Sep 1 • Rachel Aspinall

Revolutionising Recruitment: Lara Montefiori on the Power of Simulation-Based Assessments

Traditional hiring methods aren’t cutting it for assessing talent in markets and quant roles. Enter simulation-based assessments, the game changer. Lara Montefiori, our new VP of Product, reveals how real-world performance is revolutionising recruitment, making hiring smarter, fairer, and more accurate. Curious? Dive in.
At AmplifyME, we know that financial institutions face a major challenge when it comes to finding and developing the next generation of talent. Traditional hiring methods, like theoretical assessments, often fall short in showing how candidates perform in real-world, high-pressure scenarios.

That’s why we're on a mission to transform early careers recruitment. Led by our new VP of Product, Lara Montefiori, we're enhancing and expanding our simulation-based assessments to deliver deeper insights into candidate performance across markets and quant roles.

These assessments focus on decision-making, quantitative analysis, and behavioural skills, giving our industry partners a more accurate and inclusive way to evaluate talent, and make smarter, fairer hiring decisions.

Lara, who has been leading our upgraded assessment features as a Non-Executive Director for the past nine months, brings deep expertise in AI-driven assessments and a passion for revolutionising the way we assess early talent. With her guidance, we’re raising the bar for how financial institutions identify, assess, and develop talent, ensuring a more inclusive, data-driven, and person-centric approach.

To dive deeper into how our simulation-based assessments are shaping the future of early talent recruitment, we asked Lara to share her vision for transforming how financial institutions assess and develop their next generation of talent.

Lara Montefiori, Vice President of Product

Shaping the Future of Hiring with Real-World Simulation Assessments

Welcome to AmplifyME, Lara! Can you share a bit about your journey and what excites you about joining the team?

My journey has been beautifully unconventional. I started in Fine Arts and avant-garde fashion - fields that taught me to see patterns everywhere and question everything - and then I moved on to science, where I actually started questioning everything. If you'd told me 20 years ago that I'd be a VP of Product in finance today, I would have laughed and asked what took so long but mostly I would have thought you were joking.

When I developed a deep curiosity about how the brain works and dove into cognitive neuroscience and behavioural psychology, I discovered something that genuinely bothered me: workplace assessments were ridiculously biased. The gap between how terrible these tools were and how much they impacted people's lives didn't sit right with me at all.

So I decided to build the science to fix it. Combining neuroscience and differential psychology with game technology wasn't some grand master plan, it just made logical sense and I decided to go with it. With Arctic Shores, I pioneered what became a completely new field of psychological assessment - game-based assessment hadn’t been attempted before, and it turned out to be a massive success.

We worked with universities worldwide, and yes, got plenty of pushback from traditional assessment folks who couldn’t quite accept that there was a better way to do things. That pushback told me we were disrupting something that desperately needed disrupting so I just released more and more games and gained a great momentum in the industry and academia.

After Arctic Shores, when Multiverse approached me about matching apprentices to jobs, I thought bigger. Why not build something that maximises both individual opportunities and company performance through really smart, personalised learning?

I pulled together experts in psychometrics, learning, and organisational development, and we created the blueprint for what became an intricate diagnostic ecosystem at the core of a three-sided marketplace platform that is now supporting hundreds of clients and tens of thousands of apprentices.

Fast forward through a bit of academic teaching, consulting, advising tech incubators and running some weird and wonderful cyberdelic VR experiments, here I am working with you!

I'm genuinely excited about joining AmplifyME for three reasons. First, there's this AmplifyME-shaped gap in the market that's clearly calling out for what we're building—a platform that actually gets early careers in finance right, and I love a big challenge.

Second, I made myself a promise years ago to only work on projects that help people unlock what they couldn't access otherwise. What we're doing here - democratising finance careers while giving institutions really solid, unbiased data - matters to me at a deep level because I know we can improve this interface and change lives.

And third, honestly? Having been around AmplifyME for about one year as a fractional leader, I can say that we have by far the best company culture I've ever encountered. As somebody who has been in tech for a long time, finding a place where being kind, supportive and authentic is not just virtue-signalling or at best tolerated but actively valued and modelled as a core part of the culture is really precious!

How do you see simulations playing a crucial role in transforming how financial institutions assess talent, particularly when compared to traditional assessment methods?


Simulation-Based Assessments are genuinely game-changing for how we spot talent in finance, and here's why I think they matter so much right now.

The obvious win is that they provide high-fidelity insights into how someone will actually perform. Simulations showcase unambiguous maximal performance on how well a person actually trades. The data is objective, easy for hiring managers to understand, and clearly shows where training might help. No complicated scoring gymnastics needed.
But here's where it gets really interesting—the trace data.

I've spent most of my career building technology that captures not just what people do, but how they do it. How they inform their decisions, how they think under pressure, how fast and well they recover from failure, etc. This gives us unprecedented insight into behavioral patterns that predict long-term success way better than traditional assessments ever could.

The beautiful thing is, when you focus on how people naturally respond rather than just limiting assessment to tangible outcomes, you can identify talent regardless of all those unfair advantages such as prior exposure, coaching, fancy education or internships.

Traditional assessments get tangled up in these advantages through familiarity and practice effects. We're looking at the science of how people actually think and react in the moment, based on what we know makes a great trader, and this empowers employers to make a smart call on whether investing in developing someone is going to deliver real ROI or a short lived benefit.

At AmplifyME, we're pretty strict about making sure our trace data is explainable, actually linked to job performance, and works fairly across all candidates and regions. We're not just hoarding data, we're extracting genuine behavioral intelligence from our simulations.

Traditional methods ask people what they can do. We just watch them do it in environments where we can capture and understand every decision through validated behavioral models. It's not just better, it's where assessment is heading, and we have decided to get there first.

The timing works perfectly too. With AI heavily challenging traditional assessments, institutions need something that can't be gamed. The way our simulations work, there's really no way for candidates to get AI help, which gives our clients genuine confidence in what they're seeing.

You've worked on behavioral assessments and AI-based matching systems in the past. How do these experiences align with the work we're doing here at AmplifyME?

What I bring is experience solving the two big challenges AmplifyME is tackling: figuring out how to objectively assess people, and then intelligently matching that insight to career opportunities for them. It's the combination of deep behavioral science with practical workplace-based AI that actually works.

These challenges look similar but they're quite different beasts. Measuring people through behavioral assessment is very person-centric and science-first. Using that data for matching means getting into the messy reality of extracting features from actual roles and performance contexts, which is a much more applied type of work.

There's this complex dance between metrics we have to infer—like risk tolerance, which we model theoretically—and things we can directly observe, like PnL performance.

Good AI-based matching balances these different data types, and each requires completely different approaches to collection, validation, and technical implementation.
My experience is really about understanding what data AI-matching actually needs, how to collect it efficiently, how to score it meaningfully, and how to build it all into a diagnostic system that serves both sides of our platform, that is, democratising access for candidates while optimising performance for companies.

What we create is something that doesn't just assess or match—it builds intelligent connections between talent and opportunity in ways that simply haven't existed before in this field.

Can you explain how the new updates to our scoring models and simulation metrics will improve the way institutions assess talent?

We're taking our scoring models into genuinely innovative territory. I'm working on two parallel tracks that I believe will fundamentally improve how this field operates.
First, we're extracting much more nuanced, contextual data from the assessments themselves. Second, we're building deeper partnerships with clients to scientifically establish what early behavioral patterns actually predict success in their specific contexts later down the line.

My goal is scoring models that achieve both incredible accuracy and great fairness—the kind that enable transparent, inclusive hiring practices that actually deliver results for all involved. This means embracing serious computational innovation and committing to continuous refinement as the science evolves. The key is objectivity and thoroughness.
And here's the thing about early career assessment: we need to give candidates real insight into themselves so they can make smart career choices, while also protecting our clients' scoring from gaming and focusing on potential rather than current polish. Our updates are designed to achieve exactly that balance.

We're not just evaluating candidates, we're scientifically unlocking what they're capable of while giving institutions the predictive insight they need to make genuinely smart hiring decisions.

What role do regulations play in shaping how we develop and deploy assessments? Why is it important for us to be aligned with industry standards?

Our mission is about creating opportunities for both candidates and clients while eliminating selection bias and finding genuinely good matches. That's only possible when you follow established protocols and never compromise the science for speed or flashy features.

I actually use regulations as guardrails for innovation rather than seeing them as obstacles. I've built our approach with global standards in mind so we can operate confidently anywhere and be the kind of partner our clients can really trust.
Here's something that might surprise people: regulations actually make innovation easier, not harder. When you build with proven frameworks from the start, you're free to be creative because you know you're building something solid that will scale and stand up to scrutiny.

Regulations give you the clarity you need to measure what matters, do it accurately, not unfairly disadvantage anyone, and provide clear insights for objective decisions.

These aren't limitations; they're the foundation for building something genuinely useful.

Great UX matters, but innovation has to deliver real utility, and that's hard to achieve without following proven principles. Think of regulations as the reliable foundation that lets you build creatively on top.

Looking ahead, where do you see AmplifyME's assessment offering going? What exciting innovations or expansions are you most looking forward to?

I'm working toward making AmplifyME the go-to platform for early career finance talent - not just for assessment, but as a real ecosystem where talent and opportunity find each other naturally and grow together.

My roadmap has three main focus areas for now:

First: Getting our market, banking, and quant assessments to a level of scientific consistency and reliability that sets a new standard. More rigorous validation, comprehensive documentation, richer reporting, and continuously evolved scoring that simply outperforms anything else available.

Second: Expanding beyond simulations to create a comprehensive learning ecosystem where candidates grow, connect, and build community. People don't just get assessed - I want them to develop skills and find their tribe within our platform.

Third: Integrating clients directly into the platform and creating a true marketplace. Employers showcase opportunities, offer mentoring, connect with talent in ways that feel natural rather than transactional. While candidates learn, grow, understand themselves deeply, showcase their potential, and connect with each other while genuinely choosing their pathways and employers. What truly drives me here is that we're creating a two-way system where both sides get to be selective, not just the institutions. Candidates become empowered choosers, not just hopeful applicants. A much needed shift in the status quo.

I see AmplifyME becoming a flagship platform where finance careers begin and flourish. A community where people understand their potential, access world-class resources, achieve their goals, and connect with peers and employers who are genuinely seeking exceptional talent.

It's ambitious, and that's exactly what makes it worth building and talking about.
Get in touch to discover how our game-changing assessments can transform your hiring in 2025 and 2026.