Jump's Approach to Security and Compliance
One in ten financial advisors use Jump.
From meeting intelligence to automated documentation and follow-through, AI is a mainstay in advisor workflows.
As adoption accelerates, however, another trend is emerging alongside it: increased regulatory attention.
Industry guidance makes clear that technology used in the delivery of advice must be understood, reviewed, and governed. Advisors remain responsible for the outcomes produced through their workflows — including those shaped by AI. At the same time, platforms themselves carry an important responsibility to support transparency, oversight, and control so firms can confidently operationalize these tools.
At the same time, firms are navigating a crowded market of AI tools. While transcription and meeting assistants can improve efficiency, financial conversations carry additional complexity: sensitive client data, documentation requirements, and supervisory expectations. As conversational AI begins generating notes, tasks, and client communications, firms need confidence in how those interactions are captured, reviewed, stored, and distributed.
This is why governance and trust are central to advisor AI adoption. Firms require platforms that support policy enforcement, human review, consent management, and data protection without disrupting advisor workflows.
At Jump, these controls are built directly into how conversational intelligence is captured and operationalized:
- Flexible capture and retention controls. Firms can choose how meetings are processed, including summary-only modes that generate AI outputs without storing audio or video recordings, as well as configurable retention policies for transcripts and media.
- Firm-defined compliance policies. Administrative controls allow organizations to centrally manage settings for meeting capture, disclosures, data movement, integrations, and access permissions across advisor accounts.
- Human review before system actions. Firms can require advisor attestation before syncing notes to CRM systems, generating follow-up communications, exporting notes, or triggering downstream workflows.
- Consent and disclosure management. Recording consent can be verified through transcript detection, advisor confirmation, or a hybrid model, with firm-defined disclosures automatically attached to notes.
- Data protection safeguards. Built-in controls support automatic redaction of sensitive information and restrictions on transcript copying, downloads, and external data sharing.
These controls allow firms to apply their own governance standards to advisor AI workflows — ensuring that technology adapts to firm policy, not the other way around.
As advisor AI continues to evolve, we believe trust will be the defining differentiator.
If you’re interested in how Jump approaches governance, oversight, and control across conversational workflows, explore our trust center.