What Are the Applications of AI in Legal Compliance Practice

What Are the Applications of AI in Legal Compliance Practices?

Artificial intelligence (AI) can seem like more of a buzzword than a tangible solution. However, this new technology is a driving force in technology strategies across all manner of business practices, compliance included.

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Compliance is an essential process and organisations need to extract maximum value, ensuring that they don’t incur unnecessary charges on the business. Below Colin Bristow, Customer Advisory Manager at SAS UK & Ireland, explains how new technologies can ease some of the pressure from organisations when it comes to compliance.

Unsurprisingly, the extent to which technology accelerates outcomes depends on how sophisticated an organisation’s technology architecture is in the first place. Therefore, establishing where a business is starting from becomes just as important as identifying an end goal.

RegTech, AI and the future compliance landscape

The burgeoning RegTech (regulatory technology) industry is seeking to highlight how AI can be at the forefront of augmenting compliance practices. RegTech partly focuses on improving the efficiency and effectiveness of existing processes. As part of that improvement, organisations are starting to use AI, machine learning and robotic process automation (RPA) to smooth the integration and processes between new RegTech solutions, existing legacy compliance solutions and legacy platforms.

Why look to AI for help? Recent regulations, such as GDPR or PSD2, are handed down in the form of large and extremely dense documentation (the UK Government’s guidance document for GDPR alone is 201 pages). Identifying the appropriate actions mandated by these lengthy documents requires a great deal of cross-referencing, prior knowledge of historical organisational actions, and knowledge of the relevant organisational systems and processes. What’s more, several regulations attract fines or corrective actions if not applied properly (like the infamous “4% of company turnover” penalty attached to GDPR).

In short, the practical application of regulations currently relies on human interpretation and subsequent deployment of a solution, with heavy penalties for noncompliance. This is where AI can help, reducing the workload involved and improving accuracy.

Here are three key examples of how AI can help companies turn compliance into a value-added activity.

1. Ensuring regulatory compliance

Following the deployment of compliance processes, there is often residual risk. This can be as a result of unforeseen gaps in compliance processes, or unexpected occurrences that become apparent when operating at scale.

That’s partly because there are usually a lot of steps and processes to be carried out during the data collation stage of compliance programmes. RPA can help reduce administrative load associated with these processes that include a high degree of repetition – for example, copying data from one system to another. AI can then help process cross-organisational documentation, combining internal and external sources and appropriately matching where necessary.

AI can also help to reduce companies’ risk of noncompliance with, for example, privacy regulations. Using AI techniques, organisations can automate transforming and enhancing data, and intelligent automation allows companies to carry out processes with a higher degree of accuracy.

2. Streamlining processes

Inefficient processes can hinder compliance. For example, automated systems that detect suspicious transactions for anti-money laundering (AML) processes are sometimes not always as accurate as they could be. A recent report highlighted that 95% of flagged transactions are closed in the first stage of review. Effectively, investigators spend most of their day looking at poor quality cases.

Use of an AI hybrid approach to detection ensures there are fewer, higher quality alerts produced. It is also possible to risk-rank cases which are flagged for investigation, speeding up the interaction and relegating lower-risk transactions. Although AI forms an underlying principle across most modern detection systems, maintenance is key to managing effective performance.

AI can also be used to bolster AML and fraud measures more widely. For example, applying AI to techniques such as text mining, anomaly detection and advanced analytics can improve trade finance monitoring. This, in turn, can improve the regularity for document review and consignment checking, improving the validation rates of materials as they cross borders.

3. Keeping up with constant change

Compliance never stands still. Businesses have to contend with a constantly evolving landscape, potentially across several regions. AI can help to optimise the processing of these regulations and the actions they require, helping companies keep up to date. Companies that need to effectively comply with several differing regulations require an understanding across all parts of the business. The size, complexity and legacy systems of the business can be significant obstacles.

To mitigate this risk, companies can use natural language processing (NLP) to automate aspects of regulatory review, identifying appropriate changes contained in the regulation and then relaying potential impacts to the appropriate departments. For example, AI could help geographically diverse companies determine whether changes in the UK have an impact on their Singapore office.

4. Believe in humans

Artificial intelligence and RegTech are by no means panaceas, and humans will still play a key role in compliance processes. AI is accelerating outcomes in RegTech, but it is used primarily to automate manually intensive and repetitive tasks. Ultimately, these new technologies are complimenting the work of humans, enabling them to increase operational efficiencies.

Like any technology, there are no shortage of issues, for example doubts around the possibility of bias in AI deployments. Elsewhere, there are arguments around the ownership of generated IP and the importance of transparency and governance of applications. Therefore, human involvement is crucial, providing the necessary levels of manual oversight.

The applications of AI in compliance practices are numerous. The technology quickly sifts through vast documents, pre-emptively detects fraudulent activity and provides meaningful insights from complex data. Whether at the beginning of a regulatory review, or the end of the compliance process, AI is an invaluable tool which will ultimately lead to a much more streamlined compliance function.

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