Increasing the effectiveness of AI projects
It is a stark reality that 9 out of 10 AI or Machine Learning projects fail to make it to production. In some cases, this is understandable. Many AI projects are experimental in nature and therefore will not be suitable for a full production deployment. However, it’s difficult to believe that this should be the […]
Internal processes should enable not hinder AI projects
Too often financial institutions are hamstrung by internal processes which aim to control how projects are executed, but more frequently place blockers in the way of progress, particularly where new technologies are concerned. With the advent of AI and other complementary technologies – cloud computing, big data analytics – it’s vitally important that governance, procurement […]
AI solutions are nothing without quality data
Artificial Intelligence solutions are nothing without data, and banks certainly have a lot of it. The challenge is around quality rather than quantity, and an inability to identify and really harness the types of data needed to design, build and develop an effective AI solution. There are several capabilities financial institutions can build that will […]
AI is as much about people as it is about machines
The organisation can sow the seeds of a culture, but it’s the people that cultivate it and allow it to blossom. For an AI project to produce fantastic results, firms need a blend of engineering, delivery and business skills. The boundaries between data, analytics and technology need to be broken down and the organisation needs […]
Technology – The beating heart of AI
If data is the lifeblood of an AI solution, technology is the heart that keeps the blood pumping. The science behind AI and ML algorithms hasn’t changed dramatically in the last 30 years – it is the advent of cheap, scalable computing power hosted in the Cloud that is driving the conversation around AI today. […]
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 […]