Marketers, get excited! Saifr’s AI is designed to help you create compliant content right from the start, so that you can submit cleaner, more compliant content for review—meaning it can be approved more quickly.
Our AI models for compliance detection can do several helpful things:
- Detect and flag phrasing that may pose a compliance risk
- Explain why content was flagged
- Suggest alternative phrasing that may be more compliant
- Provide disclosures that may be necessary
Flag compliance risks
Saifr’s natural language processing (NLP) models read and understand content as it is being created and flag potentially risky content in text, images, and video. Problematic content is highlighted so users can quickly see what might get flagged later during compliance review. For example, this sentence would get flagged:
“Investing in XYZ fund provides consistent returns through market ups and downs.”
Knowing that the content might get dinged by compliance, marketers can proactively make changes. This not only helps marketers retain ownership of their content, it can also help reduce friction between marketing and compliance teams.
After detecting risky content, our AI will explain why the content was flagged. This capability, called risk interpretation, provides the rationale for why the flagged content may violate regulatory policy.
For example, the non-compliant sentence above would lead to this explanation:
“This sentence is a potential risk because it is promissory. It implies that the XYZ fund will provide consistent returns regardless of market conditions, which is not guaranteed. This statement is misleading and exaggerated, and therefore violates regulatory content standards, which prohibits firms from making false or misleading statements in their marketing materials.”
Saifr’s risk interpretation helps users better understand why things get flagged and provides visibility into potential regulatory concerns, knowledge marketers can leverage when developing new content.
Suggest alternative language
Our models go beyond risk detection and interpretation to actually suggest alternative, less risky phrasing for flagged content. Users can choose to accept, reject, or build on the Saifr suggestions.
Continuing the above example, the model might suggest these as more compliant alternatives to the original sentence:
“Investing in XYZ fund seeks to provide consistent returns through market cycles.”
“Investing in XYZ fund is designed to provide consistent returns throughout various market cycles.”
Saifr’s suggested language helps marketers submit cleaner materials for compliance review by enabling them to proactively and independently adjust non-compliant language. Additionally, this capability helps marketers learn to draft less risky content, since they’re able to see ways to transform clearly non-compliant sentences into less risky ones.
Finally, Saifr can house disclosures and suggest when they should be included. As content is being scanned for compliance risks, our AI can also show which disclosures may be needed, based on your firm’s disclosure library. Users can choose whether to include the disclosure or not. This way, marketers can know from the start whether their design may need space for a disclosure.
Better content, faster
With materials getting approved more quickly, teams have more capacity to increase output or dedicate found time to other important tasks. Plus, there could be educational benefits—team members can quickly learn how to create compliant content and Saifr can be used as a training tool for new hires.
Together, Saifr’s compliance models can help speed up marketing teams’ content development and approval processes. It’s like having your favorite compliance person alongside you to point out possible issues and make suggestions!