Background and initial situation

A large financial institution operating globally faces the constant challenge of ensuring compliance with complex regulatory requirements and internal policies. The compliance department is often very busy reviewing policies, responding to regulatory inquiries and training employees on compliance issues. Manual processes led to delays and increased workload for the team.

Aims of the project

The main objective of the project was to increase the efficiency of the compliance department by automating recurring requests and improving the quality and availability of compliance information. Specific objectives included:

• Automation of frequently asked questions and regular compliance checks.
• Reduce processing time for regulatory requests.
• Improving the availability and accuracy of compliance information.
• Support for monitoring and compliance with regulations.

Solution implementation

To achieve these goals, the AI was integrated into the company’s existing compliance management systems. The implementation process followed a structured plan:

a) Needs analysis and planning:

• Identifying the most common compliance requests: By analyzing request data, the most common questions were identified, such as data protection regulations, anti-money laundering guidelines and corruption prevention.
• Determination of integration points: Relevant systems, including the compliance management system (CMS) and document management platform, were determined.

b) Development and integration:

• Creation of discussion workflows: Development of specific workflows to handle compliance issues and provide compliance support.
• Technical integration: The AI was seamlessly integrated into the compliance management system and the document management platform.

c) Training and knowledge database:

• Data import and structuring: Historical compliance data and frequently asked questions were used to expand the AI’s knowledge base.
• Regular updates: Planning regular updates to the knowledge base to ensure the relevance and accuracy of the information provided.

Application example and process scenario

Scenario: Request for compliance with data protection regulations

• Step 1: An employee makes a request for compliance with data protection regulations via the internal compliance chat system.
  – Employee: “AI, what measures do we have to take for data storage in accordance with the GDPR?”
• Step 2: The AI processes the request and retrieves relevant information from the compliance management system.
  – AI: “One moment please, I am checking the applicable data protection regulations in accordance with the GDPR.”
• Step 3: The AI provides the requested information on data protection regulations.
  – AI: “Under the GDPR, we must ensure that personal data is stored securely. This includes measures such as:
  1. encryption of data.
  2. use of access controls.
  3. regular security checks.
  4. compliance with the retention period and timely deletion of data.
  Would you like more detailed information on any of these points?”
• Step 4: The employee states what exactly they need.
  – Employee: “Yes, please provide more information on encryption.”
• Step 5: The AI provides detailed information on data encryption
  – AI: “Sure, you should consider the following when encrypting data in accordance with the GDPR:
  1. use strong encryption algorithms such as AES-256.
  2. ensure that both data at rest and data in transit is encrypted
  3. regularly reviewing and updating encryption technology.
  Are there any other aspects you need information on?”
• Step 6: The employee thanks you for your help.
  – Employee: “No, that was very helpful. Thank you very much!”
• Step 7: The AI documents the request and the information provided in the compliance management system.
  – AI: “You’re welcome! Your request has been documented in the compliance system. Let me know if you need any further assistance.”

Results and benefits

Following the implementation of AI, there were significant improvements in compliance and regulation management:

• Reduced processing time: The average processing time for compliance requests was reduced by 50%.
• Improved availability: Employees had quick access to up-to-date and accurate compliance information at all times.
• Increased efficiency: Compliance staff were able to focus on more complex regulatory tasks.
• Increased compliance monitoring: Automated documentation of requests and solutions improved compliance monitoring.

Conclusion

The integration of AI into the company’s compliance and regulatory management processes led to a significant increase in the efficiency and accuracy of compliance work. By automating recurring requests and providing up-to-date information, valuable time was freed up and the quality of compliance work was significantly improved. Future enhancements could include the implementation of additional regulatory requirements and the use of advanced analytical tools to further optimize compliance monitoring.