RegTech

RegTech is not optional for regulated institutions. It is purchased to reduce enforcement risk, meet reporting obligations, and operationalize compliance workflows. Institutionally, the market is underwritten by auditability, accuracy, integration, and buyer urgency, not UI or “AI” claims.

From an allocator perspective, regtech affects:

• budget durability (compliance is non-discretionary),
• operational load (false positives and manual reviews),
• audit and evidence trails, and
• integration into core systems (data sources, identity, transactions).

How allocators define regtech risk drivers

Allocators segment regtech credibility by:

• Use case: KYC/AML, sanctions, transaction monitoring, GRC, reporting automation
• Accuracy and burden: false positives, false negatives, review workload
• Auditability: explainability, evidence trails, model governance
• Integration depth: data ingestion, core banking, payment rails, case management tools
• Regulatory alignment: jurisdictional requirements and update velocity
• Procurement reality: security reviews, vendor risk management, implementation timelines
• Evidence phrases: “sanctions screening,” “transaction monitoring,” “KYC automation,” “GRC,” “audit trail”

Allocator framing:
“Does this regtech reduce compliance risk and operational burden with audit-grade evidence—or does it create noise and workflow friction?”

Where regtech sits in allocator portfolios

• strong thematic area within fintech and enterprise software
• demand reinforced by enforcement actions and evolving sanctions regimes
• increasingly intersects with AI/ML for automation—while auditability becomes more important

How regtech impacts outcomes

• durable revenue when embedded into compliance workflows
• churn risk if false positives create operational overload
• long sales cycles due to vendor risk and regulatory scrutiny
• high switching costs once integrated and trusted

How allocators evaluate regtech companies

Conviction increases when:

• the product is audit-grade with evidence trails
• accuracy reduces manual work measurably
• integration is deep and sticky
• the company keeps pace with regulatory changes
• buyer urgency is clear and budgets are stable

What slows allocator decision-making

• insufficient proof of accuracy and workload reduction
• unclear auditability and governance posture
• implementation complexity with weak time-to-value
• reliance on “AI” claims without validation

Common misconceptions

• “Compliance software sells itself” → procurement and implementation can be heavy.
• “AI reduces compliance cost automatically” → auditability and false positives often dominate.
• “Sanctions is a feature” → sanctions workflows can be enterprise-grade programs.

Key allocator questions

• What is the measured false-positive rate reduction vs incumbents?
• How do you provide audit trails and explainability?
• What systems do you integrate with and how long is implementation?
• How quickly do you update rules/models for regulatory changes?
• What is your evidence of renewal durability and switching costs?