AI&SOCIETY - 26/11/2019

The Opportunities AI Brings to the Banking Industry

The future of the financial services industry is closely associated with technological development -just like anything in this day and age. It demands a digitalized banking system and application of AI strategies at all levels, from the front office (conversational banking), middle office (anti-fraud) to the back office (underwriting). 

According to the OpenText report, more than 80% of banks are aware of the opportunities that AI can bring, and over 30% of financial services are currently implementing Artificial Intelligence plans in their business (most of them belonging to the front or middle office).

AI Opportunities For Global  Banking Systems

Many banks are using cognitive tech operations like Predictive Analytics or Voice Recognition. Still, broader adoption refers to numerous aspects and a high potential for the industry.

With advanced analytics, banks can finally get in the way of fraudulent transactions, biometric frauds, and haunt the money laundering activities in just a few seconds. Furthermore, it could be possible to process a high volume of data at record speed. Based on the same AI algorithm, there is a huge opportunity to improve crucial business elements like the quality of service, interaction with more clients, and customer experience.

In numbers, AI can radically boost income and reduce costs. Potential financial savings over the next three years could reach the sum of an incredible $447 billion.

AI Application in Banking

Regarding the AI application in the banking industry so far, as well as the industry flaws which require pragmatic solutions, we will outline the essential opportunities AI could provide for banks.

1. Better customer experience

According to the previous interactions with customers, banks will be able to understand their behavior better, and thus offer more personalized financial services. This way, they will be creating a stronger bond with more satisfied customers.

2. AI prediction of future outcomes

With the help of Machine Learning and intelligent analysis of past behavior, banks will be able to predict future outcomes. Such an application would help detect frauds, prevent money laundering, and save millions for the industry.

3. Cognitive process automation

Traditional banking services are expensive, overloaded with information, and prone to many errors. Cognitive automation has the task of speeding up data processing and significantly reducing costs.

4. Realistic interactive interfaces

Using chatbots that can give adequate answers in a written conversation with clients can also significantly lessen costs.

5. Effective decision-making

AI can deliver real-time solutions by using the available database, which can be widely applied in banking, especially in strategic decision making.

6. RPA

With Robotic Process Automation or RPA, cognitive technology is transforming a massive number of processes into automatic ones. Such an opportunity can free up workers of jobs that involve constant repetition and direct them to fields where human knowledge is more needed.

Conclusion

Banking leaders are already focusing their strategies on AI adoption. The future is in cognitive technology that will help optimize the use of both human and machine power. Also, growing AI in the banking sector will bring many opportunities to develop new and better financial products and services, more processed information and, therefore, a better consumer experience.

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