Enterprising Investor
Enterprising Investor

Roger Urwin: From Strategic Asset Allocation to a Total Portfolio Mindset Description

01 February 2026 50:28 CFA Institute

Listen to episode

About this episode

Roger Urwin, Global Head of Investment Content at Willis Towers Watson, reflects on how leading asset owners are rethinking strategic asset allocation amid faster regime change, rising systemic risk, and growing complexity. In a conversation hosted by Mona Naqvi, Managing Director of Research, Advocacy, and Standards at CFA Institute, he draws on decades of experience advising global funds to explain why a total portfolio mindset is gaining traction—and how it reframes goals, governance, and investment decision-making. The discussion explores what it means to invest through a truly holistic lens, why mindset and organizational design matter as much as models, and how the investment profession may need to evolve for a more uncertain world. Listen to the episode to hear Roger Urwin's perspective on the shift from strategic asset allocation to a total portfolio approach.

Chapter Markers

00:00 Introduction and Welcome 01:12 Roger Irwin's Career and Industry Background 04:02 Why Total Portfolio Approach Matters Now 04:58 Origins of Strategic Asset Allocation (SAA) 09:32 Benchmarks, Universality, and Communication Challenges 12:01 How TPA Addresses Complexity 14:47 Accessibility vs Flexibility: SAA vs TPA 16:13 Governance Trade-offs and Organizational Design 17:53 Systems Thinking and Market Disruption 19:16 Ecosystem Thinking, Reflexivity, and Risk Models 21:21 Recalibrating Investment Frameworks 22:56 Is TPA More Resilient Than SAA? 24:27 People, Incentives, and Cultural Barriers 28:49 AI, Human Intelligence, and the Future Analyst 30:46 Human + Artificial Intelligence in Investing 34:48 Managing Systemic Risk and Long-Term Horizons 40:57 Value Creation in a World of Real-Time Information 43:55 Stewardship, System-Level Investing, and Externalities 45:00 Can SAA and TPA Coexist? 47:29 Industry Momentum and What Comes Next 49:36 Closing Thoughts and Series Preview

Want to find AI jobs?

Join thousands of AI professionals finding their next opportunity

We respect your inbox. Unsubscribe at any time.

© 2026 Enterprising Investor. All rights reserved.

Common Questions

Frequently asked questions

Quick answers about how DevFound's AI matching, resumes, and referrals work.

DevFound's AI Copilot ingests your profile, goals, and live job data to deliver curated matches in seconds. Every match includes a resume variant, suggested referrals, and interview prep so you can act immediately. The more feedback you provide, the sharper the Copilot becomes.

AI-led job searches shrink the hours spent sifting through boards and formatting resumes. DevFound pairs automation with your personal outreach, so you reserve energy for interviews and negotiation. Traditional networking still matters, but AI gives you a lift before you even send a message.

Modern AI roles expect comfort with production-grade code, data fluency, and practical ML tooling. The strongest candidates pair deep technical chops with storytelling—translating model impact to product, GTM, and exec partners. Continuous learning keeps you ahead as stacks evolve.

DevFound rewards active seekers. Keep your profile fresh, respond to match quality prompts, and enable alerts so you never miss a role. The AI prioritizes companies and teams that align with your feedback, accelerating both introductions and interview invites.

High-density tech hubs continue to host the deepest AI talent pools, yet distributed teams are catching up fast. Use DevFound filters to hone in on onsite, hybrid, or fully remote roles and watch openings expand across time zones.

DevFound aggregates thousands of remote AI openings and flags the nuances—core hours, async culture, and visa needs—up front. The Copilot also recommends how to position your distributed work experience so hiring managers know you can thrive on a remote team.