Capital Bank

Capital Bank OF Jordan

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Capital Bank Partners with JBS and IBM to Build a Data Platform for Machine Learning and Artificial Intelligence

As part of the agreement, Capital Bank will apply a unified data management and artificial intelligence platform, the IBM Cloud Pak for Data, which is an artificial intelligence-enabled system for the cloud environment that standardizes and simplifies the processes of collecting, organizing and analyzing data. This platform will allow the bank to support the fact-based decision-making process by harnessing automation to discover, classify and enhance data, and ultimately provide ready data to business circles in record time. This, in turn, will lead to heightened employee productivity, enhanced work efficiency and an elevated customer experience while simultaneously increasing the bank’s operational efficiency.  

Machine learning (ML) and artificial intelligence (AI) solutions and models will aid Capital Bank in understanding customer behavior by helping predict their future actions, manage their relationship with the bank throughout its various stages and help the bank reduce and manage risks by improving the quality of credit subscriptions and the credit approval process, detect and prevent financial fraud and improve know-your-customer (KYC) procedures. This will involve analyzing customer behavior and discovering cases that allow the bank to manage anti-money laundering and anti-terrorist financing efforts more efficiently.

Artificial intelligence and machine learning solutions will also be used to enhance the operations of the customer service center by converting incoming customer calls into text and extracting patterns from them, including the most common reasons for calling, frequent complaints and the quality of the calls in order to analyze them, identify their causes and handle them as a way of augmenting the quality of services provided to customers. Capital Bank will also be able to study and analyze methods of stimulating spending on credit cards in order to develop and provide suitable services and solutions to customers.

Speaking about the partnership, Capital Bank Chief Operating Officer Izzidin Abu Salameh said, “Capital Bank is a pioneer in digital transformation, and data management and processing is a main pillar in the digital transformation journey. This step will add the dimension of artificial intelligence, which will enhance operational efficiency and ensure that clients receive the highest quality of services. In addition, it will aid in the process of product development and marketing, which will allow the various departments of the bank to offer products that are compatible with the unique needs of our customers. In this context, our partnership with JBS comes through its commercial partner IBM, which will be providing us with the Netezza Performance Server, the latest generation of servers dedicated to processing data.”

According to Capital Bank Chief Data Officer Bahaa’ Awartany, “Our cooperation with JBS and IBM comes in line with our belief in the importance of providing advanced and high-level data management technologies, as well as developing machine learning (ML) and artificial intelligence (AI) applications to improve the performance of our banking services. By remaining up to date with the latest technological developments in the global banking sector and strengthening the digital infrastructure of the bank, we can ensure smooth and efficient operations.”

JBS Director of Innovation and Business Transformation Khaled AlKadi spoke about the importance of adopting artificial intelligence solutions in the Jordanian banking sector, which will allow banks to provide the most suitable and innovative solutions to their customers. AlKadi went on to add that Capital Bank is a leader in the field of digital transformation, both locally and regionally, and its implementation of the IBM Cloud Pak for Data and Netezza Performance Server solutions will centralize data in a single master system that enhances analysis for a quick, methodical and proactive decision-making process.

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