Marketing and compliance teams across the financial services sector are under mounting pressure. Channel proliferation, AI-accelerated content production, and an ever-shifting regulatory landscape are colliding, and the data tells a stark story.
According to a survey of US financial marketing and compliance leaders by Saifr, 61% of compliance executives reported rising review volumes, with more than half saying their teams require four to five days to assess a single piece of content, and 39% needing between six and ten days.
Saifr recently discussed how contextual AI is helping transform pre- and post-marketing compliance review workflows.
The root cause lies on both sides of the compliance fence. For marketing teams, the shift towards omni-channel campaigns and personalised advertising has dramatically increased the volume and variety of content that must be produced, and rapidly. To keep pace, many departments are now using generative AI tools to generate channel-specific material at scale, while others are experimenting with user-generated content, where influencers produce videos and posts based on their direct product experiences. None of this content is exempt from regulatory scrutiny, and in a regulated industry, skipping the compliance review simply is not an option.
On the compliance side, the challenge is equally acute. Review teams must contend not only with higher volumes but also with the technical nuances of disclosure requirements across formats including social media, video and imagery, as well as a regulatory environment that is still evolving. In the US, FINRA has sharpened its focus on generative AI outputs, while life insurance regulators enforce strict boundaries around what constitutes advertising. User-generated content adds a further complication, introducing creators who may have little to no familiarity with regulatory expectations, increasing the likelihood of non-compliance and requiring additional rounds of review.
What lies beneath these challenges is a more fundamental structural problem: legacy review workflows are simply not built for this environment. Most firms still rely on iterative, manual processes that depend heavily on the individual knowledge of each reviewer. These siloed systems lack shared intelligence and automation, fragmenting institutional knowledge and slowing content to market. Saifr’s research reveals a telling visibility gap. Compliance leaders estimate they review approximately 66% of all created content, whilst marketing teams report that only around 59% actually passes through compliance. That disconnect leaves both sides operating with an incomplete picture of what it takes to bring promotional material to market lawfully.
Manual handoffs between people and tools also introduce version sprawl, inconsistent documentation, and patchy audit trails, making it harder to defend decisions, increasing error rates, and eroding trust between teams. Over time, extended cycle times and operational inefficiencies do more than slow output. They introduce measurable reputational and regulatory risk, particularly when content reaches audiences without full compliance visibility. The traditional approach to scaling, whether adding headcount or extending timelines, is no longer sustainable.
This is where contextual AI is beginning to make a meaningful difference. Unlike general-purpose AI tools, contextual AI models are trained on industry-specific policies, regulatory frameworks, and communications standards. They can assess content not just for tone and language, but for compliance within the context of its intended audience and distribution channel. Crucially, they can be embedded into automated, platform-driven workflows that reduce manual touchpoints and accelerate the journey from draft to approved.
In the pre-review stage, these models use natural language processing and machine learning to flag potentially non-compliant material with evidential reasoning, helping marketers reach cleaner first drafts with fewer revisions. The result is more consistent quality control without sacrificing speed to market. Human oversight remains essential throughout, particularly at the point of final approval, but the handoffs between reviewer and system become cleaner and more structured.
The value extends into post-review workflows too. Contextual AI can enable side-by-side comparisons of content versions, provide in-line policy references and suggested remediations, ensure consistency of response across review teams, and build auditability into the process by design, capturing timestamps, version histories, approver records, and exportable logs. When regulations change, models can be updated quickly, ensuring that compliance protocols keep pace with the regulatory environment rather than trailing behind it.
Taken together, these capabilities represent a fundamental shift: from a fragmented, reactive compliance process to an integrated, proactive workflow that spans content creation through to final sign-off. For financial services firms navigating an increasingly complex content landscape, those that rethink their review infrastructure now will be best placed to scale compliant output, reduce risk exposure, and ultimately move faster than their competitors.
Read the full Saifr post at this link.
Copyright © 2026 RegTech Analyst
Copyright © 2018 RegTech Analyst
