A forecast in an email reads like a guarantee.

A projection written like a promise

Forward-looking statements are claims about the future: growth, returns, performance. In financial communications they have to be balanced and not misleading, and the right version carries the uncertainty with it. The risky version drops the uncertainty: we will definitely hit target, you can expect double digits, this is basically certain. Written down, an overstated projection reads as a commitment.

The pressure to sound confident produces the line. An adviser reassuring a client, or a manager updating investors, reaches for the definite phrasing because it lands better. Review and approval catch some of it later, in a controlled document. The everyday email is where it slips, and that is where the wording can still change.

The overstatement, with a measured rewrite

VerbaPulse reads the draft as it forms, flags the projection that has lost its balance, and offers wording that keeps the message. Real output from the product:

The same check covers the related patterns:

• Definite forecasts ("we will definitely hit", "you can count on it").
• Unhedged return projections ("you can expect double digits", "this will return X").
• Certainty framing on an uncertain outcome ("basically certain", "guaranteed to grow").
• Past performance presented as a forward promise.
• Your own rules: upload your communications policy and VerbaPulse enforces it on every draft.

In the inbox your team already uses

The writing layer, before review and disclaimers

VerbaPulse does not run your investor relations review, your approval workflow, or your standard disclaimers. Those still apply. VerbaPulse adds the earlier layer: it catches the overstatement in the draft, while the wording can still change, so fewer of them reach review or the recipient in the first place. It is one control inside email compliance for financial services, and it sits next to financial promotions, which covers guarantees and the wider promotion regime.

• Email content is never stored: drafts are analyzed in memory and discarded immediately.
• Nothing is used to train AI models.
• The audit trail is anonymized by design: risk types, severities, and outcomes, never message text or named individuals.
• It keeps the writer's intent, so the forecast still goes out, just without the certainty it cannot support.

For the evidence behind this, our language risk benchmark runs real, anonymized cases through the product and reports what it flags.

Common questions