Although, ethical debates entailing AI are still pretty much alive, the factual benefits of applying automation to banking processes outweigh the apprehensions. As per a recent report by Accenture, in which banks who have incorporated AI to their workflow were analysed; the results showed that an average bank can proliferate their earnings by 20-25% solely by adding AI to their work processes. These statistics do not even take in to account the revenue generated for new product lines and customer retention.

Finance is undoubtedly the industry that experiences one of the gravest needs of automation. Unlike marketing, or any other field, the work processes in Finance demands significant diligence and meticulousness from worker’s end, as regulations grow more elaborate, and it’s challenging to keep track of all new requirements. That is why the need for custom-tailored interactions are growing, and apparently it is becoming difficult for bank employees to keep on top of these changes, as they lack the time and energy to satisfy these expectations.

Fortunately, there is a solution.

AI can be applied to all fields of financial activities, thanks to its diverse practicality. Mentioned below are some areas of AI implementation.

Making User Journeys Smart

Implementing robots for process automation, has become a common practise in big organisation nowadays. However, while this may increase the speed of the service, the efforts still remain obscured behind the veil, away from customer’s point of view. Instead, automation should be in areas which are visible to the end client.

How that can be done?

Banks and insurance companies can simplify the process of getting a mortgage. Affordability checks and short consults can be entirely performed by AI. While the human expert will still oversee the process, the simplest procedures can be quickly done by bots.

Preventing Cyber Security Attacks

AI and machine-learning algorithms are perfectly equipped to analyse systems and detect suspicious patterns. By training AI to analyse the transactions and website access history, bank management can identify shady behaviour.

The main uses of AI in financial security are the following:

  • Detecting fraudulent actions that resemble bot activity or hacking threats.
  • Handling suspicious financial operations.
  • Identifying security vulnerabilities in online systems.
  • Exploring potential safety risks.

As the company scales, so grows the volume of data that needs to be analysed. Massive amounts of work can’t be performed manually. AI, on the other hand, will handle a broad analysis with no problems.

Artificial Intelligence is a perfect addition to any innovation that you are implementing, be it block chain, Internet of Things, or big data. When machine learning algorithms power these technologies, they work faster and more precise. So, if your company has been already on the track of implementing disruptive technologies, artificial technology is the next logical choice.

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