Today, the UAE Ministry of Finance announced that it has completed phase two on its journey of embedding robotic process automation (RPA) into many of its internal processes, leading to major productivity and efficiency improvements. The Ministry now uses bots, which are software applications that carry out automated tasks for 1.8 million transactions with greater than 98% accuracy, saving 39,000 hours of human labour.
We have all probably interacted with a bot at sometime in our life. The most commonplace are chatbots who manage telephone and online interactions between organizations and their clients. Bots are also increasingly used in the public sector as government entities try to improve efficiency and customer services.
The Ministry of Finance, possibly among the most important of government ministries, is responsible for implementing all fiscal, monetary, and industrial policies related to the UAE’s economic development. The more efficiently it can manage its internal processes, the better able it is to deliver the UAE’s national priorities.
Before 2020, the Ministry identified functions that could be improved with automation. These included accounts payable, payroll and pensions, financial accounting, IT processes, and webservices and hardware monitoring. They were carried out manually and the repetitive and undemanding nature of the tasks led to employee frustration, errors and poor service delivery.
In theory, if bots could carry out these tasks, they would be done more efficiently and accurately, leaving human staff with more time to carry out more stimulating and important tasks.
Hence, the Ministry of Finance sought to identify where they could deploy bots to maximum effect, design and test the bots, and then implement the new system. The Ministry worked closely with a partner to set up all the bots from scratch. By 2022, it had more than 50 bots working unattended, delivering great results, and it expects to save an additional 12,000 working hours in 2023. To date, the Ministry of Finance has automated 63 processes and subprocesses, reflecting a 95% reduction in errors and a 65% reduction in average handling time.
RPA is one aspect of the modernisation of government affairs, which will create a culture of excellence. In turn, the culture creates a conducive environment for innovation, which paves the road for the transformation of the UAE as laid out in the ‘We the UAE 2031’ vision and the UAE Centennial Plan 2071.
The process automation initiative falls under the Ministry of Finance’s Strategic Plan 2023-2026, which is a roadmap to accelerate government performance through financial empowerment, sustainability, innovation, financial leadership, and sustainable development. It is underpinned by a series of pillars designed to improve the function of government by promoting innovative practices – such as the adoption of RPA.
The Ministry’s initiative also aligns with the main objective of the UAE Digital Government Strategy 2025 – to create a government commitment for embedding the digital aspects into overall government strategies. This is crucial to ensure that the UAE Government is digital by design, and that all capacities, structures, and opportunities are integrated on a national level and aligned with the UAE’s strategic digital government vision.
Bots are likely to become a regular feature of the internal processes of ministries in the UAE, but they also appear on public sites. On its website, the Ministry of Finance offers a Digital Procurement Platform, which enables it to accelerate processes from 60 days to six minutes, creating greater competition by allowing more small companies to compete for government contracts.
The benefits of automation for the UAE are clear. The Ministry of Finance, among other federal and local government entities, has realised the potential of implementing robotic process automation and is only at the beginning of its journey towards improved efficiency and productivity in business operations.
Phase three of embedding RPA is expected to raise the total of automated processes and subprocesses to more than 100 and a further reduction in average handling time by 10% with error reduction across all bot-handled processes by 98%.
