Abu Dhabi, UAE – April 08, 2021: Abu Dhabi Islamic Bank (ADIB), a leading Islamic financial institution, has partnered with SAS to utilize their advanced AI-driven Fraud Management technology to help enhance and improve the bank’s fraud detection and investigation capabilities.
Through the partnership, ADIB will benefit from an enterprise-wide fraud detection system built on the SAS Fraud Management solution, which utilises industry-leading data analytics and machine learning technology to monitor payments and non-monetary transactions, as well as events, enabling ADIB to utilize AI for predictive fraud detection.
The solution utilises in-memory processing to deliver instant responses, seamlessly integrating and analysing all data regardless of source or type, including third-party data. Equipped with a range of powerful tools at their disposal, administrators have the ability to handle alert resolution, manage payments and risk decisions, perform hot listing and blocking, and conduct downstream fulfilment actions from a single interface.
Additionally, ADIB will benefit from an array of innovative cloud computing capabilities powered by SAS, helping the bank align its business and operating model implementations. The integrated solution will offer the bank significant cost efficiencies, scalability, and flexibility, ensuring that their infrastructure can handle increased traffic spikes and support compute-intensive workloads securely and at scale.
Commenting on the partnership, Mamoun AlHomssey, Chief Information Officer of ADIB, stated, “ADIB has invested heavily over the years in technologies and strategies to combat fraud. As a pioneering organisation and one of the leading Islamic financial institutions in the GCC region, ADIB is strongly committed to innovation and utilising the latest solutions to further enhance and strengthen our fraud detection resources. Working with SAS, a leading analytics and Fraud Management vendor, we want to take advantage of a fraud detection and prevention solution that can support multiple channels and lines of business and enable us to carry out enterprise-wide monitoring from a single platform. A particularly attractive feature of the SAS Fraud Detection solution is the embedded machine learning capabilities that ensure the system will become even more effective over time and able to recognise new types of fraud as they emerge.”
Michel Ghorayeb, UAE Country manager at SAS added, “SAS is committed to safeguarding the organisations’ reputation and bottom line by helping them stay ahead of shifting tactics and new fraud schemes. With SAS Fraud Detection, ADIB will be able to better anticipate, protect and prevent new complex frauds as well as get a holistic view on all fraud risks across all their channels in one single platform. It is vital that the application of sophisticated new techniques do not adversely impact the customer experience. With our enhanced fraud detection system and support for in-memory computing, machine learning methods and real time decisioning, response times are more rapid and false-positive cases are immensely mitigated, delivering an improved customer experience.”
With the rise of the prevalence and sophistication of fraud attempts brought by the Covid-19 pandemic, ADIB continues focus on safeguarding its customers from such attempts. Through utilising cutting-edge technology, the bank works to continuously evaluate, develop and implement advanced banking security measures to protect customers from fraud. Based on ADIB’s strong and ongoing commitment to fraud prevention, the bank has one of the lowest fraud rates amongst card issuers in the UAE.
Disclaimer: The content of the above information is sourced (or provided), in entirety or in parts from an external source and the content may or may not be edited. The Wealth Today shall not be held liable for damages arising out of any action taken with respect to the use or consumption of information or service published above or anywhere else on the website. This website does not guarantee the accuracy, views, opinions or any promises expressed in the above news.
If you find any errors or discrepancies in the above information, you can write to us at email@example.com.