Getting the whole picture

AI cybersecurity dataprivacy fintech machine learning
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As a necessary matter of compliance, banks routinely risk-score their customers to ensure they comply with their pre-defined risk-appetite. Whether during onboarding or through monitoring customers and transactions, every entity is screened by the major financial crime divisions, usually broken down into: Know Your Customer (KYC), Anti-Money Laundering / Counter-Terrorism Financing (AML/CTF), Sanctions, Fraud, and Transaction and Customer Monitoring.

However, most of these entity reviews operate in business silos, with each assessment generally taking place across different systems, executed by disparate policies and processes, with a lack of centralized customer data to provide a holistic view of a customer.

By being assessed separately, different risk-scores or versions of the same entity can exist and cause complications for the bank. For example, a customer with a business loan could have been identified as a Politically Exposed Person (PEP) but their business account rates them as a low risk customer.

This can lead to customer fragmentation, data duplication or multiple records of a single entity. As a result, many financial crime departments in banks lack efficiency and have not leveraged the technological potential to create an enterprise-wide, single customer view.

Entity Resolution / Single Customer View

Entity resolution (ER) is the white knight of financial crime risk management. ER can untangle the digital web of complex customer data to create a holistic, real-time view of their customers and the networks they interact with. Stitching together the data from different internal systems and augmenting it with external data will modernise the ability for banks to fight financial crime. Artificial Intelligence can further be used to improve analysis of a customer’s risk, being able to better explain certain behaviors or relationships hidden in the data.

ER also brings the promise of enhanced analytical capability by combining disjointed data systems. A consolidated customer profile will mean a superior monitoring capacity, more robust customer due diligence, automated reporting, streamlined processes, increased traceability and better data lineage. Perhaps most significantly, the ability to perform enterprise-wide case management will be a giant leap forward in conducting financial crime investigations. The benefits don’t just stop at the operational level but using data to create a single customer view can help enhance a bank’s reputation for security, improve customer retention and, crucially, transform a bank’s ability to fight financial crime.

Implementing the Technology

Banks often have the right intentions, driven by motivated people, but, as soon as the costs and complexities start adding up, they can choose an easier path. Implementation of entity resolution will require heavy investment in technology and security; uplifting of policy, procedures and governance; and most likely a structural re-organization to integrate all financial crime risk management portfolios under a synthesized framework. Yes, this is a lot to chew, but the dividends are significant and will be a bank’s best bet at providing customer and institutional security in the future. To borrow shamelessly from Nelson Mandela, it always seems impossible until it is done.

Fortunately, in many cases the necessary data to complete a single customer view already exists. The challenge, however, lies in bridging the vast volume and velocity of data and putting it in a format that can be read across different systems. There are three main data initiatives that banks can take to make the step towards entity resolution:

  • Removing duplicates of repeated data
  • Finding records that reference the same customer or entity in different systems and linking them
  • Standardizing the form of data that had previously been represented in multiple forms, also known as “canonicalization”

Other global players are already further ahead than the UK in this regard. The Social Security system in the US provides each citizen with a unique ID number that records an individual’s income or wages, which can be used by financial institutions to check their credit score or other require information about an entity. Across Europe, Norway’s BankID and Iceland’s Kennitala system give citizens a single numerical identifier that provides each person with access to every bank and public agency, and the relevant administration authorities with a centralized repository of customer records. In China the large technology and financial services players, such as Ant Financial, are consolidating the huge mass of customer data at their fingertips to create a visual network view of all of a customer’s interactions – both financially and socially.  

UK institutions still have a lot of room to grow. According to a poll of 90 FIs by NICE Actimize, a leading provider of unified customer views, over 50% of banks with at least US$60billion in assets have over 10 detection systems, and a further 31% have over 20.

There are more efficient ways to perform necessary anti-financial crime checks. Assigning a single number or unique identifier to all of the data associated with one entity across a network is a good starting point. Moreover, it is worth noting that the World Bank advocates that having a Unique Identified Number (UIN) through civil registrations systems is critical to achieving the UN Sustainable Development Goals (Target 16.9).

The Multiple Uses of a Single Customer View

Aside from financial crime, the use cases for entity resolution are immense. From optimized marketing, to resource management, to specialized services, knowing the context of your customers can only serve to improve your personalized business offerings. Predictive analytics can be much more targeted with a better understanding of individualized customer needs.

A holistic customer risk rating through a single customer view may not be the norm yet, but as the culture of compliance develops and deepens in banks, this is undoubtedly a necessary goal.

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