The popularity of mobile banking services is on top of in-branch banking systems. Nearly 75% of bank account holders are installing banking apps for instant money transfers, checking balance and loans dues, or requesting banking services online. Thus, mobile banking apps are facilitating a convenient and comfortable experience for the users. But, the cyber intruders on the other side are very eager to create opportunities from online banking services. Mobile banking applications are the best platform for intruders to hack bank accounts or theft sensitive banking information of the users.

Sponsored Everyone seems alive to the potential of Artificial Intelligence in business and the public sector. According to research from PwC, worldwide we can expect to see a boost to economies of $15.7tn by 2030 as more organisations unlock new opportunities in big data and advanced analytics in such fields as financial services, retail, transport and government. The sweet spot of AI is the potential scale of data processing at a volume beyond human capabilities – combined with the capacity for systems to learn and develop unprompted responses. But while PwC's numbers are impressive – and explain why so many are keen to start big-data and AI initiatives – it's important to remember we're still in a very early stage of deployment. "We have to think that AI is still a teenager," says Walter Riviera, EMEA AI Technical Engineer at Intel .

Artificial Intelligence is already changing the face of banking on a global scale. Long before chatbots popped up as interesting business-use cases, long before mobile banking applications offered military-grade secure transactions, and much before focused analytics tools for banking made themselves known, AI apps for banks augmented by machine learning and deep learning began creating an impact in the world of banking. The question is natural, and when you think of it, this hardly comes as a surprise. Artificial intelligence is already playing a role in critical finance and banking functions such as loan approvals, asset management, portfolio design, and risk management. However, the true potential of AI apps for banks extends much beyond these often talked about areas of work.

In modern IT operations teams, one of the biggest challenges is monitoring an increasingly complex environment--across many different tools--with fewer people. On top of that, teams face more pressure to avoid outages. And due to the immediacy of social media, outages can become very public, very quickly, negatively affecting customer sentiment of the company's brand. Some companies are choosing to employ data scientists to help them overcome challenges like these. The data scientist can use machine learning libraries to build a custom solution to help monitor their environment for potential problems.