A steep financial burden that proceeds to grow steeper.

The sum of money that FIs of all shapes and sizes are investing in KYC and customer due diligence continues to skyrocket year after year, with around 10 percent of the world’s major financial institutions spending upwards of $100 million annually (and many exceeding $500 million in annual KYC related spending). Sorry to say this trend shows no signs of slowing: in 2017 the figure was increased by over 5.4 & and in 2018, KYC spending increased an estimated 18.3 percent (source: Thomson Reuters).

This figure doesn’t even consider the manpower costs associated with dedicating a lot of time and energy to due diligence: over half of all banking account executives estimate that they spend a minimum of a day and a half of each week conducting onboarding; time that can be more productively invested in other tasks.

The Problem.

Under pressure from regulators, the FIs needed a strategy to support different internal groups’ needs and integrate seamlessly with current transaction monitoring and case management systems.

With multiple business lines and hundreds of thousands of new accounts annually, any regional (let alone international) bank necessitates a high number of full time employees (FTEs) and temporary staff to handle the amount of work involved with account risk screening. They often also perform ongoing monitoring for over millions of portfolios, a process producing high false positive rates and a slow decision process.

The problem with most KYC solutions is that the risk scoring process is unchanging: once an initial risk score has been determined, it’s rarely updated. But clients aren’t leading static lives, and their information is routinely changing.

FIs needs to find a solution that enables them to monitor this information and dynamically administer it to their risk scoring system.

Not only that but the long, complex journey to expose ultimate beneficial ownership might be time consuming and arduous. According to a number of recent surveys of wealth managers and financial institutions, among one of the most significant challenges of today’s KYC landscape is trying to identify ultimate beneficial ownership.

Additionally, having to keep an updated track record of all controlling persons, particularly when they’re bound to change at any given time combined with the registering authority having flawed checks and balances; is an ongoing struggle. Keeping tabs on all key stakeholders is a tedious task, and one that requires exceptional diligence, and also astute detective skills.

Despite continuous investment, onboarding times are still rising and refreshing data can be a nightmare.

Issues are;

  • FIs claim that usually it takes 26 days to onboard a new client, up from 24 days in the same 2016 survey. However, corporate customers claim that on average it takes 32 days.
  • FIs expect onboarding times to rise again by 12% in 2018. Their corporate customers, however, are more distrustful, expecting onboarding times to increase by 24% in the next year.
  • Banks say they got in touch with their clients usually four times during the onboarding process, but their corporate customers report that they were spoken to on eight occasions.
  • Refreshing data takes on average 20 days and three customer contacts.
  • Around a third of corporate customers don’t inform their FIs of material changes.

The Solutions Future.

The ideal solution provides the ability to screen and continually monitor all customers and transactors more efficiently against the broadest database of sanctions, PEPs and Adverse Media.

To apply a risk-based approach, countries, and FIs must take appropriate steps to identify and assess the risks of money laundering and terrorist financing for different market segments, intermediaries, and products on an ongoing basis. In line with the concept of a risk-based approach is acknowledgement that the nature and extent of AML/CFT controls will depend upon a variety of factors. The FATF, a global financial organisation that sets standards connected to AML/CFT procedures, recognises the following factors as determinants of the proper extent of AML/CFT controls:

  • The nature, scale and complexity of a financial institution’s business.
  • The diversity of a financial institution ‟s operations, including geographical diversity.
  • The financial institution’s customer, product and activity profile.
  • The distribution channels used. The volume and size of the transactions.
  • The degree of risk associated with each area of the financial institution’s operation.
  • The extent to which the financial institution is dealing directly with the customer or is dealing through intermediaries, third parties, correspondents, or non face to face access.

Key to success is the ability to streamline onboarding with decision-ready, dynamic due diligence reports and enhance protection with ongoing monitoring of the clients’ portfolios for material changes. With this the compliance workflow process should be demonstrably simplified with end-to-end technology, quickly and easily configurable to the clients’ needs.

Artificial Intelligence, Machine Learning and Data Mining.

Because money laundering and terrorism financing tactics are continually emerging, regulators and FIs are constantly having to update their methods for fighting financial crimes. But with advancements in machine learning, KYC technologies and systems are increasingly able to recognise sequences and make observations autonomously, ultimately enhancing their abilities to make predictions about customer behaviours and risk levels. AI could ultimately revolutionise KYC and CDD processes, taking an enormous burden off the shoulders of FI employees.

Author: Lee Werrell Chartered FCSI – Compliance Consultant

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