AI drives cost savings for regtech – research

Although AI has vast potential, its use must be in line with overall business objectives

AI drives cost savings for regtech – research. Source: shutterstock.com

New data from Juniper Research forecasts that the value of regtech spending will exceed $127 billion by 2024, up from $25 billion in 2019. This growth will be driven by a dramatic rise in the automation of resource-intensive tasks, such as those involved in KYC (Know Your Customer) checks and increasing use of AI in transaction monitoring.

According to the research, AI is ideally suited to regulatory space, as it can dynamically reduce false positive and false negative rates; leading to significant time, resource and ultimately cost savings for compliance monitoring processes.

With no anticipated relaxation of regulatory rigor over the forecast period and the ever-increasing specter of financial penalties for non-compliance, global regulatory compliance spending will increase from just under $278 billion to more than $316 billion over the next 5 years. Juniper Research forecasts that growth in West Europe will be driven by potentially divergent regulatory rules mandated by the UK and the EU following Brexit. While disruptive, this will create additional opportunities for regtech in the region.

The combined cost savings for KYC checks for banking and property sales will near $1 billion by 2024; a growth of 690%. The impetus for this will be efficiency savings, as well as the enhanced user experience that can be implemented in customer onboarding. This will reduce user frustration by improving response times; increasing overall user satisfaction.

As the financial systems of developing regions become more advanced, so will their needs for regtech solutions; these regions will have increased regtech spending in the longer term. The report recommends that organizations invest in the cost-saving potential of AI and cautions that although AI has vast potential, its use must be in line with overall business objectives or deployments will invariably fail to meet expectations.

SEE ALSO: AI in fintech: how technology applies to business

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