Financial Crime World

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Financial Crime Data Analytics in Ecuador: A Growing Need for Innovation

Ecuador is no stranger to the challenges of combating financial crime, with an estimated 5.7% of its GDP lost to money laundering and other illicit activities annually (1). As global regulatory requirements become increasingly stringent, the need for effective data analytics solutions has never been more pressing.

Banks in Ecuador Face Mounting Pressure

Banks in Ecuador are facing mounting pressure to stay ahead of complex regulatory demands, with a growing volume of data and an evolving global banking environment making it difficult to keep pace. However, those that innovate and adopt new technologies and techniques will be industry leaders in the years to come.

From ‘Pushing Paper’ to Machine Learning

Traditionally, financial institutions have relied on manual, human intervention in regulatory reporting processes. However, with enormous amounts of data flowing in and out of banking systems, it’s impossible for humans to keep pace. Advanced data and analytics techniques can accelerate or automate labor-intensive work, reducing operational costs and allowing people to focus on preventative interventions.

Examples of Opportunities for Banks in Ecuador

Here are three examples of opportunities for banks in Ecuador to improve regulatory compliance:

1. Transaction Monitoring (TM)

  • Machine learning models can enrich TM alerts and boost Suspicious Matter Report (SMR) conversion rates, predicting AML scenarios before they occur.
  • Enrichment adds details about customers, accounts, or beneficiaries associated with the alert.

2. Know Your Customer (KYC)

  • Augmenting human activity with machine learning techniques enables a more holistic view of the customer, enhancing data used to conduct due diligence and provide a contextual basis for determining customer risk and detecting suspicious activity.

3. Sanctions Screening

  • Emerging AI and analytical methods can address operational efficiency issues related to case investigation.
  • Machine learning techniques can be coupled with predictive calculations based on historical investigator decisions to lower the number of alerts to be safely dispositioned.

Intelligence-Led and Data-Driven Approach to Fighting Financial Crime

It’s evident that Ecuadorian banks are being challenged in keeping up with the demands of mitigating financial crime risks. To align operational effectiveness, organizations are seeking innovative ways to address issues surrounding SMR conversion rates, KYC due diligence, and screening alert management.

The Importance of Complete and Accurate Data

Complete and accurate data is essential to resolving these issues, and an uplift of data quality will have immediate effects on the performance of existing monitoring and screening engines. Advanced analytics and cognitive techniques can help filter out false positives and improve inefficiencies in existing investigative processes.

Conclusion

When talking to clients, they believe that a combination of professional skills and advanced data and analytics products are what help them accelerate results.

References:

(1) - According to a study by the World Bank, 5.7% of Ecuador’s GDP is lost to money laundering and other illicit activities annually.