These days it is difficult to pick up a business journal without finding a story about Artificial Intelligence (AI) and how it is going to 1) transform business processes, 2) eliminate jobs and 3) replace human thinking with machines who will ultimately rule the humans. Although the first element seems likely, at least in some use cases, the second remains a work in progress and the third is hard to imagine.
AI has become the flavor of the year. In 2018 it was blockchain, a technology that is very slowly inching its way into a few niche applications. But unlike blockchain, which requires multi-party cooperation to work at scale, AI has the potential, among many possibilities, to simply increase throughput and create order for one actor.
As we become a seemingly evermore-regulated world there is the inevitable and concomitant trail of paper created. New ways of search, examination and validation must be found to relieve the workload and improve processing. This is nowhere more true than in the area of compliance.
The demand for document compliance is driven by both increasing regulation and the potential liability to businesses failing to properly evaluate, monitor and react. Accenture’s 2019 Compliance Risk Study found that nearly three-quarters (71%) of compliance departments at financial institutions face a cost reduction target, with nearly two-thirds targeting budget reductions of 10% to 20% over the next three years. They are also suffering employee attrition, with reports of compliance officers being overworked and exhausted.
More human labor thrown at the task is not the solution. There is an urgent need to embrace new technologies to improve both compliance and productivity. AI and Natural Language Processing (NLP) will be required, causing companies to re-imagine their workflows and business processes. Apart from work speed improvements are the potential qualitative changes that AI could bring to compliance. For example, are documents being interpreted correctly and in compliance with internal and/or external requirements?
The financial service sector alone brings enormous opportunity to businesses able to reduce their daunting compliance-related costs. In a large bank, 200—500 analysts may be charged with Know Your Customer and Anti-Money Laundering compliance alone. Making matters worse, conventional searches generate very high rates (up to 95%) of false-positives, requiring further manual follow up.
Machine-learning technologies have a role to play because the financial burden imposed on organizations is significant. In our world – business services - there is increasing pressure for faster throughput and greater efficiency. Even drugstores are feeling the pinch – they are now required to track prescriptions amid issues like growing concern over the opioid crisis. It can be reasonably assumed the demand for document tracking and compliance will not diminish and the service expectations of clients will become greater and more complex.
There will always be trade-offs between black-box processes like AI and humans, but the trend toward ever-greater vigilance in many industry sectors clearly demands the attention of businesses able to contribute solutions to this growing challenge.
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