Safeguarding Trust

The rise of generative AI (gen AI) is transforming the financial compliance landscape, offering tools that enhance productivity, deepen insights, and enable faster decision-making. At the Institute for Financial Integrity (IFI), we’ve embraced this potential through the development of AskFIN, our proprietary gen-AI-powered financial crime assistant.

AskFIN leverages DOLFIN, IFI’s proprietary online library, which is home to expertly curated content, resources, and analysis on financial crime-related topics. DOLFIN has long been a trusted resource for compliance professionals seeking authoritative information and actionable insights. By integrating DOLFIN’s robust database with cutting-edge gen-AI technology, AskFIN delivers precise, reliable, and secure answers tailored to the unique challenges of financial compliance.

However, building and delivering gen-AI-powered capabilities like AskFIN comes with its own set of complexities, from ensuring privacy and security to maintaining transparency and accuracy. This article delves into two critical challenges in this space—privacy and security, and transparency—and outlines the strategies that underpin AskFIN’s trusted approach to gen-AI in compliance.

Challenges in Building Trusted Gen-AI Capabilities

Privacy, security, transparency, and governance are critical considerations when implementing generative AI solutions in financial compliance. These foundational elements ensure sensitive information is protected, decisions are transparent, and user trust is maintained. These principles guided the development of AskFIN, ensuring it meets the unique demands of the compliance space.

• Privacy and Security
  Safeguarding privacy and security must begin at the design phase. In building AskFIN, we prioritized localized data processing environments, ensuring sensitive information would never feed external AI models. By leveraging permission-based access controls, AskFIN ensures users can only access data they are authorized to view. These approaches create a scalable, secure environment that protects interactions while enabling powerful productivity workflows for compliance professionals.
• Transparency and Accountability
  Transparency is essential in building trust with users and stakeholders. In developing AskFIN, we moved beyond the traditional “black box” approach, enabling users to trace every response back to its specific, credible source. This transparency has been enthusiastically received by users, who value the ability to understand the rationale behind answers and the data underpinning them. Regular updates and feedback loops continue to refine AskFIN’s sourcing granularity and functionality, fostering accountability and confidence.

Strategies for Building Trusted Gen-AI Capabilities

The following strategies, applied in the development of AskFIN, can serve as best practices for organizations aiming to responsibly implement gen-AI in compliance:

1. Domain-Specific Guardrails: We implemented clear guardrails to ensure AskFIN remained focused on financial integrity topics while allowing flexibility for adaptation to new concepts and terms.
2. Restricted Content Scope: AskFIN draws exclusively from expertly curated content within DOLFIN, avoiding reliance on unverified external data sources. This ensures responses are reliable and aligned with industry standards.
3. Iterative Development and User Collaboration: Throughout the development of AskFIN, we prioritized regular updates, transparent sourcing, and incorporating user feedback to refine functionality and maintain accountability. These practices help continuously evolve AI systems in alignment with user needs and industry expectations.