Financial institutions across the world are facing a collective, unprecedented challenge. Constantly-evolving, stringent Anti-Money Laundering (AML) regulations and “Know Your Customer” (KYC) safeguards require these businesses to present a transparent, detailed and precise view of customers. Cutting through the complexity of these regulations and managing data to ensure compliance places a huge burden on these firms financially, technologically and in terms of appropriate skill sets. It is, however, absolutely critical as the impact of non-compliance can result in millions, if not billions of fines for an organization.
Financial institutions around the globe have been impacted, making headlines in recent years. The media spotlight on this and other high-profile cases is adding pressure to regulators to respond and further tighten controls.
But the risk isn’t limited to just large, multinational banks and businesses. Regional, community banks and small financial institutions across the country are also being impacted by stringent AML regulations – often with far less resources to adapt to evolving laundering trends than their larger counterparts.
Around the world, financial institutions spend millions in compliance efforts, with a chunk of this spend being attributed toward human capital, and thousands of employees whose sole job is to investigate fraudulent detections and file suspicious activity reports (SARs).
According to the report, more and more financial institutions and community banks are turning to technology to assess exposures to different types of risk. Robotic process automation, advanced analytics, natural language processing, and blockchain are just some of the latest solutions providers are deploying to avoid AML fines, and to provide accurate and detailed information on customers structured in a consistent, transparent way.
Unfortunately, KYC and screening list data is prone to error and variation, and for smaller financial institutions, manually monitoring data to meet compliance can be a daunting and burdensome task. Pitney Bowes estimates that 95-98% of all suspicious activity is a false-positive. And for organizations without automated processes in place, this means the majority of these activities must be manually investigated by dedicated staff, which can result in millions of dollars spent in time and labor.
Smart organizations are overcoming this, and developing a clearer understanding of risk by applying new screening solutions that can aggregate data from multiple sources, such as KYC databases, transactional records, vessel lists, and notes on client engagements to create consistent, precise customer data. These screening solutions look at different data sources and references to an individual, taking into account inconsistencies, errors, transliteration, abbreviations and incomplete records, and determines whether they warrant further investigation, and are in fact, a true positive. By developing this “Entity Resolution,” both on the FI side and with the screening list data, they can eliminate much of the “noise” in the data and match with a higher level of confidence thereby reducing false positives.
Screening solutions are well within reach for community banks and small financial services providers. One example is the recently-announced Spectrum Screener software from Pitney Bowes. The software enables financial services providers of all sizes to enhance their anti-money laundering systems and processes by managing a centralized repository of high quality customer and non-customer (“pseudo”) data. This in turn drives deeper insight into complex webs of obvious and non-obvious relationships, providing an improved first-line defense against suspicious transactions – allowing a community bank to more quickly make the connection that Mr. Jonathan Goldberg of Stamford and Mr. Jon Goldberg of Stanford are one in the same.
Spectrum Screener provides banks with the ability to:
- Automatically identify, resolve, and match entities against federally-monitored lists, such as Politically Exposed Persons (PEP) lists, Do not ship vessels lists, Patriot Act, and those created internally by the institution;
- Significantly increase cost-savings by applying Entity Resolution to reduce false positives and investigative burden;
- Reduce burnout, turnover and training expenses for the investigation teams;
- And improve overall productivity so that these teams can focus on suspicious activities that return a true-positive result.
Regulators continue to tighten their grip on the industry, and financial institutions are increasing their focus on AML solutions. It’s the time to shine for screening solutions – and the smart institutions rolling it out.
Learn more about Pitney Bowes Spectrum Screener today, and visit us online at https://www.pitneybowes.com/us/customer-information-management/industry-solutions/spectrum-screener.html