I started my career at T-Mobile as a Credit Risk Modeller, building behavioural and application scorecards. KPMG was the more defining role, where I advised financial institutions on credit portfolio and risk management, regulatory change, and enterprise lending transformation. It gave me an early appreciation for how differently banks think about risk versus how consultants and software vendors think about solving it. That gap, between what institutions genuinely need and what they get, became a thread I kept pulling.
From KPMG I moved to Lloyds Banking Group as a Portfolio Manager, then back to the vendor side with Moody's Analytics and eventually Quantexa, where I led the Global Risk Solutions team. Across all of it, whether advising a bank, working inside one, or selling into them, the question was always the same: how can I help the institution solve a real problem.
Working in my family business and at a T-Mobile store during university confirmed something early: my strength is in helping customers, solving their problems, and giving them the best service possible. Client-facing roles are where I do my best work.
When I met the GX team, what stood out was the foresight the co-founders had eleven years ago, building something that has only become mainstream with the rise of agents and generative AI. This is not a product built in the abstract. It was built with financial institutions, over a decade, on credit data and regulatory context that generic AI vendors never engage with. It is fully deployed and embedded, not in testing.
As Chief Growth Officer, my job is to connect GX's capability to the institutions that need it most. That means working closely with CROs, portfolio management, and risk leadership teams, understanding where their monitoring genuinely falls short, and making sure GX earns its place in their stack through evidence, not through a pitch.
Financial institutions are at an inflection point. Those that move early on risk-specialised AI will have a structural advantage. Those that wait will feel it in their books. I joined GX because what has been built here aligns closely with where financial services is heading, and because this is the right moment to help shape that commercially.
I am looking for financial institutions that treat AI and data as strategic growth enablers rather than compliance tools, and executive teams ready to modernise lending, underwriting, risk assessment, and portfolio monitoring meaningfully. The right partners are typically Tier 1 and Tier 2 commercial or development banks investing in AI-led transformation, where budgets are tied to measurable outcomes rather than procurement cycles. Strong sponsorship from a CRO, CDO, or Head of Portfolio Management makes a significant difference from day one.
A great partnership starts with clarity: shared objectives, defined KPIs, and an honest conversation about existing challenges and legacy constraints. What I look for is a collaborative working model, a commitment to iterative delivery, and a willingness to think beyond Phase 1.
The signals that tell me a risk team is genuinely ready are usually straightforward. They articulate specific pain points rather than asking for AI in the abstract, there is executive urgency around efficiency and decision quality, and conversations move quickly from theory to implementation.