Prospecting
AuraScore 81/100

Institutional Asset Management Consultant Search and Mandate Acquisition Spec

Create a structured prospecting specification to target investment consultants and secure institutional asset management mandates.

Use this template when designing an institutional business development strategy targeting gatekeeper investment consultants and institutional allocators. It provides mandate tracking rules, consultant engagement workflows, and alpha attribution positioning specs.

Template

Role: Managing Director of Institutional Asset Management Distribution and Global Consultant Relations.

Context

  • Asset Class Strategy: {{asset_class_strategy}}
  • Target Institutional Segment: {{target_institutional_segment}}
  • Gatekeeper Investment Consultants: {{investment_consultant_gatekeepers}}
  • Performance & Track Record Data: {{benchmark_outperformance_data}}
  • Commercial & Fee Terms: {{fee_structure_terms}}
  • ESG and Reporting Standards: {{esg_reporting_standards}}

Task

Author a comprehensive institutional prospecting and consultant positioning specification to insert {{asset_class_strategy}} onto the approved buy-lists of {{investment_consultant_gatekeepers}} for {{target_institutional_segment}} allocators.

Method

  1. Profile the manager research and field consultant hierarchies across {{investment_consultant_gatekeepers}} to identify specific asset-class practice leads.
  2. Translate {{benchmark_outperformance_data}} into factor attribution, risk-adjusted alpha (Sharpe/Information ratios), and downside capture metrics.
  3. Identify market search triggers within {{target_institutional_segment}} (e.g., funded status thresholds, style rotation away from legacy benchmarks, mandate terminations).
  4. Formulate consultant-specific briefing documents highlighting active risk budgeting and implementation efficiency.
  5. Align the investment vehicle's operational compliance with {{esg_reporting_standards}} (e.g., SFDR Article 8/9, PRI, TCFD reporting).
  6. Structure competitive fee positioning using {{fee_structure_terms}} against peer group quartiles in databases (eVestment, MercerInsight).
  7. Establish a formal 90-day consultant engagement sequence designed to advance the strategy from "unrated" to "recommended/buy" status.
  8. Define institutional RFP pre-qualification criteria to filter low-probability search notices from active mandate pipelines.

Constraints

  • MUST present performance positioning strictly in compliance with GIPS (Global Investment Performance Standards).
  • MUST NOT make forward-looking performance promises or unsubstantiated return projections.
  • All database and outreach specifications MUST align with the institutional reporting standards in {{esg_reporting_standards}}.
  • Minimum of 3 quantitative proof points required for every marketing claim.
  • Language MUST adhere to institutional investment governance and fiduciary terminology.

Output format

  1. Consultant Research Landscape (Gatekeeper profiles, key research heads, ratings cycle timelines)
  2. Strategy Factor & Alpha Positioning Spec (Factor exposures, track record analytics based on {{benchmark_outperformance_data}}, down-market performance profile)
  3. Commercial Terms & Capacity Architecture (Fee structures based on {{fee_structure_terms}}, capacity limits, vehicle availability)
  4. 90-Day Consultant Engagement Blueprint (Outreach milestones, formal due diligence questionnaire preparation, pitch deck specifications)
  5. Mandate Qualification & Go/No-Go Decision Matrix (Scoring system for inbound searches and RFP invitations)

Self-review

  • Ensure all performance discussions are framed around {{benchmark_outperformance_data}} with institutional risk metrics.
  • Confirm the engagement workflow targets both manager research analysts and field consultants.
  • Verify that commercial terms directly account for {{fee_structure_terms}} and institutional fee scrutiny.
AuraScore breakdown
81/100Provisional
Instruction clarity15/15 · Strong

Explicit role, a named task, and discrete steps the model can follow.

Context architecture12/12 · Strong

Background, inputs and variables the model needs before it starts.

Constraint engineering12/12 · Strong

Hard boundaries — what the model must and must not do.

Output specification6/14 · Thin

A named, field-level shape for the response.

Reasoning structure10/10 · Strong

Ordered work items that force analysis before an answer.

Model compatibility10/10 · Strong

Length and structure that travel across frontier models.

Token efficiency5/10 · Thin

Signal density — instruction weight without padding.

Reusability7/7 · Strong

Documented variables so the scaffold adapts to new inputs.

Robustness3/5 · Adequate

Quality bar, assumptions and behaviour when inputs are thin.

Observed performance1/5 · Thin

How much real usage the template has behind it.

sales
sales-prospecting
financial-services
institutional-sales
asset-management
consultant-relations