How can AI help governments and firms save money on economic crime?

The discussion around artificial intelligence isn’t likely to conclude anytime soon, with many industries looking to the expanding technology to understand how they can benefit from it. In the area of economic crime, what role could AI play in bringing down burdensome costs?

In the view of Joseph Ibitola, growth manager at Flagright, AI has already begun to revolutionise the fight against AML and economic crime, and its potential to drive cost savings for governments and businesses is immense.

He said, “Traditional AML compliance systems are not just costly, they’re often inefficient, leading to a flood of false positives that require significant human resources to investigate. AI changes the game by making these processes faster, smarter, and more cost-effective.”

One of the most applications for AI, Ibitola claims, is in transaction monitoring. By using ML algorithms to analyse transactional patterns, AI is then able to more accurately flag suspicious activity, reducing the number of false positives.

“This not only cuts costs associated with manual review but also allows compliance teams to focus on genuine threats,” said Ibitola. “At Flagright, our AI-driven solutions empower financial institutions to streamline AML processes, delivering faster and more accurate insights at a fraction of the cost of traditional methods.”

In the area of government, Ibitola explained, AI can provide a key boost in tackling economic crime by boosting the efficiency of public sector investigations. These AI-powered tools are able to analyse huge amounts of financial data – such as tax records, public spending, or cross border transactions – at a speed hard to match by humans. This, he adds, helps governments identity fraud, money laundering and tax evasion schemes more quickly.

Ibitola explained, “Looking to the future, AI’s ability to predict and prevent financial crime could be transformative. Imagine a world where governments and businesses use predictive analytics to identify vulnerabilities in their systems before bad actors can exploit them. By deploying AI-driven risk assessments, institutions can take pre-emptive measures, avoiding costly breaches and penalties.”

AI is also able to open the door for increased collaboration between public and private sectors. “Shared AI-driven platforms could enable real-time information sharing between financial institutions and regulatory bodies, creating a more unified front against financial crime.

“Ultimately, AI is about creating a more agile and effective defense against the growing sophistication of financial crime. Governments and businesses that embrace AI-driven solutions today will be better equipped to handle the challenges of tomorrow,” Ibitola concluded.

TD Bank AML failure 

AI is able to take the fight to financial crime actors in various ways. 4CRisk.ai provided the recent example of TD Bank’s AML failure – stating that if TD Bank had a solid compliance map solution in place, things could have gone differently.

The firm explained, “A tool like this could have helped the bank stay on top of its regulatory obligations in real-time, mapping external requirements, like the BSA, to its internal policies, procedures, and controls. This wouldn’t have been just a formality — it would’ve provided real-time insights into gaps or weaknesses in their compliance framework. “

4CRisk stressed that if TD had implemented something similar to its Compliance Map solution, their risk of non-compliance would have been substantially reduced – saving time and money whilst maintaining their compliance programs.

“Instead of missing out on huge chunks of transaction monitoring, TD Bank could’ve used the Compliance Map product to quickly assess gaps in their AML program. AI-driven Compliance mapping flags weak or incomplete controls almost instantly, instead of relying on manual processes,” said 4CRisk.

With Compliance Map, 4CRisk stated that the bank could have kept track of where gaps were in their compliance controls in real time, especially in high-risk areas. A simple visual representation would have showed what was missing before things got out of hand. The RegTech firm’s products also help bring together policies, contracts, controls and procedures into one unified strategy.

“For a bank as global as TD Bank, this would have been a game changer, making sure that everyone was on the same page, no matter where they were,” said the firm.

It continued, “While AI tools can handle a lot of the mapping and assessment work, human experts are still needed. If TD Bank had used tools like 4CRisk, it could’ve sped up decision-making and acted on regulatory warnings before the penalties piled up.

The firm concluded, “Our products also keep up with regulatory changes as they happen. TD Bank could’ve stayed ahead of any updates, avoiding future violations and staying in the clear.”

Providing cost remedies

From the viewpoint of South African RegTech RelyComply, AI is providing remedies to the cost of compliance, mostly by speeding up the investigation and reporting time burden. Most banks, the firm said, have spotted that the tech can process a large volume of transactions between accounts in a matter of days, all with pinpoint accuracy to flag any odd payments.

RelyComply said, “Wasting time and money on false positives is a huge challenge for compliance teams, especially when we’d like to think most global transactions are legitimate and contribute to a free-flowing macro-economy.

“AI models trained in historical behaviours can know instantly when they are suspicious, funnelling time and effort towards the high-risk alerts that may genuinely matter in investigating and fighting bad actors. AI’s predictive analytics may save institutions cash further down the line, too: both people and AI’s expertise in deep learning and natural language processing is growing, meaning more accurate predictions of future money laundering threats are possible,” said the firm.

Prior to the tech explosion, banks and specialist units may once have felt like they were playing catch-up to criminals, but as the firm highlights, AI provides multiple ways for fims to remain on the front foot.

RelyComply added, “I feel that’s the major shift in the power granted by AI: it alerts compliance teams to the crime before it happens. They’re proactive rather than reactive. Housing financial data and using it wisely through automation is the key to more streamlined and precise investigations, and efficiency is the key to empowering a more safeguarded financial system.

A wall of protection

According to Jon Elvin, strategic risk advisor at Saifr, AI can help businesses and governments prevent, deter and respond to global financial crime with techniques not previously seen.

To Elvin, there are three key areas with immediate impact. Firstly, to help drive insight, context and actionable implications drawn from massive amounts of customer characteristics and transaction data that humans cannot process thoroughly or timely absent new technology.

Secondly, such technology is able to drive substantial operational efficiency and effectiveness in speeding up cross-channel investigations across multiple institutions, networks and global jurisdictions.

The last area it can help is to drive effectiveness that not only helps address financial crime, but a dual value return to better understand and serve customers, improve employee experiences, and reduce unneeded questions and delays in opening and managing the customer experiences while protecting their privacy.

Elvin concluded, “While AI can help thwart financial crime and is often seen as a significant accelerator for financial crime fighters, but it is also true that bad actors will assuredly experiment with AI to shape their tradecraft and probe weaknesses in financial and business pathways. It is the proverbial “cat and mouse” and a journey of measures and countermeasures. Sometimes bad actors adjust and react quicker than legislative, regulatory, and/or investigative agencies do.”