot, or Replit can generate thousands of lines of code in minutes. This shifts focus from writing code to designing the impact — freeing talent to be creative rather than repetitive.

• Fintech vs. traditional banks

  Fintechs are agile, AI-driven, and disruptive — but lack the reach, infrastructure, and trust of big banks. The future lies in collaboration — with traditional banks learning from fintech speed while leveraging their scale and security.

• The rise of Chief AI Officers

  The role should not be a rebranded CDO. It requires a hybrid profile — commercial acumen plus technical expertise. For Bart, AI will soon outpace traditional data governance tasks, making this role more relevant than ever.

• Readiness matters

  Many companies rush into AI without solid data foundations. Poor data quality, legacy systems, and lack of AI literacy block results. Only 5–10% of companies have formal AI training today — a massive gap that must be closed.

• What excites him

  Hyper-personalized banking — where apps anticipate needs like Netflix recommends content. And advances in cybersecurity, including quantum-safe solutions, which will make banking both smarter and safer.

• His advice to leaders

  Don’t try to solve everything internally. Build use cases tied to ROI, fix data quality, modernize infrastructure, and bring in experts. The adoption curve is inevitable — the difference lies in how prepared you are.

 

 

The Takeaway

 

AI is not an experiment for banks anymore — it’s a commercial necessity. Those who tie initiatives to ROI, balance innovation with compliance, and invest in data foundations will thrive. As Bart puts it, “It’s just a matter of time — we’re all going to adopt it eventually.

This summary is AI generated