One of the most pressing problems in international banking, from the perspective of financial institutions located in the developing world, is Derisking. The ongoing cancellation and termination of vitally important correspondent banking relationships in North America and Europe held by banks in the Caribbean and elsewhere abroad, due to decisions made onshore pursuant to risk-based compliance programs, directly threatens the actual existence of banks whose customers depend on access to the mainstream financial structure of the developed countries, for international trade and commerce.
Without direct access to American and European banks, the purchase of imported goods through access to the Dollar, Pound and Euro for trade becomes not only more expensive, it approaches the point where the cost is prohibitive. Imagine how you would feel, as an importer abroad, or any individual or company with financial intercourse with firms in the United States or the United Kingdom, if you could not do business? You would certainly desert your local bank in an instant, for a nearby branch of a New York or London bank in our jurisdiction. The result might be that your local bank, being unable to compete, would fail.
While we totally understand the reasons behind Derisking, ultimately it is bad for business. Local markets abroad can be negatively affected if the increased costs of indirect access to the onshore financial structure make goods too expensive for consumers in a market-driven economy. Clearly, something has to be done, before banks in the Caribbean and elsewhere lose all their correspondent relationships, as appears to be a distinct possibility in the not too distant future.
Enter AML/CFT compliance programs employing Artificial Intelligence and machine learning; banks abroad can employ such platforms, which will elevate the effectiveness of their abilities to interdict money laundering and financial crime to the point that there is sufficient assurance that those wire transfers from banks in dodgy jurisdictions can be declared safe by the world's major banks, which operate in a risk-based environment, and demand that their respondent banks do the same.
Adopting compliance systems in those banks in the developing world that use AI and machine learning to identify, and interdict, on a real-time basis, financial crime, can supply sufficient protection to satisfy even the most demanding compliance department of a major international bank, as such a platform will not only be able to catch the money launderers, its evolving nature will uncover and discover any and all countermeasures devised by the laundrymen seeking to find flaws and opportunities, because machine learning will match their moves, and unmask them, and their transactions.
When banks in New York or London need no longer worry about the quality of compliance in banks abroad in high-risk jurisdictions, Derisking will become a thing of the past. It is high time that bank executives that have been watching all their vital correspondent relationships in New York evaporate get on board with platforms that are powered by AI, and employ machine learning, to ferret out potential financial crime, so that they can keep those correspondent accounts operating, without fear that they will be terminated.