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The artificial intelligence revolution is transforming the way businesses operate — driving innovation and reshaping the workforce. This emerging technology has significant implications for just about every kind of company but will have a particular impact on industries like financial services, which are subject to high levels of regulatory compliance. An experienced cybersecurity services provider can help organizations successfully implement this new solution and achieve an ROI with AI-enabled tools and training.

Some financial institutions have dipped their toes into AI waters with such initiatives as automated negative news screening and analysis, automated data retrieval, and using predictive models to enhance or accelerate such decision-making processes as risk scoring for transaction monitoring. Thanks to the development of ChatGPT and other generative AI models, however, some regulated organizations are also considering deploying AI to save countless full-time employee hours by scanning authoritative sources for regulatory updates, and quickly producing summaries of the most important information for senior management to review and interpret.

If management then determines that certain regulatory changes will require updates to an organization’s standards and procedures, AI solutions will be able to generate first drafts of policy documents with a simple command like, “Create an AML [anti-money laundering] compliance policy for a bank in the U.S.” Although the document will be a template – and will need to be customized based on the specific nature and size of the bank, as well as any applicable laws and regulations – the governance model can help businesses significantly reduce their regulatory mapping costs while expediting the change management process.

AI can also turbocharge other time-consuming processes, including transaction monitoring and sanctions screening, which typically generate a high volume of false positives that must be investigated and resolved. For example, while screening for the name “Tom Jones” might produce a high number of low-quality hits, a search for “Tom Jones” that reflects such additional information as age, vehicle registrations, address, work history and other inputs from a variety of sources would likely produce a high-quality, shorter list that can be resolved in less time.

AI may also provide a speedier solution for a vital but time-consuming AML tool: suspicious activity reports that must be issued by financial institutions whenever a client’s activities raise red flags. Researching and completing these lengthy reports can currently require significant FTE hours, but AI tools can be trained to generate a customer profile and then scan a variety of sources to flag any potentially suspicious customer activity, freeing up investigators for higher-level review tasks. Streamlining these kinds of resource-hogging processes will also save on operational costs and should reduce the number of alert backlogs at institutions, leading to fewer regulatory penalties.

But even as AI enhances productivity in financial services and other organizations, the increased adoption will bring new compliance challenges. For example, because AI and machine learning rely on large amounts of training data, businesses must take steps to avoid bias, and ensure that AI-enabled systems have access to accurate, complete, and relevant information.

And since the data used for AI training models may contain sensitive or personal information, organizations may need to adjust their policies and procedures around data collection, storage and use. The rise of AI also introduces new cybersecurity risks, including phishing, where cyber criminals fraudulently send emails or other messages – which appear to be from a reputable source – to induce individuals to reveal passwords and personal information or to transfer cash and other assets.

However, an automated AI-powered email security approach can help to detect fraudulent content and a comprehensive, multilayered cybersecurity plan with employee training, state-of-the-art authentication methods, and privilege management can help to guard against cyber criminal intrusion. A successful cybersecurity initiative will include schedules for periodic audits and compliance monitoring with provisions to adjust algorithms to accommodate regulatory requirements. Staff should also undergo robust training on the principles, practices and implications of AI projects — including the potential for bias and other ethical issues.

AI-related and other compliance solutions can provide critical data visibility and control throughout an organization, simplifying data classification and compliance monitoring, and providing critical transparency.

Combined with comprehensive data security, a well-developed compliance solution administered by a trusted IT support services provider will deliver the peace of mind that businesses and regulators alike require.

Carl Mazzanti is president of eMazzanti Technologies in Hoboken, providing IT consulting and cybersecurity solutions for businesses ranging from home offices to multinational corporations.