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RegTech and client onboarding– Striving for “frictionless onboarding”

[fa icon="calendar"] 06-Jun-2017 19:40:16 / by Philip Creed

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‘Frictionless onboarding’ is a term that seems to be cropping up more and more within the FinTech community. In an increasingly competitive, digital environment, creating a simple client onboarding process, while complying with regulatory pressures, can be the difference between success and failure. But is it even possible to be truly frictionless? What role does technology play? And what are the key considerations to be made before committing to your product roadmap.

To try to prevent Money laundering the regulations state you need to

  • identify;
  • risk assess; and then
  • monitor your client

However, to do this when you have 10’s of thousands of clients is unachievable and unrealistic without technology.

Identification

So, if we take each area of this lifecycle how can RegTech help? For identification, the UK has always pioneered the way in terms of electronic identification, this as per the Joint Money Laundering Steering Group (JMLSG) is suitable. Once we push beyond the UK the quality of data diminishes dramatically so with FINTECH companies pushing globally what is the answer?

At government level, internationally,  more countries are following the UK’s lead and opening up their data out, most notably, with the implementation of the 4th Money Laundering Directive (4MLD) in the EU. However this is a long term strategy and is unlikely to ever be fully implemented around the world.

In the short term we must  find other ways of solving this issue. And this is where technology plays a crucial role. Many companies have endeavoured to solve the challenge of onboarding with technology. Indeed an entire branch of RegTech is dedicated to it. One such example is the huge focus on Biometrics, such as Facial recognition  - a method matching a person’s identification document to their actual face. While this technology is not perfect by any means and when you have different people, with multiple ethnic backgrounds the match rates reduce massively, it is getting better every day and is certainly an area to keep an eye on.

In short, even with the leaps we are making in technology, the identification of clients still offers up significant challenges to becoming truly frictionless.

Risk Assessment

Now let’s look at the risk assessment of clients.

I have seen in my role as compliance consultant the difficulties risk assessment represents for FinTech companies. FinTechs  are under extreme pressure to grow their user base making the temptation to accept all customers that sign up is very high. This coupled with the actual practical difficulty of risk assessing your customers, whose numbers potentially range in the tens of thousands makes it a high-risk area for firms and an area which is prime for RegTech.

For payments firms the margins made on a per payment basis can be low, As such investing in systems which allow you to risk assess your client base effectively is not widespread. Additionally, private individuals are notoriously difficult to risk assess. Why? Because even though it would supply more significant information on your client, credit checks are not compulsory and this data is expensive to obtain. Therefore, generally on most occasions you are relying on self-proclaimed statements from the customer. For example, the company might ask how much the prospective client intends to  trade through them. For argument’s sake let’s say it’s £10,000. In most company’s risk assessment, this will not flag, even though £10,000 in spare cash is a lot to the vast majority of individuals in the UK.

So again, how can RegTech help? The big data approach has resulted in an enormous amount of data everywhere. The issue with this is it is difficult to get implicit meaning. We are seeing greater Investment in RegTech  to help develop tools to assist financial institutions  get true meaning out of data, helping them focus on their core activities.

Social media is an area where data is exponential and an area where data can be used to implicit risk on private individuals. Recently, I met a company using social media solely for identification in emerging economies, as many people did not own photo ID. I would describe it as crowdfunding for identification. Is this viable in Western economies? No, but to “know your customer”, certainly, understanding their social media, for example using LinkedIn to get their job information and comparing that to salary data, can allow you to build a risk profile for your client which is far more specific to their circumstances.

Monitor your client

Having identified and risk assessed (or got to know)your client, transaction monitoring for anti-money laundering (AML) is the game changer. If you are going to catch money launderer, that’s where you are likely to do it. All the identification and risk assessment, even cleverly completed can be manipulated by a money launderer, if they know what they are doing.

However, once the launderer wants to transact, they need to get their money out the other side. Being able to monitor these transactions will significantly increase your chances of catching them. Again,  we have seen significant strides in the use of RegTech to effectively monitor client transactions.  Historically Transaction Monitoring systems were based on a series of hard coded rules with no flexibility. However, the use of Big Data from reputable sources, married with machine learning and clever alerts, is allowing RegTech firms to fundamentally change the way in which money laundering is detected, thus revolutionising the way we approach AML.

In conclusion, is frictionless onboarding possible? Fundamentally and theoretically yes. Will it ever be totally frictionless? No.

Why? Because trying to fit multiple countries and cultures under a single open data concept, in my opinion, will just not be accepted as an idea. As an extreme example on delay, it took the USA 10 years to accept chip and pin as a method of payment, after it was already commonplace in Europe.

So, as a FinTech you should not be searching for perfect, but trying to figure out what your version of perfect looks like in compliance with the regulations with your bespoke situation. Focusing on this will allow you to make the best of the resources you have both from a technology and personnel standpoint.

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Topics: 4MLD, FINTECH

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