KYC due diligence: what you don’t know can hurt you
Some refer to it as know your customer, or know your client (KYC) or simply client acceptance. Whatever the name, the process remains the same, and it lies at the heart of customer identification and onboarding for financial institutions.
In the past, KYC was designed for routine checks on new clients. Today, KYC is the first line of defense against financial crimes, such as fraud and money laundering. While financial institutions are well versed in the KYC process, it remains a costly and complex undertaking. According to some estimates, global financial institutions spend an average of $150 million annually on KYC due diligence operations.
Financial regulators levy hefty fines for non-compliance. Then, there’s the potential costly exposure to reputational damage. The results of reputational damage can be wide-ranging — from brand destabilization to erosion of shareholder value to a loss of customers.
Despite all the resources and time being spent on KYC due diligence, many organizations still struggle with inefficiencies, including a high reliance on manual processes such as online searches for adverse news on potential clients.
What’s more, the standard in the industry is to rely on watchlists and databases to find information on individuals and entities. While these resources are an important part of the process, there's an increasing need for real-time information gathering and always-on monitoring. Institutions cannot simply rely on existing clients to provide them with updates on material changes to their companies. They also need to keep a close eye on high-risk clients.
Adverse online media monitoring
Not enough institutions are adequately or effectively monitoring online media for adverse news on the people with whom they choose to do business. Given that online search algorithms change often, and the list of information sources grows by the day, manual searching is a painstakingly ineffective way to conduct due diligence.
Artificial intelligence is a game-changer in this arena, because human beings cannot be expected to parse through the staggering amount of publicly available online data that could exist on thousands of potential business stakeholders at any given time. It’s why Valital combines human and artificial intelligence to help organizations identify, detect, analyze, and mitigate reputation risks.
Valital uses Natural Language Processing (NLP), a form of AI that enables computers to extract language from unstructured text. The AI learns human language and uses content and context to perform real-time search and pulse analysis of online media, blogs and tweets, flagging misconducts related to universally recognized misbehaviours: discrimination, financial crime/fraud, harassment, violence, and abuses.
For financial institutions that have a fiduciary responsibility to customers and access to large volumes of sensitive information, the old adage of trust, but verify isn’t good enough. Verify, then trust means organizations can make better, more confident decisions about the people with whom they choose to do business.
Financial institutions exist in an ever-changing global regulatory environment. They need ongoing, real-time access to information and monitoring. Adverse online media monitoring is an essential part of the KYC due diligence process, and institutions need the right technology deployed at the right time to help shore up risk management efforts.