Learn more about the benefits of big data - from keeping up with compliance standards & increasing customer satisfaction to revenue increase.
Access to finance has always played an important role in driving the efficiency and growth of the economy. Nowadays it is easier for individuals and enterprises to obtain financial services, thus accelerating economic prosperity in both developed and developing countries.
But while these countries are constantly improving their strategies for encouraging investment, creating sound economic plans and strengthening relationships with financial institutions, the financial industry is facing its own challenges. How to properly assess risks in client on-boarding and really ‘know-your-customer’ (KYC)? How to comply with more and more stringent Anti Money Laundering (AML) regulations across different jurisdictions? And, most importantly, how to avoid reputational fallout?
While today’s financial institutions are much safer from dangers such as the wild gangs of the 1800s in America, the ever-changing regulatory environment poses other challenges. Essentially, non-compliance or inefficient customer due diligence (CDD) lead to serious reputational damage.
Case in point: the money laundering scandal at Danske Bank that erupted in 2018 and tarnished the reputation of Scandinavian banks.
Danske Bank has “gone from being one of Europe’s most respected financial institutions to getting caught red-handed in one of the world’s biggest money-laundering scandals,” Richard Milne and Daniel Winter wrote for the Financial Times about the scandal in December 2018.
According to EY, financial crime around the world – including money laundering, tax fraud, corruption and terrorism funding – is estimated to cost between $1.4 trillion and $3.5 trillion every year. There is around $2 trillion worth of illegal funds in circulation in the global financial system, Dai Bedford, EY Global Banking & Capital Markets Advisory Leader, wrote in an article in January 2019.
Financial institutions are pouring more and more resources into the KYC process in order to avoid getting inadvertently involved in financial crime or other fraudulent activities. Their task is complicated by the rapidly growing data and information as well as numerous news articles and publications about people and organizations. Now, these institutions need to spend more and more time and resources in background checks, figuring out if their potential clients are law-abiding citizens and businesses or not.
As part of the KYC process, banks monitor media articles to check if the ultimate beneficial owner (UBO) they have identified – regardless if a person or an organization – is mentioned in the news in a negative way. For example, whether they have been linked to any crimes in the past or if they are related to a person who is known to have been involved in financial fraud.
In order to establish that, bank analysts sift manually through hundreds of negative news articles every day. To complicate things further, these articles often refer to a company with the same or similar name to the UBO of interest. Or they mention the correct UBO but the negative event they speak about concerns other parties.
This is where semantic technology can offer an advanced solution and help financial institutions perform efficient and cost-effective media monitoring as part of their KYC processes.
By disambiguating between people, places and organizations with same or similar names, semantic technology facilitates the process of filtering out irrelevant mentions and false positives. This does not only speed up the overall analysis of negative news but also significantly improves its quality.
Ontotext has developed a smart media analysis solution based on knowledge graphs that combine banks’ proprietary data with public resources such as OpenCorporates and CrunchBase. The solution provides a fully automated workflow for negative news monitoring: from loading content exports from the news dumps, through filtering out irrelevant news and ranking the rest by relevance and confidence score, to highlighting specific line items with relevant content for a quicker review.
Check out our case study to see how and why we developed our smart media analysis solution or discuss your particular use case with us.