Robotics and artificial intelligence have been at the forefront of fintech innovation for several years now, and it seems the majority of organisations have started to accept and integrate various AI-powered financial solutions. From social media chatbots capable of real-time payment processing, to predictive analytics suites designed to optimise customer journeys, there are plenty of practical applications being rolled out by FIs, incumbents and unicorns alike.
But how has treasury responded to the increasing influence of robotics?
Believe it or not, robotics continues to be a fairly contentious point amongst treasurers. After all, while organisations are constantly on the hunt for further automation and smart treasury solutions capable of lowering costs and streamlining labour-intensive processes, mainstream adoption of AI in treasury has been stunted by a lack of trust and an inherent fear of redundancy.
According to a 2018 study commissioned by Deutsche Bank, 42% of treasurers claim that AI solutions are expected to be the most beneficial tech application for their organisations in the future. Yet that same survey found the technologies that crucially underpin AI applications such as robotic process automation (RPA) are relatively undervalued, with just 19% citing RPA as a key driver of operational change in treasury.
Likewise, the 2018 AFP Risk Survey found that many institutions are still wary of the technological risks like third-party data sharing associated with the deployment of robots in treasury – with only 14% of more than 600 treasury and finance executives surveyed reporting their organisations were “significantly prepared” to accept and cope with such changes.
Turning point
Despite that lack of preparation, 2019 is likely to be the turning point in which organisations finally warm to the idea of incorporating robotic software to strengthen their existing treasury functions. Some of this progress will stem from the development of ever-improving AI-powered treasury solutions – yet by and large, the majority will be introduced as reactionary responses to the deployment of robot technology across other departments.
RPA treasury solutions have been available on the market for some time now, and despite a wariness to adopt these platforms they appear to generate substantial returns. At its core, RPA is an automated tool designed to realise cost savings by removing the need for staff to carry out high-frequency tasks while simultaneously slashing processing times. Robotic solutions eliminate human error, improve compliance processes, speed up invoicing and accelerate underwriting processes.
Researchers at EY estimate the cost reduction associated with RPA deployment can save an organisation around 70% on some automated activities, while accelerating innovation by up to 12 months with tactical integration. In turn, organisations using RPA solutions should quicken the rate of service and product pilots without the need for costly legacy system upgrades or integration dependencies.
Mass adoption of robotics
Bearing in mind the net benefits of robotic processing in treasury, it’s little wonder Capgemini has estimated mass adoption of treasury automation tools like RPA could add $512 to the global revenues of financial services firms by 2020 – and in order to reach that potential, software providers now appear to be placing their focus on the development of easy-to-integrate RPA tools that can be closely monitored and made to scale.
For example, at the start of January leading RPA developer Automation Anywhere announced the launch of the industry’s first-ever mobile app for treasurers to securely monitor and manage bespoke RPA bots. Meanwhile, providers like Oracle and IBM have introduced RPA bots and processes that are available as quick and relatively affordable add-on products teams can seamlessly bolt onto their existing TMS or ERP platforms.
Above all else, it will be these easy-to-deploy and easily monitored treasury bot integrations – alongside reactionary solutions to the increasing influence of robotics and AI in other organisational departments – that should drive mass adoption in 2019 and beyond.
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