By James Duez, CEO of leading intelligent automation firm, Rainbird.
Our recovery from the coronavirus pandemic is set to accelerate automation adoption, with 41% of respondents to an EY survey saying they are increasing investment in this area. But unless organisations are able to capture specialist expertise, they will be more vulnerable as automation spreads: to make judgements at scale that are consistently in line with a company’s best practice, automation technology needs to have human subject matter expertise at its heart.
For example, while bots can comb through transactions to identify regulatory breaches, human specialists are still needed to discuss with clients the precise implications of compliance lapses.
Additionally, as transactional tasks like accounts reconciliation or journal entries are increasingly automated, specialist skills will still be required to understand novel, nuanced situations. For example, robotic process automation (RPA) can streamline administrative functions so employees have resources to invest in important (but relationship-based) activities, such as networking with peers, prospects and customers. In fact, AI integration could cut costs and increase productivity in the financial industry by $1 trillion by 2030, according to recent research.
While its efficiency gains are rarely in doubt, RPA has been called a mere “gateway drug” to digital transformation, with its application confined to menial tasks. If businesses are serious about becoming dynamic, adaptable organisations, they’ll need to take the next step on the ladder to go beyond narrow task-based automation tools, towards technology based on the human logic of subject matter experts. From fraud investigators to insurance underwriters.
Human expertise is still king
Today’s AI will soon surpass human computational ability, objectivity and accuracy – in finance, machine-created credit decisions are expected to surpass human ones by 2024, showing this industry is no exception to the trend. However, AI still simply cannot compete with human intelligence when it comes to novel thinking, adapting to new contexts and circumstances, and navigating social situations or exhibiting self-awareness.
These key differences can be of great use to almost all industries, finance chief among them. Specifically, the industry is faced with enormous compliance challenges, in the wake of major political and regulatory changes (such as Brexit and the implementation of MiFID II). With more specialists needed to tackle these shifts in regulation and the resulting technological demands, it is simply unsustainable to expect humans alone to tackle challenges of this magnitude.
To efficiently utilise their resources, financial services firms must invest in intelligent automation solutions that can handle key aspects of nuanced compliance decision-making, alongside employees. This would in turn ease the pressure on hiring and leave relationship-based responsibilities to the most-qualified human experts.
Specialist knowledge is gaining importance
This kind of automation of expertise is likely to create remote, non-hierarchical workforces, composed of small, specialist ‘skunkworks’ working independently. These teams will have ‘knowledge authors’ who create models of an expert’s knowledge within machines. The machines then make expert judgements on typical auditing scenarios, while human specialists are reserved for complex ‘edge cases.’ Linear career ladders will also likely be phased out, as companies increasingly automate entry-level roles such as law clerks. Knowledge, lateral thinking and emotional IQ will replace job experience as important hiring criteria, as humans are increasingly hired at specialist, rather than entry, level.
The unprecedented demands placed on work—due to the technological revolution of recent decades, new regulations and the recent pandemic—necessitate a fundamental change in approach if we are to survive and thrive. By embracing and investing in intelligent automation across finance, the industry can lead the way in transforming the role of human expertise, while increasing the speed, accuracy and scalability of good decision-making across organisations.
