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AI in Banking: Who’s active in the GCC and what are its use cases?

It’s still early in the game for financial institutions (FIs) in the region and the globe, but AI is getting some attention and for good reasons

Unlocking value from AI will be the differentiator between winning and losing banks IDC forecasts that $96 bn will be spent on AI by 2023 AI utilized appropriately can help to drive more efficiency when dealing with customer queries

It’s still early in the game for financial institutions (FIs) in the region and the globe, but AI is getting some attention and for good reasons.

AI Adoption- Banking 

Financial institutions aiming to deploy AI need to be conscious of the risks that come with the technology, including unintended biases and difficulties managing the vast amount of data that AI models require.

However, AI in banking is maturing and helping banks with their anti-money laundering (AML), know-your-business (KYB), and know-your-customer (KYC) obligations, reported Business Insider Intelligence.

A solid majority of global financial services firms have either implemented or working to implement AI solutions in business domains like risk management (77%), generation of new revenue potential through new products or processes (80%), customer service (74%), process re-engineering and automation (73%), and client acquisition (69%), according to the Cambridge Centre for Alternative Finance and the World Economic Forum.

More than three-quarters (77%) of global bankers believe that unlocking value from AI will be the differentiator between winning and losing banks, as per a survey conducted by The Economist Intelligence Unit. 

The technology is manifesting itself in front-office banking in the form of biometrics, virtual assistants, personalized insights, and targeted product offerings.

And in the back office, AI is automating tedious tasks and helping employees be more effective at their jobs.

Saudi Arabia had the potential to double the size of its economy to $1.6 trillion and add an extra $293 billion by 2030 if it fully adopted intelligently automated systems in all sectors, a report by Automation Anywhere has revealed.

IDC forecasts that $96 bn will be spent on AI by 2023, with retail, banking, and manufacturing taking the lead, representing almost 39% of the total spend.  

Banking AI, UAE

After receiving approval by the UAE’s Central Bank, Al Marya Community Bank stated that clients may open new accounts and take advantage of “smart banking” services developed using AI-enhanced technology that’s integrated with the UAE government’s smart services.

The new services will mainly focus on financial management, aiding savings and investments for local Emiratis and expats.

Standard Chartered has implemented ‘Client Insights’, a cloud-based artificial intelligence tool housed in Amazon Web Services, designed to sift through vast pools of customer data to give front-line banking service providers detailed and actionable information. 

The goal was to move beyond traditional banking services to a more tailored, personalized set of offerings – now being delivered to Standard Chartered clients across Singapore, UAE, UK, and France. 

Banking AI, Qatar

Qatar Islamic Bank (QIB) is the first bank in Qatar to launch a conversational virtual assistant armed with proprietary artificial intelligence (AI) and machine learning algorithms.

‘Zaki’, meaning smart, is an additional communication channel for QIB website visitors to interact with the bank.  

Zaki is designed to provide relevant and contextual responses to QIB existing and new customers’ queries in a more convenient and instant manner. 

Zaki will allow customers to interact with the bank 24/7 and receive information or advice on their inquiries directly through AI and machine learning algorithms without the need to visit a branch or call the QIB call center.
 Zaki is available in Arabic and English and will continue evolving in the future to interact with more requests and answer further inquiries from visitors.

Zaki will eventually help make transactions on the chat window itself. Customers will later be able to initiate transactions either through voice or chat.

 Use cases for AI in banking 

1- KYC/KYB/AML and customer onboarding

AI can help streamline KYB, KYC, and customer onboarding by allowing for verification techniques like facial recognition, or automation of document uploading. 

AI can also play a vital role in AML by helping banks move from rule-based analysis to more risk-based assessments in determining false positives on suspicious transactions. 

2- Servicing queries

AI utilized appropriately can help to drive more efficiency when dealing with customer queries, by using a combination of chat-bots, dynamic FAQs, and Robo-advisory.

3- Collections

AI data can be used to determine the best channel, time of day, and communication style that will yield the best opportunity to collect overdue payments.

4- Fraud

AI can help to prevent, as well as identify Fraud, through analyzing customer behavior in real-time to determine what activity looks out of kilter with normal actions. 

5- Underwriting

If we think about document management, information processing, and generating decisions as largely rule-based, then machine learning can make a significant difference to the time it takes to structure the data and then support decision making.