Institutional fund sales relies on adept personalisation, where tailored AI-generated product films can be made in minutes.
TL;DR: pilot AI projects using control groups.
AI agents are all the rage, and can even produce a tailored product film for individuals out of hundreds of targeted accounts – according to legal AI firm Harvey. This is how:
- Agents pull from internal sales data to script every film: sales call recordings, won-loss reports and documented internal discussions.
- The AI can also follow brand rules, with parameters written specifically for them.
- A cloned voice is used to narrate it.
- Clips can be assembled in Figma using a shared library of demo flows, product screens and animations.
- Marketers can review a sample of the output to give feedback to the agents, which can pull new rules into their workflows.
Staggeringly, one batch of 36 films can take just over an hour to complete.
So, what does this mean for fund marketers?
Institutional asset managers are driven by account-based marketing and sales, adopting target lists of pension schemes, insurers, consultants, and private banks with different concerns relating to liability matching, liquidity, or ESG policy.
Hand-picking content per individual has been a time and cost pressure for decades. But this approach suggests a tailored strategy can be more targeted, and far less hours put into it.
These films are promotional by nature, and that means stringent compliance. Under the SEC Marketing Rule, templated content personalised at scale will not count as one-to-one communications. Performance presentations and hypothetical projections all fall within scope.
Clear, non-misleading content to professional clients is expected in the UK and EU, and distribution relies on adhering to the Alternative Investment Fund Managers Directive’s (AIFMD) pre-marketing limits.
Luckily, Harvey’s model of shared pre-approved building blocks can still be worth following to fit funds’ ‘regulatory reality’:
- Get compliance sign-off on strategy narrative or risk language to ensure personalisation does not introduce wild new claims.
- Tailor openings to prospects’ known priorities and keep disclosure fixed.
- Use CRM data (consultant feedback, RFP themes, meeting notes) that are covered by data protection rules.
- In advance, plot what proportion of personalised outputs are checked before release, and what triggers a full compliance review.
Harvey has not published conversion results for the films. Therefore, any pilot undertaken by a fund manager should have a control group in mind to track meetings, DDQs and consultant ratings against.
Source
Harvey, “How Harvey is Building a Frontier Marketing Org” (via TLDR Marketing)
