By Dhanum Nursigadoo
No news is good news. We’ve probably all said this at one time or another.
Except whenever we say “no news is good news”, what we really mean is that until we have been told something bad, there is no need to worry about it. But in a world of increasing regulation, financial institutions aren’t able to be so relaxed — especially when it comes to being protected against financial crime.
This is why financial institutions have increasingly incorporated adverse media searches – essentially looking for bad news – in compliance practices. All major regulatory advisory bodies now recommend adverse media screening as a must have; and with an incipient financial crisis, the chances of more regulatory changes are incredibly likely.
A negative media profile could highlight any potential involvement in money laundering, fraud or terrorism funding. Having this information will aid any institution in their investigations, and flag any customers that are hiding their high-risk histories. But how can you take action if the news you’re getting is not a full and accurate picture?
The media landscape has changed, and the tools to analyse media coverage have to change with it. There was a time when this analysis would have been conducted by picking up the national newspapers and having a quick flick-through in the morning. No one would think this was an effective or resilient practice now, especially as so much news has now moved to the vast online space.
And yet companies are still relying on ‘keyword’ searches that are no longer fit for purpose, which drastically increases the workload for analysts.
You’ve also got to rely on the fact you hope the journalist who potentially wrote an article about a prospective client and their alleged fraud, well, used that exact word ‘fraud’ and not any permutation such as ‘fraudulent’ or ‘defrauded’ or even common journalistic derivatives such as ‘cheating’, ‘swindling’, ‘trickery’ or ‘duplicity’. The list is endless, but a financial institution’s time is not.
Financial institutions are now beginning to understand the importance of artificial intelligence, and using tools that utilize machine learning that doesn’t suffer from the limited scope of keyword searches.
With AI, it is now possible to collect a greater breadth of articles, blogs and broadcast media from all over the world. Crucially these results are more accurate in flagging up the results that matter most so analysts can get straight to the facts. This is more time efficient for companies who can now spend more time on their results, meeting the financial risk appetite of their companies (and the regulators), while also making sure that customers still receive a timely response.
Imagine that intern who used to get sent out to pick up the national papers in the pre-internet days, but now they spoke hundreds of languages, visited newspaper shops across continents, and could compile it into a report on the relevant potential customer you’re investigating all before anyone else had even arrived at the office. This is what machine learning is offering companies – the ability to forcefully protect them from facilitating financial crime with investigatory power far beyond the average analyst and their generic keyword searches.
And now this is not just a luxury for financial institutions who want to go above and beyond. There is an increasing level of regulation, compliance, and of course, expectation that institutions need to carry out proper risk assessments for any potential customer – and a simple search on Google may not protect businesses if there are any legal ramifications in the future.
AI can prove once and for all: no news is good news.
