Developments and advances in innovative technology provide wealth-management firms with new ways of dealing with old problems when it comes to anti-money-laundering and know-your-customer processes.
These developments, along with the emergence of managed services (the practice of outsourcing the responsibility for maintaining, and anticipating the need for, a range of processes and functions), now provide credible options for firms to consider when they try to balance money-laundering and KYC control with the urge to make their operations more effective, their approach to risk and the experiences of their clients on the whole.
The 'onboarding' of large volumes of customers is normal in the retail sector. One might think that this lends itself to automated processes nicely, but actually there is a low level of automation (less than 40% in some cases) in that area. This causes long "exception management" queues, long lead-in times and bad experiences for customers.
One common problem is private banks' (in)ability to gather enough information about potential clients, which results in plenty of "false positives" (results that indicate falsehoods) and "exceptions" (anomalies). As a result, KYC operations have to sift through and clear large volumes of invalid anomalies.
Automation that harvests data more effectively from internal, public and external sources is at hand. It uses automated artificial intelligence (AI) and deploys "knowledge graph-based entity resolution." The capture of more extensive and accurate data at the point of onboarding allows a bank to gauge risks more effectively.
As a result of such IT, banks are improving their STP (straight-through processing) by more than 40%; some of them operate at 90%+ STP, while not lowering their appetites for risk.
Some retail customers find the 'onboarding' process harrowing. The recent pandemic, which has forced branches to close and has made staff less available for work, has only made matters wose. Compared with other industries, the level of "digital penetration" in the KYC/AML field remains low.
Furthermore, more and more prospective HNW customers are demanding a fast and simple but secure onboarding process, ideally without the need to visit branches in person. This gives digitally capable firms a significant advantage.
Added to this, most wealth-management firms have old systems and processes and it can be costly and timely to make any changes to these in order to afford the customer a better experience.
However, financial institutions are now embracing the innovative technology that is being used in other industries and adapting it for AML and KYC-related purposes. Digital onboarding processes now use optical character recognition (OCR) to read passports and identity cards, face recognition software and "liveness detection." An HNW 'prospect' can use his smartphone during the onboarding process by merely clicking through a series of textual links with no need to download any software. This easy and straightforward automated workflow reduces the time for onboarding down to minutes, reducing human error and making the whole process conform very closely to regualtory rules.
The regulators have supported these advances. The UK's Financial Conduct Authority has provided guidelines to govern the ways in which financial institutions can take advantage of this technology by performing digital authentication, accepting scanned documents and using 'selfie' match photos to verify identities.
This is an area where we have seen the greatest advancements. Many firms now subject their existing clients to continual screening and monitoring processes and they can assess risks even more effectively with new technology.
A good example is software that can ‘refresh’ a group of clients quickly, looking at their characteristics and measuring them up to updates in the firm's risk policy. The benefits are two-fold: the software spots highly risky clients whom the firm previously classified as 'low risk' (their situation might have changed since onboarding). Conversely, it might classify highly risky clients as 'low risk.'
Not only do firms now have the capacity to monitor clients' risk ratings continuously; they are now extending it to perform near-real-time KYC or ‘KYC Live.’ Software can now automatically detect changes in data by looking at internal and external data sources, taking stock of policy rules, 'trigger events' and published alerts. This process benefits from extensive in-built rules engines with customisable rules that deal with those 'trigger events' and perhaps patterns.
As summer unfolds and travel is at the forefront of our minds, we can take some pointers from the airline industry as we consider the role of AML/KYC managed services.
Thirty years ago, the airline industry was owned and operated by the airlines themselves, which performed such inessential functions as the processing of tickets, the handling of luggage, ground services and catering. This was a largely ineffective way of doing things because it limited operational efficiency, stopped people from managing risks and deterred investment. However, these airlines transformed themselves by developing standardised services and using specialists to provide them with goods and services. As a result, they were able to concentrate on other business.
We see a similar trend now emerging in financial institutions with complex, essential tasks being performed by specialists. Firms are always going to make their own decisions about risks and their appetites for risk, but the complex work for KYC and AML operations can be handled better by businesses that specialise in managed services.
More and more financial institutions are going to want to hire specialist KYC & AML firms to do peripheral jobs - firms which are working with many financial institutions at the same time, which know about regulation and which have the best software to do the job. This is going to reduce costs and remove many burdens from the shoulders of senior managers at banks.
* Gary McClure can be reached on +44 203 890 4803 or at firstname.lastname@example.org