How data management can help financial institutions gain crucial insights

The importance of gaining insights from data

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 analyze data. However, only with well-organized data management can Financial Institutions ensure that their data will be used as effectively as possible.

Such technologies can help Financial Institutions to analyze 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 and terrorist financing risks.

As part of this, Data Maturity Assessments, conducted by a reputable consultant in the financial services industry, 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 realize 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 centralized 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.


Data fragmentation is further aggravated by institutions operating across different regions, business divisions or channels, each operating 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. This increases 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 organizational strategy.


An even bigger problem is often the failure to align data strategy with the overall organizational 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 centralized systems, this is generally not the reality in many organizations. 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.

Based on our experience in the financial service domain, Synechron has merged its industry expertise with best practices (such as DAMA, or Data Management Association International, and Cobit) to develop a Data Maturity Assessment tool. With this assessment, Synechron can provide organizations with insights into the maturity of their data management practices and then create a roadmap that outlines how to most efficiently improve their data management practices and the data quality within the organization. This assessment speeds time-to-market and can generally be performed in six to eight weeks.

DAMA defined 11 capabilities within Data Management which are all necessary parts for a mature data management function. However, there is also value in adopting a modular approach, targeting only the most relevant capabilities established during an intake session with the client. An assessment should produce the following deliverables:

  • As-is picture of the data management organizational maturity (with focus on impacted business and IT units)
  • Gap-analysis where all issues are weighted with all relevant stakeholders
  • Roadmap with prioritized activities to reach the desired maturity level for each Data Management capability in order to improve data quality

The Cobit Maturity Model will form the basis of our assessment. The model is defined upon five levels, from ‘initial’ to ‘optimizing’, each one of which describes a possible maturity stage. It provides a picture to understand and measure the current stage, plan for the target stage and indicates the steps to get there. See Figure 1. for an overview of high-level results of the Synechron Data Maturity Assessment.

Figure 1: High-level results of the Synechron Data Maturity Assessment

How to address Data Management objectives  

There are a series of steps that Financial Institutions can take to benefit from maturity assessment tools, which will help them address key KYC data challenges.

Firstly, Financial Institutions should identify critical data within their organization 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 organization using a 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 ‘optimizing’, 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 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 understand identify important data governance processes, helping them consider their own business strategy and objectives. Within Financial Institutions’ unique KYC and data management systems, and in partnership with the client, Data Maturity Assessments such as Synechron’s can help to identify the critical data capabilities so improvements can be made.

Given the challenges around Know Your Customer (KYC) 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.

Authored by: Fabricia Blauwhof, Senior Consultant, Client Experience and Lifecycle Management, Synechron, The Netherlands

Disclaimer: The views expressed in this article are those of the author and do not necessarily reflect the views of ET Edge Insights, its management, or its members

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