Exclusive Content:

Haiper steps out of stealth mode, secures $13.8 million seed funding for video-generative AI

Haiper Emerges from Stealth Mode with $13.8 Million Seed...

Running Your ML Notebook on Databricks: A Step-by-Step Guide

A Step-by-Step Guide to Hosting Machine Learning Notebooks in...

“Revealing Weak Infosec Practices that Open the Door for Cyber Criminals in Your Organization” • The Register

Warning: Stolen ChatGPT Credentials a Hot Commodity on the...

How dLocal Streamlined Compliance Reviews with Amazon Quick Automate

Transforming Compliance in Cross-Border Payments: dLocal’s Journey with AWS Quick Automate


Leveraging AI for Continuous Merchant Compliance and Operational Excellence


Transforming Compliance in Fintech: dLocal’s Journey with AWS Quick Automate

In the rapidly evolving landscape of fintech, maintaining compliance is paramount, especially for cross-border payment solutions. dLocal, Uruguay’s first unicorn, has pioneered this domain since its inception in 2016, connecting over two billion consumers with global technology giants across more than 40 emerging markets. Yet, as dLocal expanded, so did the complexities of compliance—a challenge they are meeting head-on.

The Compliance Challenge

As a major player in cross-border payments, dLocal handles thousands of merchant e-commerce sites. Each month, the company rigorously reviews these sites to ensure alignment with strict compliance standards. This includes verifying that merchants do not sell prohibited goods or services and confirming that their domains are valid and accessible. However, the compliance challenge extends beyond initial onboarding; it necessitates ongoing monitoring to adapt to changes in merchant offerings and practices.

As dLocal grew, the limits of their established compliance processes became evident. While a proprietary generative AI solution accelerated the initial review, the exponential increase in merchant onboarding placed a strain on the system. A significant portion of reviews still required manual assessments, creating bottlenecks that widened as transaction volumes increased.

Introducing Automation with AWS Quick Automate

In 2023, recognizing the need for enhanced automation to streamline the compliance review process, dLocal turned to AWS. By implementing Amazon Quick Automate, they positioned themselves to address the scalability issues effectively. Quick Automate facilitates resilient automations at scale, combining UI automation, API integrations, and orchestration in a comprehensive solution.

This innovative partnership enabled dLocal to automate their merchant compliance website review process significantly, achieving large-scale and efficient policy enforcement. Quick Automate employs generative AI to analyze user inputs, allowing for tailored automation solutions across business systems and user interfaces. It also intelligently engages human operators when necessary, balancing automation with expert oversight.

The Automation Solution in Action

The implementation of Quick Automate involved a strategic collaboration between dLocal and the AWS team to design a solution capable of navigating multiple product pages and evaluating compliance against dLocal’s rigorous policies.

Core Workflow:

  1. Case Management: Merchant cases are retrieved for evaluation from a processing queue, enabling simultaneous processing and optimization of efficiency.

  2. UI Agent Evaluation: This specialized agent navigates websites across various languages, assessing compliance with dLocal’s standards and identifying prohibited items.

  3. Handling Exceptions: Websites that are inaccessible are flagged, and accessible sites are evaluated to determine compliance status. Detailed reasoning is provided for all decisions, with ambiguous cases routed to human reviewers.

  4. Secure Data Storage: Compliance results are logged and stored securely in Amazon S3, ensuring adherence to regulatory standards.

By enhancing their compliance processes with automation, dLocal reduced the manual review burden and improved efficiency. With Quick Automate, up to 75% of merchant website reviews can now be completed without human intervention, allowing compliance specialists to focus on complex cases where expertise is essential.

Results and Impact

The results of this automation initiative are clear: dLocal has not only improved compliance monitoring but also positioned itself to scale merchant onboarding effectively. As the company continues to expand, the automation rates are expected to rise, enabling rapid adaptation to the growing demands of the fintech landscape.

As Mauricio Clausen, VP of AI at dLocal, noted, “With Amazon Quick Automate, we’ve accelerated the evolution of our AI-assisted solutions, enabling efficient scaling of merchant due diligence for cross-border payments. This partnership has allowed us to streamline the compliance process significantly.”

Conclusion

dLocal’s integration of Quick Automate exemplifies a transformative approach to compliance in fintech. By leveraging AI-powered automation, the company has effectively navigated operational challenges while strengthening its compliance posture. This not only positions dLocal as an industry leader but also offers a scalable model for other organizations facing similar regulatory demands.

As the fintech industry continues to evolve, the lessons learned from dLocal’s journey with AWS highlight the potential of technology to enhance compliance processes, allowing companies to focus on growth while ensuring rigorous standards are maintained.

Learn More

To explore how Quick Automate is revolutionizing operations and enhancing compliance workflows, delve into the resources provided by AWS and dLocal’s ongoing innovations in the fintech realm.

Latest

Best Practices for Reinforcement Fine-Tuning on Amazon Bedrock

Optimizing Model Performance with Reinforcement Fine-Tuning (RFT) in Amazon...

Claude vs. ChatGPT: My Reasons for Switching

Why I Switched from ChatGPT to Claude The Tone Problem...

How Robotics is Revolutionizing Joint Replacements in Gloucestershire

Advancing Knee Replacements: The Future of Robotic-Assisted Surgery at...

AI Unravels Alzheimer’s Mysteries, Speeding Up Research Advancements

Decoding Alzheimer's: How AI is Revolutionizing Research and Treatment Why...

Don't miss

Haiper steps out of stealth mode, secures $13.8 million seed funding for video-generative AI

Haiper Emerges from Stealth Mode with $13.8 Million Seed...

Running Your ML Notebook on Databricks: A Step-by-Step Guide

A Step-by-Step Guide to Hosting Machine Learning Notebooks in...

Investing in digital infrastructure key to realizing generative AI’s potential for driving economic growth | articles

Challenges Hindering the Widescale Deployment of Generative AI: Legal,...

VOXI UK Launches First AI Chatbot to Support Customers

VOXI Launches AI Chatbot to Revolutionize Customer Services in...

Best Practices for Reinforcement Fine-Tuning on Amazon Bedrock

Optimizing Model Performance with Reinforcement Fine-Tuning (RFT) in Amazon Bedrock Explore how to customize Amazon Nova and open-source models with Reinforcement Fine-Tuning (RFT) to achieve...

Introducing Stateful MCP Client Features in Amazon Bedrock AgentCore Runtime

Unlocking Interactive AI Workflows: Introducing Stateful MCP Client Capabilities on Amazon Bedrock AgentCore Runtime Transforming Agent Interactions with Elicitation, Sampling, and Progress Notifications In this article,...

Contemporary Topic Modeling Techniques in Python

Unveiling Hidden Themes with BERTopic: A Comprehensive Guide to Advanced Topic Modeling Understanding the Basics of Topic Modeling Explore traditional methods vs. modern approaches. What is BERTopic? An...