Maintaining up-to-date customer due diligence information is a legal requirement for regulated entities and involves at its core, verifying a customer's identity and all business areas they are involved in, before being able to provide financial products or services.
The challenge for financial crime operational teams is that to satisfy this requirement, significant amounts of data should be gathered at regular intervals from multiple sources, consolidated, and then validated to be able to create a full picture of the customer. This data could be found within banking platforms, public sources, regulatory sites, third-party data aggregators and screening tools or, in many cases, directly from customers.
I find that this continues to pose several challenges from a time, cost and customer experience perspective, but predominantly in aiming to ensure that the data collected is trustworthy, relevant to your business and up-to-date. The penalties for getting it wrong can be significant, so if your information isn't as robust as it should be, then how can you find better ways to source it?
Using data for a 360 view of the customer
In my experience of over a decade of running client customer due diligence operations, one of the key challenges I still come up against is the ability to gain a clear understanding of the customer. One of the major headaches for many of my clients is the fact that data is stored across multiple systems, and they might be using multiple CRM systems and banking platforms, making it almost impossible to bring together the right information to review, whilst also identifying and responding to changes in customer behaviors. Increasingly my clients are looking to connect legacy systems together; integrating sales and administration systems with CDD platforms, to bring in existing customer data, striving to reduce unnecessary outreach and give a fuller picture of customer activity.
I believe that where direct outreach is required, aiming to ensure that the process and approach taken is accurate and effective should be a key area of focus for financial service providers. Unclear requests and/or requesting documents that have already been provided leads to inefficiency through repeated activity, responses that don't satisfy requirements and frustrated customers - all of which elongates the outreach process.
Where firms can digitize policy to pinpoint clear requirements and then provide multi-channel communication options, implement robust chaser cycles and engage with relationship managers upfront to inform and support their customers, they can drive a much better response rate. Customers will likely feel more engaged and better informed of what's being asked of them and a reduced number of outreach interactions can help improve overall case handling times.
Additionally, investing in robust data analytics is helping firms move from reactive customer due diligence to proactive customer insight by using customer data to identify trends and uncover links between businesses. This data driven insight looks across several categories including payments, risk rating, industry and country of incorporation to help inform on things like customer turnover versus economic value and high growth customers. From a financial crime perspective, it's possible to use analytics to identify common key parties, payment loops and money flows that wouldn't otherwise be visible, linking multiple common addresses and identifying the movement of money between UBOs. By leveraging this type of data, banks can gain greater insight into developing criminal trends whilst at the same time helping to reduce manual effort, which can ultimately driving cost efficiency.
How can you reduce manual, repeatable tasks through the 'datafication' of CDD processes
In my opinion, CDD data doesn't just have to be limited to the details of the entities and individuals being reviewed but can be incredibly useful from an operational perspective. By taking policy and risk models and quantifying them into a dataset of their own, with rule-based conditions, actions and types of acceptable documents, you can automate the generation of relevant regulatory requirements, which can increase quality outcomes and driving operational efficiency.
In the operations that my team run at KPMG in the UK, while the actual assessment of acceptability remains a human endeavor, the team can take away the manual elements of the CDD process through automation, focusing people on the subjective elements requiring human review. For example, why spend time assessing whether the type of document the customer has provided is acceptable against a policy document, when that 'acceptability data' can be automatically retrieved and presented to you alongside the document from a quantified policy? Why not go even further and detect the type of document provided, and offer an automated assessment of acceptability requiring only a rapid human validation to confirm?
To see how KPMG firms can support you with enhancing your data in the fight against financial crime, please view our report on Insights into successful CDD execution: Smart data and technology.
Read additional blogs in our Financial Crime series.
