Data silos are common throughout the financial world but they're holding compliance teams back.

December 9, 2022 1 minute read

How to break through data silos with automated transaction monitoring

Data silos are common throughout the financial world but they're holding compliance teams back.
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A data silo is a collection of data that’s either inaccessible or difficult to access by other groups within an organization. This is a real problem when handling compliance. Customer data, including identifiable and contextual data, can easily become separated from the transaction data that compliance officers review every day.

Data silos are becoming increasingly problematic as data begins to proliferate and transform every organizational process, making it more difficult for teams to carry out critical functions.

Siloed data is stored in a standalone or isolated system often because it’s incompatible with other datasets. Although the intentions of storing data in this way usually aren’t malicious, it does make it harder for it to be leveraged for the organization’s benefit.

Why are data silos bad for compliance?

Although they may sound harmless, data silos hinder operations and the data analytics processes that support them. Not only do they limit the ability of leaders to use data to manage operations and make informed decisions, but they also prevent operational workers such as compliance officers from accessing relevant information easily that could help them meet their objectives more efficiently.

This is commonly seen when investigating flagged transactions and trying to match customer activity with customer identifiable information obtained during the Know Your Customer (KYC) process. Often this set of data is separated from transactions requiring compliance officers to switch between multiple screens and even multiple platforms to obtain the contextual information they need to make a judgement.

In short, siloed data is unhealthy data. If it cannot easily be accessed and used in a timely manner, it cannot be trusted when it’s eventually released, it isn’t adding any value to operational processes, and it makes data governance more difficult or in some cases impossible—this is something you must be on top of now, at a time when regulatory bodies are introducing new data governance laws and severe penalties for noncompliance.

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Leveraging data for operational development

You may well have read the above and think, “This doesn’t really apply to us because…”, but good data governance and management applies to everyone. It doesn’t matter if you’re an established industry leader or an emerging start-up, businesses today are collecting huge volumes of data at incredibly high speeds.

This is in many ways a double-edged sword. Being in control of data means that you’re legally bound to regulations and standards that govern its collection, use, storage, disclosure, and disposal. Handling this can be a huge burden for leaders, particularly those at the helm of organizations that are data-rich or have limited resources. At the same time, having access to data provides businesses with whole new perspectives, insights, and ways to innovate and scale.

As an example, data analysis can be combined with machine learning to enable businesses to identify certain patterns. This information can then be used alongside market insights, statistics, and historic customer activity to optimize business processes, build personalized brand messaging, accurately evaluate customer value, and protect both your customers and the wider business.

Breaking down data silos for better compliance results

Breaking down data silos begins with knowing the factors that contribute to them and assessing whether any of them resonate with your existing organizational processes. Some of the biggest factors include:

  • Organizational culture — Employees might refrain from sharing data for a variety of culture-related reasons. For instance, they might not understand the rules surrounding data sharing or may choose to keep hold of certain valuable information if teams are over-competitive and don’t communicate. By embedding useable data in the compliance workflow these problems will cease to be an issue.
  • Organizational structure — Silos are particularly problematic for larger organizations that have multiple layers of leadership and teams, or where employees have responsibilities within multiple departments. Intricate structures will lead to siloed data unless processes are in place to encourage data sharing. This can also lead to ingrained frustration in compliance teams as often the first or second line of defence will flag transactions for further investigation or with a recommendation for a SAR to be filed and never receive feedback.
  • Underfunding — Data silos can sometimes come about simply due to underfunding. Business leaders may see the task of changing the status quo when it comes to their data as an unnecessary expense because of the perceived lack of return on investment—something which doesn’t reflect reality, as we covered earlier!
  • Technology — Digital transformation and technology can work wonders for businesses, but a lack of the right solutions will hold back progress. Similarly, technology that’s not used correctly might lead to data not being accessible or may cause conflicts with other systems. It’s important to have a holistic view of your tech stack and understand whether it’s working for your compliance team and making them more efficient.

Although it is possible to begin breaking down silos manually, it’s no easy feat. Data now exists in unimaginable volumes and chances are that if it’s siloed, it’s disorganized. Even if you throw all your resources at the task, it’ll still be very difficult to unearth any meaningful, relevant insights—and you’ll be using up serious resources by doing so.

Indeed, it’s implementing the right technology solutions that align with organizational goals and processes that can truly help leaders to unshackle their data and begin making a true difference in internal processes.

Data in action with automated transaction monitoring

Contemporary transaction monitoring processes have helped organizations fight financial crime for decades and, to an extent, continue to generate valuable insights. On the other hand, criminals have become familiar with legacy transaction monitoring processes, and the sophisticated nature of the tactics deployed by the most insidious of modern-day threat actors necessitates the use of more modern, tech-backed solutions.

There’s also the issue of transaction volume. In times past, when there were fewer transactions to monitor and evaluate, it was easier for compliance teams to keep ahead of their workloads. Today, at a time when finance is more open and accessible than it has ever been, legacy, human-backed processes cannot keep up because there’s simply too much data to process.

Transaction monitoring is assisted by eliminating data silos in three key ways:

  1. Customer data provides real insight to transaction activity
  2. Faster investigations are possible by unifying data sources
  3. Create easily understood reports for audits by the regulator

It’s unreasonable for compliance to continue to suffer from data silos. By integrating an effective transaction monitoring system into AML workflows, data can be compiled efficiently and created strong customer profiles. These profiles allow for rapid investigations and can result in quicker turnaround times for compliance officers.

It’s easy to see how transaction monitoring can be done better with easier access to data and you can uncover more ways to make transaction monitoring work for your business in our ebook.

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