The financial services industry is currently on the brink of a massive technological disruption. Financial institutions are now beginning to actively explore new technologies, such as Artificial Intelligence (AI) and robotic process automation (RPA) to further automate routine AML and KYC processes and thereby improve operational efficiencies and resource utilization.
The first wave of AI technology deployment is already happening in global banks: rule-based AIs (typically based on ‘if-then’ rules) are enhancing productivity in internal processes. With the advent of AI applications for Know your Client (KYC) and Anti-Money Laundering (AML) purposes, financial institutions’ adoption of technology in these labor-intensive and high-risk areas seems certain to rapidly accelerate.
Below we further explore how robotic and AI-powered solutions can digitalize various client lifecycle management processes, creating increased efficiencies and reducing associated regulatory cost pressures:
Artificial intelligence (AI)
One of the most powerful ways AI can be applied in a client due diligence context is in using Natural Language Processing (NLP) to ‘read’ vast amounts of information in any language. This can be a great assistance in the onboarding phase, through intelligent document scanning and sifting through the array of external data sources banks should be consulting. As well as massively reducing risk, it can improve sales effectiveness and enhance the overall client experience.
The real power of the technology lies in its ability to intelligently extract risk-relevant facts from a huge volume of data, but then to also synthesize and deduplicate that information so that it is both meaningful and concise. This allows unstructured data from different sources and formats to be classified automatically for the KYC profile. Eliminating false positives and irrelevant results makes analyzing true risk a much easier task.
Machine learning can further identify candidates for automation by observing trends in user behavior. Once a client portrait emerges, it becomes possible to predict or model future customer actions. By utilizing AI-powered solutions to delve deeper into customer relationships, financial institutions can prepare for a more regulated future.
RPA enables financial institutions to automate repetitive, non-value adding and data intensive tasks. It is an ideal technology for a field like compliance that is predominantly rule-based and evolving constantly.
RPA can be used to perform validation of existing customer information (structured/unstructured) by accessing databases, extracting data from documents, merging data from different places and filling in forms.
Implementing RPA can streamline KYC decision-making through more effective client data capture and regulatory client classification and evidencing. With the addition of bots, RPA automates the client data entry process and conducts initial verification, passing relevant client records to Client Services if data gaps prevail. In addition, RPA solutions can automatically consume information (data and documents) from multiple vendors and utilities. This improves overall data quality and speeds up the time it takes for account set-up and client/product onboarding.
In terms of AML and risk rating, RPA can also make decisions related to AML alert types, PEPs and sanctions, leaving higher risk alerts and clients for AML and KYC professionals to check. It further aids the digitalization of client documentation, providing best guess attempts to categorize and index information, with users required only to complete a final review.
Intensifying regulatory scrutiny and rising compliance costs have resulted in a fresh perspective to KYC and AML compliance, in terms of digital transformation, operational efficiency and the agility required to deliver new forms of customer value in an increasingly competitive climate.
Many global financial institutions are now seeking to create a Centre of Excellence approach through the centralization of all client onboarding, AML and KYC operations across multiple business units and jurisdictions. To achieve this, they are actively exploring forms of intelligent automation and emerging new technologies to digitalize client lifecycle management, streamline data management and enhance regulatory compliance processes.