Artificial intelligence and big data to prevent money laundering and trade finance fraud

Artificial Intelligence (AI) applications and big data solutions are becoming increasingly prevalent in efforts to prevent money laundering and fraud in trade finance.

Major information providers are developing increasingly sophisticated solutions for banks while smaller providers are designing products specifically for the trade finance market.

Big data

Providers of AI and big data providers are seeking to fill the gap left by basic solutions that scan documents for blacklisted keywords, but fail to account for context.

AI and big data solutions can make filtering more effective. Thomson Reuters’ World-Check for example employs technologies to build profiles and identify high-risk entities before they are officially blacklisted.

Monitoring solution

World-Check risk intelligence provides the know your customer (KYC) and third-party risk screening needs of some the world’s largest banks and financial institutions, corporations, law enforcement, and government and intelligence agencies.

The solution monitors over 530 sanctions watch, regulatory, and law enforcement lists along with hundreds of thousands of information sources, and claims to identify high risk entities months or years before they are listed.

More is needed

But this is not enough according to Tapan Agarwal, product council head at iGTB, a company that markets AI due diligence software called DDIQ.

“Banks are failing to identify threats and fraudulent activities by relying solely on curated databases,” says Agarwal.

Deep search

DDIQ can search deep through the web to find material on the parties involved in a transaction or a letter of credit.

The product uses AI and natural language processing to comprehensively search the web to profile an individual, a small- or medium-sized business or a large corporate involved in a transaction.

According to Agarwal, deploying AI solutions can significantly reduce crime in trade finance and may be particularly effective in raising red flags when, for example, the stated cost of a commodity per unit does not match the actual invoice value.



Categories: Trade Based Financial crimes News