Ben has twenty-five years of experience in financial services.
He specialises in data science, machine learning, credit risk, fraud, forecasting, stress testing, model governance and macro-economic modelling. He has a history of working in management consulting, advising clients on maximising commercial advantage from the effective use of data. He has deep skills in analysis and predictive modelling that he has recently applied to the fields of machine learning and artificial intelligence.
With experience from Experian as a Business Analyst and then a Consultant, Ben joined Jaywing in 2001 as Risk Consultant and went on to become Risk Practice Director. and then Managing Director in 2016.
Ben has been instrumental in the establishment of Jaywing's risk management, data science and analytics services. Ben combines practice management with hands-on analytical and systems/process design consultancy for financial services clients. Experienced in risk matters such as ICAAP, stress testing, credit analytics, modelling, scoring, model monitoring and decision systems, Ben brings a wide array of consultancy expertise to the table.
He has a strong analytical consulting professional with a degree in Mathematics from University College London.
Could automation technologies eventually replace traditional, manual collections?
As organisations continue embracing digital transformation to improve efficiency and cut costs, will traditional, manual treatments become obsolete? Or does human intelligence and interaction still play a vital role within collections?
Fighting Fraud - A Shared Problem?
Ben O’Brien reflects on the House of Lords and Digital Fraud Committee’s report ‘Fighting Fraud: Breaking the Chain’ and explores how cross-sector data sharing, artificial intelligence and machine learning could help prevent fraud and social engineering scams.
Celebrating 5 years of award-winning work at the Credit & Collections Technology Awards
At last week’s Credit & Collections Technology Awards, Jaywing won the award for ‘Customer engagement solution’ and secured a finalist spot in the ‘Machine learning in credit & collections solution’ category. This latest award represents 5 consecutive years of Jaywing winning at this prestigious event.
Climate Change Risk: Climate Biennial Exploratory Scenario
Through Climate Biennial Exploratory Scenarios, an opportunity has been afforded to financial firms to act now. Keep reading to delve deeper into this opportunity.
Roundtable recap: The future of Prudential Regulation for mid-size non-systemic banks and building societies
Joined by Simon Hills, Director of Prudential Regulation at UK Finance, our latest roundtable encouraged discussions around the PRAs future vision of Prudential Regulation for non-systemic banks, commonly referred to as the ‘strong and simple regime’.
IFRS 9 modelling: Jaywing extends use of Horizon platform to incorporate static models
Jaywing has now extended it's IFRS 9 approach to make Horizon available to users whose needs are more appropriately met by static models.
Upcoming AI regulations and how to get ahead of them
The EU has proposed new regulations around the use of Artificial Intelligence. Find out what the regulations are and how to get ahead of them.
Non-linear models: understanding and exceeding regulator requirements
AI delivers more accurate credit and risk scoring models than traditional techniques can achieve, but there is an intense regulatory focus on ensuring best practice in the development of non-linear models. In this article, we look at some of these areas of focus, and explain how our approach to controlling and explaining a neural network is generating big performance improvements for our clients.
Three immediate actions lenders should take to support society
Risk departments are on the front line supporting individuals and businesses and protecting the economy. Here's three areas they should focus on now.