Steve Wilcockson

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Quantexa

Member since

28 Feb 2014

Location

Diss / London

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

Summary

I've worked most recently for decision intelligence (fraud detection, risk decisioning) firm Quantexa since April 2024. Prior to Quantexa, I worked for KX, the popular kdb time-series database and language q which is used for real-time, high-frequency and quant-led trading and risk management, especially in tier 1 front offices. Before that, I worked at Azul, a Java runtime specialist facilitating Java's use inn financial low-latency and big data applications like trading, back-testing, pricing, payments, fraud detection and risk management. Before that, I was at altdata and sustainable finance satellite imagery firm Geospatial Insight, and until June 2018 I was Industry Manager for Financial Services at MathWorks, aka MATLAB.

Latest opinions

How a Data Fabric Delivers Better Financial Services Outcomes

Data Fabric: The Origination Story Throughout my career, enterprise data management paradigms have come and gone. Let’s briefly trawl some data management history to understand how data fabric emerged. Popular data management paradigms include: Data Warehouse Data Lake ETL, i.e. Extract, Transform, Load ELT, i.e. Extract, Load, Transform Data Lake...

05 August 2024 Data Management and Governance

Your LLM Will Wish You Had Used a Knowledge Graph

The problem: Generative AI Large Language Models (LLMs) can only answer questions or complete tasks based on what they been trained on - unless they’re given access to external knowledge, like your organization’s knowledge. LLMs can be fine-tuned, but it's an expensive endeavor. As a result, deploying enterprise context in conjunction with LLMs has...

18 June 2024 Artificial Intelligence and Financial Services

Niklaus Wirth, and How Financial Computing Can Help Save The Planet

More than a few computing luminaries have sadly passed over recently, unsurprising given many pioneers from the fifties, sixties, and seventies reaching end of life. One who caught my eye was Niklaus Wirth who departed this world on New Year's Day. He was a Swiss computer scientist, associated most with ETH Zurich, but he also had sixties Silicon V...

11 January 2024 Capital Markets Technology

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Latest comments

12 lessons in predictive modeling 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

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