top of page

How AI Is Mapping Regulatory Obligations for High-Growth Fintechs (The Demo Room #13)

  • Writer: Nathan Parker
    Nathan Parker
  • 4 days ago
  • 4 min read

Updated: 7 minutes ago

Blue background featuring "The Demo Room" Episode 13 title about AI in fintech. Highlights CEO’s photo and Cardamon logo. Parker & Lawrence Research noted.

Welcome to The Demo Room – your front-row seat to the future of RegTech, RiskTech, and AI innovation. 

In this series, we document our research interviews with the most forward-thinking vendors tackling the industry's biggest challenges. Each blog is built around a comprehensive product demo, providing clear insights into how these innovations address industry challenges.


On this occasion, we met with Areg Nzsdejan, CEO at Cardamon, to discuss how their AI automates regulatory compliance workflows for multi-jurisdictional financial services companies 

-

The volume of new regulations is increasing at an unprecedented rate, creating a density of obligations that manual processes cannot withstand. For compliance officers, the pressure is relentless: 64% of banking respondents in a recent risk survey cited "managing evolving regulatory change" as a high-priority concern, and 61% see reduced regulatory burdens as somewhat or very unlikely. 


This friction is especially troublesome for new, high-growth firms that aim to capitalise on rapid expansion opportunities, while still carrying relatively immature risk and compliance functions.  The collapse of Synapse Financial Technologies in 2024 serves as a warning; its failure to reconcile ledgers and maintain compliance controls left up to $96 million in customer funds unaccounted for, stranding over 100,000 customers and triggering intense regulatory scrutiny. And among countless other examples, German banking-as-a-service leader Solaris faced a severe growth bottleneck when the regulator BaFin blocked it from onboarding new customers without specific permission until its AML controls were remediated. These challenges represent existential threats that freeze product launches and erode valuation overnight.


The core challenge of mapping regulatory obligations lies in the lack of harmonisation: fintechs expanding across borders face a web of overlapping and divergent regulations. One example is the widening gap in crypto asset regulation. While the EU has harmonised rules under MiCA, firms operating in the US still navigate a fragmented enforcement-driven model that lacks a unified federal framework.


The Problem for Firms

Despite a reputation for speed and innovation, many fintechs still rely on spreadsheets, newsletters, and manual reviews to manage compliance. While some firms use technology for high-level horizon scanning or GRC dashboards, the detailed work of regulatory obligation mapping remains largely untouched by automation.


Automation at this level of granularity is exceptionally difficult to get right. Consequently, expensive and highly skilled teams are stuck in manual loops, leaving firms exposed to regulatory fines or operational bans. 


  • 98% of financial institutions in EMEA reported that their compliance costs rose in the last year;

  • 72% specifically cite rising labor costs as a primary driver;

  • Which is supported by the separate findings that the number of employee hours dedicated to regulatory activities increased by 61% from 2016 to 2023.


Ultimately, this hinders the very firms that need to be accelerating through their most critical phase of growth.


A Solution: Mapping Regulatory Obligations With AI

Cardamon’s platform addresses this by automating the end-to-end regulatory lifecycle, from horizon scanning and obligation mapping to gap analysis and policy creation, turning dense regulatory texts into structured, actionable outputs.


The platform parses regulations line by line, transposing obligations into a unified format and mapping them directly to a client’s specific products, licenses, and existing policies. Cardamon stands out by moving beyond simple summarisation; for every clause, its AI determines applicability, evaluates severity, and classifies the text as a hard obligation, a guideline, or merely context. This allows compliance teams to filter instantly to the provisions that matter most.


Crucially, Cardamon goes beyond identification to remediation. The platform runs gap analyses against the firm’s own procedures, identifying areas of insufficient coverage and generating draft policy language or controls to fix the gaps.


This workflow is supported by a "human-in-the-loop" philosophy designed for safety and auditability:


  • Transparent Decisioning: Every AI decision is accompanied by citations and hover-over explanations, allowing officers to verify the reasoning behind a recommendation.

  • Constraint-Based Chat: The interactive chat model is limited to mapped regulations and client context. It will only respond to questions for which it has referenceable answers, minimising the risk of hallucination.

  • Structured Generation: The platform generates missing policy statements and control descriptions based on identified gaps, but relies on a calibrated blend of AI techniques to ensure these outputs are grounded in the regulatory text.


By automating these complex, high-value workflows, Cardamon helps firms move beyond experimental pilots and deliver the tangible ROI that our research identifies as the critical next step for the industry.


Parker & Lawrence's View

We expect Cardamon to continue building momentum among financial services firms scaling rapidly across borders, as well as regulated enterprises beginning to confront AI governance obligations. Their advantages lie in first-mover depth in obligation mapping, an AI-native architecture, and a pragmatic philosophy that balances automation with auditability.


The key differentiator for AI in compliance lies not in the underlying model, but in the infrastructure and guardrails wrapped around it. Without this scaffolding, general-purpose models would already be competitive RegTech solutions. Cardamon’s value is in the "rails," not just the model, focusing on context, constraints, and auditability to make outputs reliable and actionable.


Challenges will include navigating long enterprise sales cycles and standing apart in a market where larger incumbents are increasingly investing in AI capabilities. But with a strong product and clear early traction, Cardamon is well positioned to become a leader in regulatory obligations mapping and broader compliance management.


Get Involved

Are you ready to become a thought leader? Reach out to discuss our ongoing research initiatives, how they impact your firm and where we can work together to position you at the forefront of your industry.



bottom of page