Allowing AI to thrive: Why the correct culture is critical
Success happens in organisations whose culture embraces innovation, promotes an experimental, fail-fast mindset and harnesses the creative flair of its people. But it’s not easy to foster this environment. Financial targets don’t lend themselves to technology investments that might not see an immediate return; performance targets don’t tend to reward “failures”; and governance processes don’t […]
How data science is helping to combat COVID-19
Since December 2019, we have seen a barely reported virus in China become truly devastating. Over 6 million infections, 375,000 deaths, and the world is largely at a standstill. As governments try to minimise the impact, it has been made abundantly clear that modelling the spread of the disease is vital. The study of the […]
Three reasons why an AI project will fail
AI projects, particularly in large institutions, are riddled with challenges from the outset. As we’ve mentioned before, one executive at a major UK bank suggested that 90% of their AI projects fail to make it through to production. And that is in a bank with a fairly sophisticated data science capability and approach to digital […]
Don’t ask too much from your Data Scientist
Data science as a profession is still extremely new. Data and statistical modelling were used to make predictions long before data scientists existed, but this role has become more established as the world shifts towards a data-driven approach. As a result, the specification for a perfect data scientist still lacks clarity. To be considered for […]
3 ways of enabling your people to use Machine Learning
Machine Learning is undeniably enabled by the technological advances of the past decade. The theory and maths have remained fairly consistent for the last 50 years, but the explosion of cost effective compute power and the availability of data has breathed life into ML as a concept that can be practically applied to day to […]
Data challenges for AI: Woodhurst’s podcast debut
Last week I was interviewed by Kyle Winterbottom for the upcoming Data Leaders of the North podcast. The podcast series will cover a range of topics on and around data. From building a Data Eco-System to creating a Data Culture; expanding into large-scale Tech Change and productionising AI. I was there to talk about our […]
Can we unpack the black box?
Some machine learning tools are incredibly complex. So complex that they are considered to be “black box” systems. On the one hand, they are determining more and more accurate outputs to increasingly difficult problems. But on the other, the inner workings of these solutions can’t easily be understood by a human, and the rationale for […]
How data science has changed fraud detection
We live in a data driven world where many of the actions we take, as a person or a business, can be recorded and quantified. Until recently, businesses did not have the computing power or the expertise to take advantage of this, but now with advancements in modern technology, machine learning is transforming industries. This […]
Would you buy a house by looking through the letterbox?
Traditional transaction monitoring systems use a number of algorithms to assign a risk score to any given transaction. If that risk score exceeds a threshold then the transaction may be blocked and will require further investigation. For example, withdrawing £100 from an ATM is unlikely to trigger an alert for investigation. However, withdrawing £100 at […]
Implementing Innovation
Introducing innovative technologies in banks is hard. We’ve seen it first hand a number of times and there is no end to the reported failures or abandoned projects across the industry. Partly this is due to the incongruence between existing and new technologies: legacy systems don’t tend to take to innovation. But it is also […]