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making maths work
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Steve Wilcockson

Technical Product Marketing
Quantexa
Member since
28 Feb 2014
Location
Diss / London
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Followed by John Sims, Martha Boyle and 5 others you follow

Bio

I enjoy model-led and data-driven technologies in financial services.
I work with quants, data scientists, data engineers, developers and business stakeholders on their research to production workflows on the buy-side, sell-side, front office, middle office, in insurance, fraud detection, and more.

Experience

Product Marketing
Quantexa
Apr 2024 - Present
Technical Platform Product Marketing for the Quantexa Decision Intelligence Platform, commonly deployed into financial crime, customer 360, Credit Risk and a range of other primarily middle office, AI and data management platform use cases.
Product Marketing
KX Systems
May 2022 - Feb 2024
KX is the leading time-series database and analytics platform within capital markets. KX also provided vector database capabilities for use in conjunction with GenAI & LLM workflows
Product Marketing
Azul Systems
Aug 2019 - May 2022
Fast-paced provider of JVM and JDK (Java) middleware, particularly popular for glitch-free Java performance in big data systems and HFT systems, meaning users could work with greater agility than in, say, C++.
Market Development Manager
Geospatial Insight
May 2018 - Aug 2019
Satellite-derived alternative data, for use by hedge funds and capital markets, also for ESG and "Geofinance" purposes.
Industry Marketing Manager (Financial Services)
MathWorks
Oct 1996 - May 2018
For a long time, the primary matrix algebra-based programming language for modeling and analytics used in financial services, particularly front office (backtesting), middle office (risk management, of all types), and commonly used in insurance/pensions (ALM simulations), central banks (macro-economics & econometrics), and the buy-side (portfolio management and analytics). I was the Global Industry Lead for many years.
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Latest opinions

Steve Wilcockson

The Future of Contextual Risk Simulations and Scenarios

Simulations are important. It was ever thus since the dawn of computing, but they have become even more important in AI-infused complex business environments. Simulations are core to any organization’s toolkit for making optimal decisions. Combining simulations with domain models (ontologies) rooted in an organization’s platform, model and data ar...

03 April 2025 Financial Risk Management

Steve Wilcockson

Contextual RAG: Identify Risks and Opportunities without Over-Engineering

While AI models - large language models (LLMs) in particular - become more powerful and widely commoditized, the need for accurate, context-rich data grows ever more critical. In regulated industries, this becomes even more essential, as organizations must also ensure explainability and governance. For the modern organization, Contextual Retrieval...

03 March 2025 Financial Risk Management

Steve Wilcockson

The Data Structures That Drive Quant and AI

Our BizDev team at work asked me to explain why Data Management developed different cultures and languages to that of Data Science. I found this hard, in part because some of my background comes from engineering maths, which, for many years, was tightly coupled with the arguably adjacent Financial Services discipline of Quant, or Financial Enginee...

18 February 2025 Artificial Intelligence and Financial Services

See all 33 opinions by Steve

Latest comments

12 lessons in predictive modelling for enhanced credit risk assessment

That's an unusually comprehensive, technical and useful blog for Finextra!

08 Nov 2024 09:08 Read comment

Blair Institute sets out 'progressive vision' for fintech

Putting the Labour/Blair thing to one side and responding to the fraud expansion comment, I do see UK Fintech leaders in real-time fraud detection and complex fraud detection (tax, AML, fincrime, etc). I've worked for two such firms.

Complex financial crime is easier to detect than it used to be. Money launderers, organized criminals and tax dodgers have far fewer places to hide. Also, streaming real-time analytics, including model inference at scale in-memory and with distributed memory, with much-improved model deployments (types and agility to recalibrate) is powerful and increasingly democratized.

That said, I'd also note that fintech favourite, crypto, is the criminal's friend and I'd hope there's a responsible crypto strategy in the bag of tricks of the next UK Govt.

19 Apr 2024 08:17 Read comment

3 GenAI Use Cases for Capital Markets: The Power of the Vector

Very good. I'd not seen it! Quite agree. Cassandra is my old stomping ground!

13 Jul 2023 18:32 Read comment

See all 10 comments by Steve

Steve writes about

  • artificial intelligence
  • security
  • regulation & compliance
  • people
  • retail banking
  • wholesale banking
  • cloud
  • devops
  • start ups
  • identity
  • markets
  • financial crime
  • predictions

Steve's opinion archive

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  • 2022 (1)
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  • 2018 (3)
  • 2017 (1)
  • 2016 (3)
  • 2015 (1)
  • 2014 (1)
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Ivan Heard

Ivan Heard
Global Head of Fraud Solutions at Quantexa

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