Artificial intelligence (AI): it’s a phrase appearing in the news and in our everyday lives more and more these days. Although there may be some truth behind the eye-catching headlines on AI and robots taking thousands of jobs, it’s unlikely to be as dramatic as it sounds.

SwissCognitiveWhile AI will replace certain aspects of our jobs, it could allow us to take on more meaningful, rewarding roles, freeing up our time to spend on the things we enjoy, and ultimately, more time outside of work with our families and friends.

In reality, AI is part of many people’s lives already, through a range of consumer technologies. But, its implementation in some business contexts are less apparent – despite the fact that the benefits are often huge. Financial services is one example, particularly the relatively new combination of AI with automation.

Faster Decisions

In business and commercial banking, it’s already having an impact on credit assessment and underwriting – the process of checking a business’ financial stability and growth potential to determine credit worthiness. AI speeds this up significantly, supporting the decision made by the credit function on whether the company in question is eligible, and continues to qualify for their lending facilities. This can typically take some banks up to ten days to process with numerous handoffs between different people, and the potential for errors to creep into the process.

AI helps by eliminating the heavy-lifting for staff, meaning they’re no longer performing rigorous, mundane, but crucial checks and re-checks on reams of complex documents. It often involves manually taking a figure from one document, cross-referencing it with another, then entering it into a system – repeatedly.

Removing this burden allows them to devote more time on the value-added aspects of their job, like spending quality time with customers, finding new opportunities for the employer and their clients.

This is achieved through several AI techniques, such as text analytics, natural language processing and optical character recognition, building a model that recognises key expressions and calculates ratios and then training that model to recognise new expressions accurately and automatically. […]

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