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Technology can unlock crucial data insights and ease KYC pain points

by Uma
iStock 1313070791

 

 

By: FabriciaBlauwhof, Senior Consultant, Client Experience and Lifecycle Management, Synechron, The Netherlands

 

Know Your Customer (KYC) requirements have dramatically increased the amount of data financial institutions need to manage and assess. Accuracy is also key. But new technologies have the potential to make Anti-Money Laundering (AML) and Counter Terrorism Financing (CTF) measures faster, cheaper and more effective. This is especially true for those technologies that offer cross-cutting benefits and enable new digital ways to succinctly collect, process and analyse data. However, only with well-organiseddata management can Financial Institutions ensure that their data will be used as effectively as possible.

 

Such technologies can helpFinancial Institutions toanalyse large amounts of structured and unstructured data, identifying patterns and trends, much more effectively. By pooling data and using advanced analytics, Financial Institutions can better understand, assess, and mitigate against the effects of money laundering andterrorist financing risks.

 

As part of this, Data Maturity Assessments, can be a crucial tool in understanding how Financial Institutions can improve their own capabilities in using data effectively.

 

Multiple challenges for Financial Institutions and KYC pain points

While institutions are beginning to fully realise the true benefits their data environment could generate, they are also grasping the magnitude of the challenges they are facing.

 

One of the main challenges for Financial Institutions is the management and monitoring of vast quantities of data. Banks feed data from a diverse set of sources into centralised monitoring systems. Generally, global banks obtain customer and transaction data from various systems and different sources. This includes both data from third parties as well as data from the customer. Data from third parties must be identified as complete and up-to-date. Information from the customer must be kept up-to-date as well, especially in an environment of perpetual Know Your Customer (KYC) mandates. Usually, this happens through customer outreach via multiple mails with various attachments, resulting in unstructured data and data fragmentation.

 

Maintaining the quality of data in terms of accuracy, timeliness

and other factors can therefore be quite difficult.

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Data fragmentation is further aggravated by institutions operating across different regions, business divisions or channels, eachoperating with different systems and data. This results from differences in policy requirements within the different regions. To mitigate data fragmentation, further pooling of data is required. Maintaining the quality of data in terms of accuracy, timeliness and other factors can therefore be quite difficult.

 

The legacy of legacy systems and misaligned strategies

Financial Institutions’ systems are often legacy (or heritage) data systems that are more than 15 years old with newer processes implemented on top of them. Thisincreases the complexity of the data landscape. The quality of the data obtained by legacy systems varies and may not offer the accuracy and detail required to comply with AML/CFT standards. When replacing or updating those legacy systems, costs and complexities are involved which makes it challenging to exploit the potential of innovative approaches to AML/CFT.

 

An even bigger problem is often the failure to align data strategy

with the overall organisational strategy.

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An even bigger problem is often the failure to align data strategy with the overall organisational strategy. Ultimately, banks need a more integrated view of relevant data. To accomplish this, they will have to pool data that, in many cases, has been stored and processed independently by, for instance, division or geography. 

Although data integration is likely to be more effective when there is a central repository of customers along with centralised systems, this is generally not the reality in many organisations. Therefore, not having proper governance in place for data can result in insufficient data that lacks quality and is outdated. Without proper data governance in place this can frequently go unnoticed for some time in larger institutions, resulting in additional KYC risks.

A focus on data quality

Data quality is one of the most important considerations, if not the most important, for Financial Institutions in their full suite of KYC processes. However, it is often difficult for institutions to know where – and how – to start addressing the root causes of data quality issues.

 

Financial Institutions should identify critical data within their organisation and assess the maturity of the data management practices within the firm’s KYC process by using a maturity assessment tool.

 

By performing a quick scan within the organisationusinga data maturity assessment tool, Financial Institutions can produce a current picture of the institution’s data management capabilities. In this process, the maturity of the assessed capabilities is established. Since the maturity has five levels ranging from ‘initial’ to ‘optimising’,this step is crucial to identifying where the institution stands on its data management capabilities, and importantly,the areas in which the institution can improve.

Following, the second step is to perform a gap analysis. During this step, all issues are weighted and discussed with stakeholders. By involving all relevant stakeholders, the financial institution decides, together with the experts involved in guiding the analysis, what is most important to them, and where to make improvements. This can result in the development of long-term strategies, as well as quick wins to make data capabilities more mature. A complete plan is developed with a view of helping the institution reach its desired maturity.

After the gap-analysis is completed, a roadmap is drafted detailing how to reach the desired goal within an estimated 4-6 weeks. The roadmap prioritises the most pressing issues, as defined in the gap analysis, for institutions to proactively address, and is tailored to the specific needs and constraints of the institution in question. Once completed, this roadmap enables the institution to mitigate against the issues and start improving the data maturity of the capabilities.

By using maturity assessment tools, Financial Institutions can map out how they can improve their capabilities in using data. Understanding their own data maturity can help Financial Institutions identify important data governance processes, helping them consider their own business strategy and objectives. 

Given the challenges around Know Your Customer mandates, and management and monitoring of vast quantities of data, Data Maturity Assessments are crucial for helping Financial Institutions map out the steps that they need to ensure data is well-managed and well-controlled, whilst also being well-governed and secure.

 

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