Organisations will benefit from standing back from the BAU and determining how their analytics and technologies, which identify and support the management of distressed customers, need to change to ensure they secure that competitive advantage.

Companies are being held accountable for the outcomes of their AI-based decisions, creating a need for explainable AI.

Machine learning in fraud detection performs better when we know the strengths and limitations of different analytic toolkits, and understand the factors that determine accuracy.

The National Board for Customer Disputes in Sweden have ruled that banks should be liable for so-called “push payment” fraud losses over a certain amount.

Are we making the progress we want to see — and regulators demand — on non-performing loans (NPL)?

Following a slide that lasted four+ years, the FICO® Credit Health Index for Russia began climbing in April 2016 and climbed another 2 points last quarter.

Until now, it has been very difficult for a lender to understand the pressures on any consumer in terms of their ability to absorb more credit and pay off the required instalments, without placing unbearable stress on their finances.

Hypnofraud refers to the success fraudsters are having with convincing people to give them their account data - but the fraud based on this can be detected and stopped.

You can't control the sun, the wind or the snow. But using predictive and prescriptive analytics, along with optimization algorithms, you can do the next best thing.

Analytics - including machine learning and optimization - is taking off in the auto manufacturing industry, and has the potential to go much further.

Statnett, the Norwegian transmission systems operator (TSO) for energy, is going to use FICO energy optimization technology to power their models of the future of electricity needs in Norway and optimize the current infrastructure.