Artificial Intelligence (AI), in a broad sense, is very simple; it is the use of computers to perform tasks much quicker than humans could. It is often used to analyse large sets of data, finding patterns and connections that achieve an outcome without the need for human intervention.
Today, most people understand the data driven approach to analytics and suggestions through AI when it comes to their recent online shopping behaviour. We purchase goods online, and our preferred vendor will offer us goods that have previously been bought that might complement our purchase. The more data this algorithm has, the easier it is for it to make predictions and recommendations for users.
Of course, this algorithm does not care about why the associations between recommendations exist, it only cares that they do. In compliance, industry analysts care about the explainability factor – or lack of – which means we are yet to see this kind of multi-layered analysis being used to drive better outcomes for financial service customers. Financial institutions (FIs) are therefore, currently using more basic levels of AI or Machine learning (ML).
Thankfully this is changing, and as the regulatory compliance market starts to find its feet with AI, the following four main areas are being explored:
- Risk reduction through pattern detection
- AI and data analytics as an enabler of efficiencies for FIs;
- AI and data analytics as a cost cutting/reallocation of resources innovation; and
- AI and data analytics as a strategic value add for FIs.
Each of these four areas can significantly improve processes, potentially lower the costs of compliance and ultimately allow FIs to understand their customers better.
AI’s involvement in risk and fraud reduction
In the last couple of years, we have seen the focus being shifted to increasingly introduce the more basic forms of AI and ML solutions into FS to focus their efforts on the prevention of financial crime and fraud.
Know Your Customer (KYC) efforts in particular, which refer to businesses understanding their customer data base, and therefore providing an improved insight into the risk that each customer represents, rely on utilising rich data sets, which realistically, can only quickly be analysed if AI methods are employed. This is a huge example of AI solutions allowing financial firms to utilise these greater amounts of data to reduce the cost of data errors, duplicates and inefficiencies in decision making.
By doing compliance right from the beginning, overlaying the data gathered with analytics and AI, FIs can gain value longer term by not only being able to understand anomalies in customers behaviours, but by also being able to offer better products to their users.
Increasing efficiency within financial services
Industry reports discuss introducing efficiencies into the process by doing the same things better or faster, rather than introducing radical changes into FI strategic initiatives. Opportunities for driving efficiency are abundant, from deposits and lending, to insurance, to payments and other sectors.
FIs have been able to digitise as much as 90% of their processes through the automation of manual work, standardising time-consuming tasks and allowing human agents to focus on key decisions. For example, FIs have introduced robotic process automation (RPA), text analytics, insights and entity resolution, and network analysis into compliance. These aspects go to demonstrate that AI and ML have the potential to enhance the efficiency of information processing and to reduce information asymmetries.
Data analytics coupled with AI can also help FIs create more efficient and smarter organisations. FIs can get ahead of market changes and regulatory forces through the utilisation of such technologies, which will drive business strategy and results while using automation to handle huge volumes of data.
Numerous FIs in the market are exploring the option of utilising new technologies as a labour-saving innovation due to the extremely high costs associated with compliance staff. A recent report from LexisNexis Risk Solutions estimates that labour accounts for 57% of costs for FIs globally. Compliance functions within FIs continue to be cost centres and the costs of being compliant increase year on year.
The entire organisation benefits therefore, when FIs eliminate human-performed, menial and repetitive tasks. This in turn allows employers to repurpose their staff for more strategic and comprehensive tasks, rather than just replacing them with a machine.
It must be noted that in compliance, given the highly regulated environment, no machine will be able to fully make decisions for obliged entities. Transparency, audit trails, and a risk-based approach are critical to any compliance program. Explainability is a key feature, particularly within financial services, which emphasises the importance of the human role in the decision making process – all decisions must be verified to ensure they are correct and the conclusion that has been reached is ‘explainable’. In line with that, decision making on how to deal with certain customers, more so with those of higher risk to the organisation, should sit with a member of staff.
Technology is not a magic bullet – it can help with efficiencies, lowering the costs associated with the time it takes to onboard a customer, but ideally, organisations would create a combination of technology and compliance staff by using a two-layered approach.
Reaping the rewards
In an increasingly data-driven era, it is vital for businesses to understand the value of data and the methods by which it can be analysed effectively and efficiently. By implementing the right technology to facilitate the vast amounts of data needed to inform decisions, processes become more streamlined, the cost of compliance is significantly reduced and the risks are lowered. By utilising AI effectively, businesses can truly reach their full potential and reap the rewards of their initial investment.
By Nina Kerkez, Market Planning Director, LexisNexis Risk Solutions.
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