── ── Industry
RIA — Client Behavior Coaching (Loss Aversion)
The parent loss-aversion-prospect-theory shows losses loom ~2× gains and that framing drives choices. An RIA's biggest value-add (and retention lever) is preventing clients from selling low. Coaching = re-framing and pre-committing against predictable behavioral errors.
Run RIA — Client Behavior Coaching (Loss Aversion) on a real problem
Bring something you're actually deciding — free, in the browser.
How it works
- Pre-commit: set the response to a drawdown in the IPS before it happens (rebalance, don't flee). - Reframe: show goal-progress and time-diversified odds, not daily P&L; frame in dollars-to-goal. - Reference points: avoid anchoring clients to the peak; anchor to plan and funded-ratio. - Distinguish behavioral panic from a real plan change (don't over-suppress legitimate concerns).
When to use it
- a market drop has clients wanting to sell
- framing performance reviews
- onboarding risk tolerance
- 'clients panic in downturns,' 'how do I keep them invested?'
When not to use it
a genuine plan change is warranted (don't rationalize a real problem away).
Worked example
RIA — Client Behavior Coaching (Loss Aversion)
The parent loss-aversion-prospect-theory shows losses loom ~2× gains and that framing drives choices. An RIA's biggest value-add (and retention lever) is preventing clients from selling low. Coaching = re-framing and pre-committing against predictable behavioral errors.
Install this skill (free, MIT)
npx skills add deciqAI/knowledge-skillsUseful? Star the repo — stars help other builders find it.
Related mental models
The parent margin-of-safety builds a buffer so estimation error doesn't cause ruin.
The parent principal-agent analyzes misaligned incentives between an agent and the principal they serve.
The parent expected-value-and-kelly sizes repeated positive-edge bets to maximize long-run growth without ruin.
The parent second-order-thinking traces "and then what?" across time and parties.