With Covid-19 changing the way we work, possibly for a long time, artificial intelligence has stepped up to help combat the challenges that have risen making it easier on employers and their staff.
Ludré Stevens is Chief Product Officer at Inbotiqa, a next-generation Intelligent Business Email for high-volume and group mailboxes utilising the power of AI. Here he shares how artificial intelligence can be used in the workplace during Covid-19.
The onset of the Covid-19 pandemic and the dramatic changes in working practices it necessitated have created many challenges, for organisations, teams and individual staff members. Entire workforces suddenly shifting to working remotely has meant banks needing to support thousands of employees as they work from home, keep track of work execution and maintain regulatory compliance. All this while also needing to ensure high standards of customer service and SLAs are met.
With a return to widespread normal office working looking unlikely, effective long-term solutions to elevated compliance risks and other challenges need to be adopted and embedded. Video conferencing and collaboration tools, artificial intelligence (AI)-driven automated solutions, analytics, and more, have helped operations to continue, recording and monitoring issues to be addressed, and have even improved productivity and management insights.
The vast amounts of data involved in the financial services industry are beyond human scale so the application of AI and machine learning (ML) in order to meet regulatory requirements, boost productivity and cut costs was already prevalent. The pandemic and the changes it has wrought have only increased the need for and accelerated the adoption of AI and ML solutions.
For example, AI and ML can be used for surveillance and behaviour tracking to find issues, meaning specialised AI and ML, in-house built or vendor-built tools, are being employed to support the new normal. Employee-surveillance software that utilises the likes of ML and behavioural rules engines was already being used by enterprises inside their office spaces.
Since lockdown started, there has been an increase in the use of such products to monitor remote-working practices. The use of surveillance tools when employees are working remotely throws up its own privacy issues, though, if they are deemed too intrusive.
A recent Bain Consulting report found that three out of four companies planned on accelerating automation initiatives across the board post-Covid, including those dependent on AI/ML, with the financial services industry having the largest percentage of respondents with this on their roadmap, at 93%. This despite the fact that many technology executives were already expressing uncertainty about their investments in machine learning and dissatisfaction with the way their companies were adopting it.
Dedicated AI-driven Regtech companies such as providers of behavioural analytics and big data and analytics or AI-powered biometrics that bolster document verification for anti-money laundering (AML) and know-your-customer (KYC) capabilities, were already established in the market place.
Companies often opt to buy rather than build solutions due to cost, time and talent issues, and there is an increasing choice of third-party tools on the market. Technologies already being built or bought to boost productivity and aid compliance have also proved uniquely helpful in facilitating remote working during this swift adjustment.
The flexibility of tools is also an important consideration. For example, our YUDOmail intelligent business email system uses its own ML to classify communications such as emails to route and classify work, meaning work can be allocated and tracked to people working remotely.
However, in addition, it also allows for vendor AI and ML tools as our structured email data can be easily ingested by them.
This structured email data including related metadata (audit trail and threads) saves other AI tools from having to search for email data and then structure it themselves. By also providing a delivery method for any workflow outcomes from these AI tools, the loop is closed.
When it comes to auditing, the man-hours alone spent on gathering data for audit purposes can be considerable, so it makes sense to integrate a compliance-driven recording strategy into communications so that an audit trail is created in real-time. Supporting asynchronous working, where employees are on more flexible hours now working from home, is another aspect of the new normal of increased remote working that needs to be considered and addressed and where AI can provide value.
Whatever the specific solutions opted for are, and whether employees are working from home or in the office, it’s clear that AI and ML are playing a big and rapidly increasing role in the financial services industry. The Bain Consulting report also notes that what separates the leaders from the pack is their ability to make real changes in the way they get work done and integrate AI into products and processes across the organisation, allowing them to differentiate themselves based on AI-driven insights.