Why Choose CompatibL AI
We are often impressed with clever responses of chat applications based on large language models (LLMs). However, a lot of research and engineering must be added before LLMs can become reliable and trusted components of enterprise trading and risk applications.
Based on our extensive research on LLM applications to quant finance presented at major industry conferences, CompatibL developed a suite of tools and components for building and validating reliable AI-based workflows and digital assistant applications, earning recognition and awards from leading industry outlets such as Risk.net, Waterstechnology and WBS.
To be clear, we do not propose that AI replaces humans in any trading or risk management task. Rather, our CompatibL AI works alongside humans to make their job less tedious and more rewarding.
CompatibL AI for Quant Finance
- Document Advisor AI
- Compliance Advisor AI
- Legal Advisor AI
- What-if Advisor AI
- Relevance Ranking
- Incident Categorization
- AI Model Governance
- AI Assistant
- Data Cleaning
Document Advisor AI
Document Advisor AI for document analysis leverages an AI-based workflow for finding the most relevant news articles, legal filings, or internal documents in a large document repository. It supports precisely defined relevance criteria that cannot be implemented by keyword or vector (embedding) database search.
The module can identify and mitigate potential sources of counterparty risk, reputational risk, and other adverse outcomes. It provides a detailed explanation of why the document was deemed relevant to the search criteria and justification for its ranking within the search results.
Independent testing has demonstrated that CompatibL’s AI-based ranking approach outperforms other AI-based search and ranking methods.
Compliance Advisor AI
Compliance Advisor is an AI compliance solution for banks that leverages an AI-based workflow to identify and analyze the legal language related to specific regulatory requirements. It mitigates the risk of operational errors in the regulatory compliance screening process by automatically extracting, analyzing, ranking and highlighting clauses that influence compliance or non-compliance with the relevant regulation in documents such as security offerings, prospectuses, client communications and others.
The solution identifies distinct legal clauses within the document and provides an AI-generated summary of findings for each clause and ranks its relevance to compliance or non-compliance. After this, it follows a sophisticated decision tree to analyze the compliance or non-compliance criteria within the relevant regulations and provides a detailed justification for the decision. It uses CompatibL AI to identify, extract, and contextualize key clauses within large legal documents, enabling legal and compliance teams to easily review and approve AI recommendations.
Compliance Advisor AI provides a much-needed second line of defense against operational errors in regulatory compliance processes while ensuring human professionals remain the final arbiters of compliance decisions. This hybrid approach aligns with emerging regulatory expectations around AI governance, transparency, and accountability.
Legal Advisor AI
Legal Advisor AI is a solution for AI-based legal document analysis. Our clients use it to validate legal analysis by humans, or to provide a draft analysis that puts the relevant legal clauses and the proposed findings at the fingertips of the human legal expert for a fast review and approval.
What-if Advisor AI
What-If Advisor an AI solution for operational risk mitigation that uses a highly reliable workflow based on AI for what-if trading analysis to identify and mitigate operational errors in what-if analysis. It is a critical bank function that involves assessing the impact of a potential new trade on the bank’s market risk, credit risk, and trading limits before it can be executed. It requires rapid trade entry from trader chat, email or voice and calculating risk and capital requirements for the prospective trade.
The what-if process has a higher rate of operational errors than other trading desk functions due to the time pressure and complexity of the trade representation format. The time-critical nature of this task and the tremendous cost of making an error take a high toll on the quants and analysts performing trade entry.
Relevance Ranking
The Relevance Ranking solution leverages an AI-based workflow for finding the most relevant news articles, legal filings, or internal documents in a large document repository. This hybrid AI-human decision-making solution for finance supports precisely defined relevance criteria that cannot be implemented by either keyword search or vector (embedding) database search. The solution can be used to identify and mitigate potential sources of counterparty risk, reputational risk, and other adverse outcomes.
The ranking is based on CompatibL’s award-winning AI research to ensure accurate comparison of ranked documents at minimal cost. It outperforms both the traditional keyword-based search and the vector database-based RAG by wide margins thanks to its ability to follow detailed user guidance when evaluating the relevance.
The solution performs multi-step ranking and generates an AI-based summary of each document and provides a detailed explanation of why the document was deemed relevant to the search criteria and justification for its ranking. It can also assign one or more categories to the document, and determine its key subjects (e.g., company, counterparty, etc.). The input can be in text, PDF, or scanned image form.
Incident Categorization
The Incident Categorization uses AI for operational risk mitigation and a sophisticated multistep AI-based workflow to automate categorization of new incidents and recategorization of historical incidents in response to regulatory changes. The system ensures high accuracy in assigning categories and providing justifications for each categorization, allowing for a seamless and adaptive categorization process.
Evolving regulations require banks and asset managers to periodically recategorize historical operational risk incidents based on new rules. The solution can propose the categorization for human approval (Copilot mode) or review manual recategorization results to mitigate the risk of human error (OpRisk mode).
A multi-step AI-based workflow analyzes the incident description and associated data to determine if any changes to the incident categorization are required under the new regulations. Each category change is accompanied by a clear justification, giving users transparency into how and why the category was amended. The solution includes a full audit log and detailed dashboards for categorization accuracy measurement and monitoring.
AI Model Governance
An AI-based solution that looks at every line of source code and every version control log message, performs an in-depth analysis of the prior documentation and release notes, and creates actionable dashboards of recommended changes to ensure compliance with model risk regulations.
As a business function that involves dealing with extraordinarily large volumes of natural language text (model documents) and source code (model libraries), model governance is uniquely suited for the application of LLMs.
CompatibL’s AI Model Governance performs labor-intensive and time-consuming work that would be unfeasible for a purely human team without AI assistance. It can look at every line of source code and every version control log message, perform an in-depth analysis of the prior documentation and release notes, and integrate all this data in a nuanced and sophisticated way. It can also cross reference the resulting documents with the specific lines of source code – something that is tremendously helpful to the bank examiners and internal risk control function, but rarely done because of the time and effort involved.
AI Assistant
CompatibL’s AI digital assistant for finance is a digital assistant to answer questions about the data in your existing systems and databases across the enterprise. It integrates your existing databases and IT infrastructure and does not require migrating the data to a separate data repository for AI. This includes predefined experts trained to accurately describe the data in trading, risk, and compliance systems.
Data Cleaning
Data cleaning involves identifying and mitigating bad data points in time series or erroneous reference data. CompatibL’s solution uses AI to identify the information relevant to a specific data point in the news feed or historical news or document repository.
With the benefit of additional context provided by CompatibL AI, plausible reasons for the outlier can be positively identified or eliminated, aiding in the final determination of whether or not the data point is valid.
Choose Between Proprietary Cloud and Open-Source LLM Families
CompatibL AI offers a strategic choice between the industry’s two primary LLM paths: high-performance Proprietary Cloud Families for cutting-edge multimodal reasoning, and Open-Source Model Families for maximum flexibility and data sovereignty. Whether you leverage the power of GPT-5, Claude 5, and Gemini 3 within secure enterprise clouds or deploy Llama 4, Mistral 3, or Qwen 3 on your own infrastructure, we ensure your AI strategy is built on a foundation of security and control.
The strategic partnerships between model providers and major cloud platforms, such as Microsoft and OpenAI (GPT-5), Anthropic and AWS/Google (Claude 5), and Google (Gemini 3), enable access to frontier multimodal intelligence within your existing enterprise environment.
If your firm already operates within Azure, AWS, or Google Cloud, these models integrate directly with your established security and compliance frameworks. Your data remains protected: it is never shared with the model providers, nor is it used for training, ensuring your enterprise-grade data protection policies remain fully intact.
The release of high-performance open-source families, including Meta’s Llama 4, Mistral 3, and Qwen 3, combined with a robust global ecosystem, provides a powerful alternative to proprietary APIs that can be deployed on-premises or in a private cloud.
Choosing an open-source approach grants your firm complete lifecycle independence and data sovereignty. These models allow you to host the entire AI stack within your own firewall, eliminating the need to rely on third-party security guarantees. While proprietary models lead in general benchmarks, modern open-source LLMs offer sufficient capability for most business use cases while providing total control over versioning, patching, and hardware optimization.
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