Artificial Intelligence (AI) is one of those digital innovations that can fundamentally change society including the public sector and its public servants. AI solutions can be used to enhance security across a number of business sectors, including retail and financial. By tracing the steps of card usage and device or endpoint access, security specialists are more effectively linking points of compromise and preventing fraud in the banking sector.

Artificial Intelligence in Banking Industry

Technological innovation is the new normal in today’s world. Though Artificial Intelligence (AI) has existed for decades, yet it is being widely accepted and tried out in the Banking industry now, more than ever. In the Banking Industry, AI is already making inroads be it in Customer Service like introducing Chat-bots, or in AML, or be it Fraud Detection. AI has been and is helping Banks in being more proactive in their approach, like identifying a potential fraudulent transaction even before it happens.

The potential of Artificial Intelligence in Fraud detection in the Banking Industry AI for customer service – Banking is one industry that deals with a huge amount of data, which could be leveraged to do advanced analysis and come up with meaningful insights. There is a range of activities being carried out by banks in using AI for customer service, for personal financial services, etc. However, there is huge scope for banks to utilise AI techniques in fraud detection. For example; Banks have started using AI techniques in identifying the fraudulent transaction patterns in a card and use the data to prevent frauds.

Analysing the spending pattern – Banks could have software, which could raise a red flag if a customer has accessed his account from 7 to 8 different IP addresses in a span of a week, however the customer could be an artist/actor/tourist who could be doing shopping while he is travelling. So here, AI software would be vital in looking and analysing the spending pattern closely. The AI technique here makes the machine to think like a human.

Analyse the user profile – Another potential use of AI would be to analyse the user profile based on transactions done and then try to determine whether there is reasonable suspicion. This way the Banks can avoid a fraudulent transaction even before it occurs. Some banks have already started replacing passwords with voice recognition for some of their services, which uses AI. Now, this can only be achieved if the system is fed with the historical data of the fraudulent patterns as well as the historical data of verified transactions.

Use case of AL in fraud detection

Companies such as MasterCard and RBS WorldPay have relied on AI to detect fraudulent transaction patterns and prevent card fraud for years now. And some proponents feel AI could have helped retailers such as Target and Neiman Marcus to prevent their recent breaches.

The future is AI

The next big thing in AI is “cognitive automation”, which can be applied across compliance, fraud and money-laundering detection. For example, banks could incorporate vision and natural language processing techniques with machine learning on free format text to automate know your customer on boarding. KYC by definition is heavy on manual document checking, something that a human cognitive ability is needed to do, but banks could make huge efficiency gains if this process could be automated.