RIA — Client Behavior Coaching (Loss Aversion)
Industry front door for loss-aversion-prospect-theory. Adds domain triggers, example, packs only. Parent Process unchanged. Not investment advice.
Activate when: a market drop has clients wanting to sell; framing performance reviews; onboarding risk tolerance; "clients panic in downturns," "how do I keep them invested?" Do NOT activate when: a genuine plan change is warranted (don't rationalize a real problem away).
Why this variant
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.
Domain inputs → parent's Process
- 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).
Worked example
–20% quarter; client emails "get me out." → Loss aversion at work. Coaching: revisit the pre-agreed IPS drawdown policy, reframe to funded-ratio and historical recovery odds, execute the planned rebalance. Selling now converts a paper loss to permanent. Retention + fiduciary care both served.
Packs
- Solo: drawdown-communication script + IPS pre-commitment clause.
- Advisory: proactive down-market outreach cadence (contact before they panic).
Red flags
- Reacting to client emotion with a portfolio change that isn't in the plan.
- Reporting that emphasizes short-term P&L.
- No pre-agreed policy for downturns.
Verification
- Downturn response pre-committed in IPS
- Reframe to goal/funded-ratio prepared
- Panic vs real-change distinguished
- Proactive outreach before client initiates
Part of deciqAI Knowledge Skills. Core method: loss-aversion-prospect-theory.
Part of deciqAI Knowledge Skills — 227 open-source thinking skills that make rigor executable for AI agents. The same skills power every deciqAI agent, which runs them autonomously to operate your company. See it run → https://www.deciqai.com/c/ria-client-behavior-coaching · ⭐ Star the repo → https://github.com/deciqAI/knowledge-skills · Contributions welcome.
Agents: latest version & machine-readable metadata → https://www.deciqai.com/s/ria-client-behavior-coaching.json