With the use of artificial intelligence by businesses and individuals alike exploding across the world, one of the biggest challenges going forward that is facing the industry is to ensure that AI remains ethical and well structured. How can RegTech help in this battle?
South African RegTech firm RelyComply stressed off the bat that AI has taken compliance by storm for opposing reasons.
The company said, “On the one hand, the usage of AI in criminal acts (fake identities and documents to curb verification, for instance) is growing. But AI also provides the means to combat this: automating onboarding and transaction checks around the clock, flagging anomalies as they happen to reduce the risk of failed compliance, or letting criminality pass by undetected.
“AI’s capabilities are brilliant for organisations to implement, so long as RegTech platforms utilising AI are doing so, they align with policies and regulations around ethics. The data science field is becoming more expert in fine-tuning AI’s side effects of hallucinations or cognitive bias. It’s not just a ‘must have’, as AI has to be accurate and fair to complement human-led AML compliance.”
RelyComply emphasised that there were enactments going on currently to ensure AI is used safely – with the EU’s AI Act one key example, which categories AI by risk and introduced penalties for misuse.
“More significant AI protocols may be enacted in countries where regulation is being introduced while others lag. Some RegTech may provide an answer by being agile to rapid changes in legislation, especially with software developed through consultations with AI expertise,” said the firm.
Despite this, the company stressed that AI governance around its use must also be widespread. Through the documentation of how AI-backed RegTech platforms run, the data they house, how their models work and underlying AI code, this means auditing its usage is more transparent.
The company continued, “Given RegTech’s interoperability with partners (for system capabilities or data handling), AI life cycle management is needed to ensure the safe cross-compatibility of any data-led decision-making tools and to identify to shareholders that the technology is working as it should.
“Using AI ethically is another collective responsibility between governments, businesses, RegTechs, and regulators that is integral to maintaining compliance. Great AI practice is a skill becoming more critical in this data-rich ecosystem; having more controlled standards by which to use it, with flexible RegTech solutions, should see safer, more informed uptake across the globe,” said RelyComply.
A crunch issue
According to Madhu Nadig, co-founder at Flagright, as AI becomes a bigger part of financial decision-making, ethical AI compliance is turning into one of the biggest regulatory challenges of our time.
He said, “Bias in AI models, lack of transparency, and unethical automation can lead to unfair banking decisions, discrimination, and regulatory fines.”
RegTech, Nadig commented, can play a huge role in solving this. Some of the keyways include making AI explainable and transparent – as regulators want AI models that work, he said, in addition to justifying their decisions. RegTech solutions, Nadig added, can also ensure AI-drive compliance systems log every decision, making them auditable and fair.
Another important area RegTech can help is with bias detection and model validation. “AI can unintentionally reinforce biases if trained on flawed data, and RegTech platforms can continuously monitor AI models for discrimination, ensuring compliance with ethical AI regulations,” Nadig said.
Nadig also mentioned real-time compliance monitoring as a key area for RegTechs in ensuring ethical AI compliance.
He said, “AI models need constant supervision to ensure they align with ethical standards. RegTech tools can track AI behavior in real-time, flagging any irregularities before they become legal issues.”
Nadig gave the example of AI-driven loan approvals. “If an AI model unfairly rejects certain demographics, RegTech solutions can detect this bias, log the reasoning, and alert compliance teams before regulators step in.”
High quality data
According Dr Janet Bastiman, chief data scientist at Napier AI, said, “AI models necessitate large amounts of high-quality data, and small financial institutions may struggle to gather, clean, and maintain such data due to smaller customer bases and less comprehensive data collection systems.
“Not every firm is inherently well placed to collate customer and transaction data, not to mention data from external sources – as this is necessary to generate a holistic picture of customer behaviour in financial crime compliance. Data security risks also arise as insufficient data security measures can lead to breaches, exposing sensitive financial data and damaging trust.”
She continued, “AI is all about pattern detection, so when a model gets a hit for money laundering it has a risk of ‘overlearning’ everything about that transaction. As a result, biased and discriminatory outcomes are possible because they’re based on flawed data, which is inadequate and unrepresentative of the populations from which they are drawing inferences. This could be tackled through Regtechs using synthetic data sets for training AI models in financial crime compliance.
“Using synthetic data sets can be used to enhance explainability and protect against potential bias risk – as it recreates the risky activity in isolation from personally identifiable information (PII) and protected characteristics and then distribute it through your data to ensure your models are learning the correct patterns. This helps in the fundamental understanding of the data you have and what is possible and what is not, with the considerations needed for effectiveness and accuracy.”
On the same highway
In the opinion of Oisín Boydell, chief data officer at Corlytics, AI compliance and AI regulation are two directions of the same highway, that are closely linked.
He said, “Compliance, in general, is complex due to varying jurisdictional requirements, and AI is no exception. This regulatory challenge as any other is precisely why RegTech and specifically Corlytics exist.
“Just as regulations shape how AI can be used, AI itself is being leveraged to manage compliance and risk. We can say that RegTech plays a dual role: it helps organisations navigate evolving AI regulations while also using AI to enhance compliance processes. At Corlytics, we apply AI to help companies stay aligned with regulatory expectations, including AI-specific compliance requirements.”
Regulatory change management
RegTech firm 4CRisk.ai detailed that in its view, RegTech can help ensure ethical AI compliance through regulatory change management and compliance framework analysis to understand what AI regulations are required by a firm, and further, how the framework has the right policies and controls in place to ensure compliance.
The company said, “At 4CRisk, we do this through our AI-powered Regulatory Change Management and Compliance Map products that provide traceability from regulations right through obligations and into policies, procedures, risk and controls, so that companies can see gaps in compliance.”
In a similar vein, Anthony Quinn, CEO and founder of Arctic Intelligence, commented that as AI becomes more widely adopted, RegTech firms are ‘uniquely positioned’ to ensure that AI is used in ways that are fair, transparent, free from bias and remain compliant with global regulations.
Quinn added “It sounds obvious but ensuring AI remains unbiased, explainable and auditable will help ensure supervisors can adequately provider effective regulatory oversight, if RegTechs play an active role in demystifying the “black box” problem, where early adopters of AI RegTech solutions can be confident in explaining how the technology works, as well as any limitations or shortfalls”.
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