At EOS partner company Svea Finans, a debt collection service provider in Norway, customer service personnel are working with an AI system that helps them make the right decisions when talking to defaulting payers.
Data is the fuel that drives many sectors. But how do companies determine the value of their data? EOS has developed a strategy for working this out.
Digitalization insufficient: Over half of European companies rate themselves poorly. This is shown by the EOS survey “European Payment Practices” 2019. Where are the weaknesses?
Developing one’s own AI solutions requires more than just a good idea and the necessary funds. Rather, three important attributes are needed.
If you take a closer look, you will see that in most cases, artificial intelligence is still in its infancy. But what actually differentiates weak AI from strong AI?
EOS Group national subsidiaries use the knowledge platform to become collectively smarter. The analytics platform will become the AI ‘super brain’ of the EOS Group.
In matters of data security there’s still work to do. An EOS survey shows that top decision-makers in European firms see cyber security as a trending issue.
How and where do I best address my customers? New AI systems are determining this using insights from behavioral economics. What are the consequences for business?
In online retail, even just a handful of data is enough to yield a valid credit score. A research paper by the Frankfurt School of Finance & Management shows how informative our digital footprint can be.
AI systems invest money, make diagnoses, steer cars and identify wanted persons. But who is liable if AI makes a mistake when carrying out such sensitive tasks?
A new breed of fintech firm is promising to make requirements like know-your-customer a breeze.
It’s not just about technology, it’s about people developing a data-driven mindset, the Center of Analytics team explains
If you work in a rapidly changing market your business software needs to keep up with the pace – as do the people using it.