Automate Client Conflict Checks with Microsoft 365 Solutions

Conflict checks are the first guardrail in ethical legal practice, yet they are often manual, fragmented, and risky. Automating this process with Microsoft 365, SharePoint, and Power Platform can radically improve speed, accuracy, and compliance. This week’s guide walks through how to implement automated client and party conflict checks using SharePoint Lists and Power Automate—so your attorneys get faster answers, compliance gets better controls, and clients get a smoother, more confident onboarding experience.

• Why Automate Client Conflict Checks in SharePoint Lists
• Architecture: Microsoft 365 & Power Platform Blueprint
• Data Model: SharePoint Lists & Metadata for Conflicts
• Step-by-Step: Build a Power Automate Conflict Check Flow
• Compliance, Risk, and Ethical Walls with Microsoft 365
• Integrating AI for Smarter Matching
• User Experience in Teams and SharePoint
• ROI & Business Case
• Operational Playbook & Best Practices
• Future Trends in Automated Conflict Checking

Why Automate Client Conflict Checks in SharePoint Lists

Manual conflict checks are slow, inconsistent, and prone to human error. Attorneys and intake teams often rely on emails, shared spreadsheets, or legacy databases with poor search capabilities. In contrast, SharePoint Lists—augmented by Power Automate and Teams—enable structured data capture, consistent workflows, and audit-ready logs. The payoff is a faster intake decision, better compliance with professional rules, and a more reliable client experience.

Architecture: Microsoft 365 & Power Platform Blueprint

A modern conflict check solution in Microsoft 365 centers on SharePoint Lists for structure, Power Automate for orchestration, and Teams/Outlook for collaboration and approvals. Depending on the firm’s maturity, you can add Power Apps for a dedicated intake UI, Dataverse for scale, and Microsoft Purview for end-to-end data governance.

• Data capture: SharePoint List “Matter Intake” (new client/matter requests)
• Reference data: SharePoint Lists for Clients & Parties, Adverse Parties, Related Counsel, Restricted/Watchlists, and Engagement History
• Automation: Power Automate triggers on new intake, normalizes data, performs multi-list searches, scores risk, and routes to Conflicts for review
• Collaboration: Teams channel posts with Approvals; comments and outcomes synced back to intake
• Governance: Purview sensitivity labels, DLP policies, retention, audit, and eDiscovery
• Optional scale: Power Apps for guided intake; Azure Cognitive Search or Dataverse for advanced search performance

Intake (SharePoint) → Normalize & Expand (Flow) → Search & Score → Review (Teams Approval)
        ↓                                                     ↑
     Log Results (Conflicts Log) ← Decision & Notes ← Notify Attorney & Update Matter
  

Data Model: SharePoint Lists & Metadata for Conflicts

Strong automation starts with a well-structured data model. For conflict checks, prioritize normalization, aliases, and relationships between parties and matters.

• Matter Intake
  • MatterID (Unique ID)
  • RequestedBy (Person)
  • ClientName (Text)
  • ClientAliases (Multi-line text JSON or semicolon list)
  • PartiesInvolved (Multi-line text; one per line with role)
  • MatterDescription (Multi-line text)
  • PracticeArea (Choice)
  • Jurisdiction (Choice)
  • ConflictsStatus (Choice: Pending, Review, Cleared, Hold)
  • ConflictsScore (Number)
  • ConflictsNotes (Multi-line text)
• Clients & Parties
  • EntityName (Text)
  • NormalizedName (Text; uppercase/stripped)
  • Aliases (Multi-line text)
  • EntityType (Client, Adverse, Vendor, Related Counsel)
  • RelatedMatterIDs (Lookup or text list)
• Conflicts Log
  • LogID
  • MatterID
  • Matches (Multi-line text; JSON with names, score, source list)
  • Decision (Cleared, Escalate, Declined)
  • Reviewer (Person)
  • Timestamp
• Watchlists & Restrictions
  • RestrictedEntity
  • RestrictionType (Ethical Wall, Contractual, Sanctions)
  • Notes

Tip: Precompute “NormalizedName” columns (e.g., uppercase, remove punctuation/spaces) to improve search reliability and performance. Index columns used in OData filters to avoid list throttling.

Step-by-Step: Build a Power Automate Conflict Check Flow

Below is a clear, practical walkthrough for automating conflict checks when a new matter is submitted to the “Matter Intake” SharePoint list.

1. Create the trigger:
   • In Power Automate, choose “When an item is created” for the Matter Intake list.
   • Capture key fields: MatterID, ClientName, ClientAliases, PartiesInvolved, PracticeArea, Jurisdiction.
2. Normalize and expand inputs:
   • Use “Compose” to convert names to uppercase and strip punctuation.
   • Split aliases and parties into arrays (use “Parse JSON” if stored as JSON).
   • Create a combined array of all names to search (client + aliases + parties).
3. Search reference lists:
   • For each list (Clients & Parties, Watchlists), use “Get items” with OData filters like substringof(‘NAME’, NormalizedName) or exact equals on NormalizedName.
   • Use pagination and filters to manage large lists; index NormalizedName and EntityType columns.
4. Score potential conflicts:
   • Assign weights: Exact match = 100; alias match = 80; partial/fuzzy = 60; watchlist hit = 120.
   • Aggregate scores across all hits; store top matches and rationale in an array.
5. Write a conflicts log entry:
   • Create an item in “Conflicts Log” with MatterID, matches (JSON), preliminary score, and timestamp.
6. Route for human review:
   • Use “Create an approval” (Teams Approvals or Outlook) with summary of matches and score.
   • Attach a link to the Matter Intake item for context.
7. Post to Teams:
   • Send an Adaptive Card to the Conflicts channel summarizing the match list with buttons (Approve, Escalate, Decline).
8. Record the decision:
   • On approval outcome, update Matter Intake: ConflictsStatus and ConflictsNotes.
   • Update the Conflicts Log with the reviewer, final decision, and comments.
9. Notify the requester:
   • Send a Teams message or email with the decision and next steps. Include standard language if escalated or declined.
10. Optional: build an ethical wall:
    • If decision = Cleared with restrictions, add parties to an Ethical Wall list and trigger separate flows to restrict Teams/SharePoint access.

This flow can be implemented in a day and continuously improved with better scoring, AI-assisted matching, and additional controls.

Compliance, Risk, and Ethical Walls with Microsoft 365

Automating conflict checks is as much about governance as it is about speed. Microsoft 365 provides security and compliance features that strengthen the ethical framework.

• Sensitivity labels: Apply labels to the Matter Intake and Conflicts Log sites/lists; restrict external sharing and enforce encryption.
• Data Loss Prevention (DLP): Create policies to prevent copying sensitive details outside sanctioned locations.
• Retention & records: Use retention labels to ensure logs are preserved for regulatory and malpractice defense timelines.
• Audit & eDiscovery: Enable unified audit; use Purview eDiscovery (Standard/Premium) to search conflict decisions and approvals.
• Ethical walls: Use separate team sites with restricted membership, private channels, and sensitivity labels. Consider Microsoft Information Barriers (where available) or well-governed site permissions to partition access.

Best-in-class conflict systems pair automation with governance. Set your defaults to “secure,” route ambiguous cases to humans, and let the system do the heavy lifting of data collection, search, and logging.

Integrating AI for Smarter Matching

AI enhances conflict checks by improving name matching, expanding aliases, and extracting entities from free text. You can incorporate AI safely and pragmatically:

• AI Builder (Power Platform): Use AI Models for entity extraction on MatterDescription to identify people, companies, and locations.
• Fuzzy matching: Create a Power Automate “HTTP” call to an Azure Function or Logic App implementing phonetic algorithms (e.g., Soundex, Metaphone) or string similarity (Levenshtein). Store and reuse scores.
• Copilot Studio: Build a secure bot confined to your SharePoint data to answer “Do we have a conflict with X?” with traceable citations.
• Azure OpenAI/Azure AI Language: Generate alias lists, normalize variations (e.g., d/b/a, f/k/a), and summarize rationale. Use tenant-governed models; disable data logging where needed.

Design principle: AI assists the reviewer; it does not make the final ethical determination.

User Experience in Teams and SharePoint

Adoption hinges on a simple, consistent experience for attorneys and conflicts staff.

• Guided intake: A Power Apps form on the Matter Intake list validates fields, prompts for aliases, and tags practice area and jurisdiction.
• Teams notifications: Adaptive Cards summarize potential conflicts with expand/collapse sections for “Exact matches,” “Alias matches,” and “Watchlist hits.”
• Approvals: One-click decisions with required comments for “Escalate/Decline.”
• Self-service search: A SharePoint page with a search web part and filters for entity type, practice area, and status.
• Attorney dashboard: Personalized view of submitted matters, status, and expected decision times.

ROI & Business Case

Automating conflict checks typically produces measurable gains in cycle time and reduction in rework, while improving risk posture.

Additional benefits include fewer missed conflicts, stronger auditability, and faster client onboarding—supporting revenue capture and client satisfaction.

Operational Playbook & Best Practices

• Start with governance: Establish policies for naming, aliases, retention, and review thresholds before launching automation.
• Normalize early: Compute normalized names at data entry to ensure consistent search across lists.
• Use tiers of review: Auto-clear low-risk matters; route medium/high scores to Conflicts with rationale.
• Index & scale: Index filter columns and use pagination; consider Dataverse or Azure Cognitive Search for very large datasets.
• Feedback loop: Let reviewers label false positives/negatives; refine scores and matching rules monthly.
• Measure and publish: Track cycle time, decision rates, escalations, and accuracy; review in monthly ops meetings.

Automate the repetitive. Escalate the ambiguous. Document everything. This triad keeps your conflicts process fast, defensible, and continuously improving.

Future Trends in Automated Conflict Checking

The next wave of legal automation brings deeper context and proactive prevention:

• Graph-powered insights: Using Microsoft 365 Graph signals (e.g., recent communications) to flag potential internal relationships relevant to conflicts.
• Continuous monitoring: Post-onboarding checks that scan new parties entering related matters and alert to emerging conflicts.
• Policy-aware workspaces: Matter sites provisioned with templated permissions and labels based on conflict decisions, reducing manual setup.
• Explainable AI: Human-readable rationales for matches with linked sources, bolstering defensibility.

Key Metrics & Reporting

• Cycle time to decision (median, 90th percentile)
• Percent auto-cleared vs. escalated
• False positive and false negative rates (from reviewer feedback)
• Matters per conflicts analyst per week
• Compliance coverage: percent of matters with complete logs and approvals

Build a Power BI dashboard connected to SharePoint Lists to publish these KPIs to leadership and practice heads.

Microsoft 365 & Power Platform Use Cases That Complement Conflict Checks

• Client Onboarding & Communication: Automate welcome packets, engagement letters, and identity verification tasks.
• Case/Matter Management: Provision matter sites with templates, labels, and task plans post-conflict clearance.
• Compliance & Risk Monitoring: Watchlist scans, sanctions checks, and ethical wall enforcement across Teams and SharePoint.
• Document Automation: Generate letters of engagement based on intake metadata using Word templates and Power Automate.

With these components working together, conflict checks become a dependable, auditable step—rather than a bottleneck.

In summary, automating client conflict checks in SharePoint Lists with Power Automate delivers faster decisions, consistent execution, and stronger compliance. By designing a clear data model, orchestrating reviews in Teams, and layering governance with Microsoft Purview, legal teams can reduce risk while improving client service. Add AI prudently to enhance matching and explanations, and measure outcomes to keep improving. The result is a scalable, defensible conflicts program aligned with modern legal operations.

Ready to explore how Microsoft automation can streamline your firm’s legal workflows? Reach out to A.I. Solutions today for expert guidance and tailored strategies.