Dawid Reckert
Expert in Climate Risk Management
Dawid
"I learn by doing the thing, then by absorbing an unreasonable amount of material about it. A few hundred hours of talks, podcasts and conversations with experts, and something built badly enough to show me where it breaks. It's how my head works, and it means what I bring to a client is first-hand."
At a glance:
Joined Baringa in
2016
Works across
Financial services, risk management, climate and sustainability, and sustainable AI
What job would you be doing in another life:
Hardware engineer. Devices are physical and immediate, the opposite of a job spent in models and documents, and I like thinking about how a thing should work and feel to use. It pulls together several of my interests in a discipline I never trained in.
In detail:
Dawid advises banks, insurers and asset managers on risk management, climate, AI in sustainability and sustainable AI. The thread through all of it is mainly quantitative. He came up building the models behind capital, valuation and impairment, and has spent most of his career inside the regulation that governs them.
He is a practitioner rather than a theorist. When agentic AI started to matter to his clients, he built agentic systems himself, in his own time, to find out where they fail. He would rather have made the mistakes personally than describe someone else's. The habit predates AI. With any subject he takes seriously he works through hundreds of hours of talks, papers and podcasts until he can see the shape of the problem for himself.
In climate, Dawid led the development of Baringa's central view of the energy transition and supported institutions through the regulatory stress tests. What held his interest came after the measurement: helping firms separate the actions open to them from the ones that only work on paper. He now spends more time on transition planning than on exposure analysis.
His AI work runs along two lines. The first is governance, where he applies the discipline he learned in model risk. Can someone explain what a system did, and can they defend that answer when it matters. The second is the physical footprint of AI, where he has been working on questions such as how investors should assess data centres, which are first a question of land, power, water and the communities around them.
He is straightforward with clients about what the evidence will and will not support, including when the answer is inconvenient.
Before joining Baringa in 2016, Dawid spent six years at Deloitte in financial services risk and regulatory transformation. His curiosity runs heavily to technology and devices, a counterweight to a job spent almost entirely in models and documents.
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