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The Data Realities of Our Financial Crime Clients

When it comes to data, our clients tell us that their challenges continue unabated. If we look across the entire financial crime landscape, this complexity stems from three main areas. While any one of these issues might be reasonable for a team to overcome, in combination they are difficult for financial services organizations and tend to be a major focus of concern in planning, operations, and resource allocation.

In no particular order, the data-related challenges we see are:

  • Access: Data is of little use if it cannot be accessed and used as required by compliance, fraud and other risk management professionals. However, either due to organizational siloes, geographic dispersion or internal politicking, sometimes merely the act of gaining access requires willpower and enormous efforts that make the seemingly simple act of "getting to the data" a profound undertaking.
  • Format: The number of formats is growing, which inherently brings challenges to our clientele. They must find ways to accommodate these new data sources and reconcile them with existing ones. Relying on manual processes to do this is not wise and not a future-proof strategy.
  • Volume: The continued growth1 in big data2 stacks3 among our clients and broadly in the financial services industry demonstrates that volumes will only grow (to state the utterly obvious). I'd even wager that down the road, people stop worrying about volumes once they know they can handle any volume, but that's a blog for another day.

On top of this, our clients must keep the following business realities front and center as they work to ensure that data is an enabler and not a disabler.

  • First, they must be able to parse and map this data so that its meaning can ultimately be extracted.
  • Second, they should have a plan for data integration so that the multitude of sources can be brought together to provide a situation approaching the nirvana-esque vision of a 360-degree view of the customer / transaction / entity.
  • Third, they have to provide and document the rationale behind their data usage in situations that require model risk management. In situations that don't formally require model risk management, they still must find a means to justify their actions to colleagues, internal audit teams and others.
  • Last, our clients talk about being on-the-ready for regulatory examinations and regulatory questioning. The spike in both data privacy legislation (think about GDPR and its main changes) and in data breaches (think of the many recent headlines) combine to make our clients constantly remain vigilant when it comes to regulatory readiness.

These data insights are what our clients think and worry about. They are why we've proposed the new autonomous vision for our industry. These challenges will only grow. By applying a new mindset and using innovative technologies such as intelligent automation and machine learning, we will help our clients turn data from a negative to a positive. We look forward to working with our clients and partners on this journey.

Interested in learning more about our intelligent automation and solutions? Download our white paper "Optimized Investigations at the Speed of Risk."

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1https://www.forbes.com/sites/gilpress/2016/12/12/2017-predictions-for-ai-big-data-iot-cybersecurity-and-jobs-from-senior-tech-executives

2 http://www.bankingtech.com/2016/03/big-data-analytics-and-its-many-uses

3 https://dzone.com/articles/big-data-and-analytics-in-2017

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