We’ve come a long way in the last 20 years in terms of identity matching. As discussed in previous articles in this series, when electronic identity matching first took off in the 90s, machines only had a few hundred names to deal with. Now, the numbers are infinitely larger and the stakes are dramatically higher too. But, the capabilities and processing power are there and machines are able to crunch the data in milliseconds.
As the numbers grow, the challenges keep growing too. They have grown in size and complexity for a number of reasons. Now that the initial data-crunching process is largely in hand, the focus is switching to these complexities.
There are three main areas that are of concern to financial institutions in the coming years and they are:
- The operational cost of compliance
- The volatility of the sanctions environment
- The complexity of geographical sanctions
These are all big issues that need to be addressed, so this is where the innovations need to happen. But, financial institutions have to be careful to balance the need to keep costs down with the need to comply with regulations and meet sanctions requirements. Those that fall foul of regulatory demands and breach sanctions run a very real risk of incurring penalties. Recent examples of multi-billion fines show how seriously regulators take sanction breaches.
So, the focus for financial institutions has to be a three pronged approach: how to reduce their operational costs of compliance, while at the same time navigating the challenges of a constantly changing sanctions environment and meeting regulatory requirements.
What next? In next week’s post we look at how organisations can address the first issue: reducing the costs of compliance through automating the decision making process even further. It’s all about enabling robots to make decisions on alerts, freeing humans up to tackle the complicated cases.
Also in our series on identity matching