Best AI tools for< Assess Risk >

MindBridge is a global leader in financial risk discovery and anomaly detection. The MindBridge AI Platform drives insights and assesses risks across critical business operations. It offers various products like General Ledger Analysis, Company Card Risk Analytics, Payroll Risk Analytics, Revenue Risk Analytics, and Vendor Invoice Risk Analytics. With over 250 unique machine learning control points, statistical methods, and traditional rules, MindBridge is deployed to over 27,000 accounting, finance, and audit professionals globally.

Pascal is an AI-powered risk-based KYC & AML screening and monitoring platform that offers users a faster and more accurate way to assess findings compared to other compliance tools. It leverages AI, machine learning, and Natural Language Processing to analyze open-source and client-specific data, providing insights to identify and assess risks. Pascal simplifies onboarding processes, offers continuous monitoring, reduces false positives, and enables better decision-making through its intuitive interface. It promotes collaboration among different stakeholders and ensures transparency in compliance procedures.

SWMS AI is an AI-powered safety risk assessment tool that helps businesses streamline compliance and improve safety. It leverages a vast knowledge base of occupational safety resources, codes of practice, risk assessments, and safety documents to generate risk assessments tailored specifically to a project, trade, and industry. SWMS AI can be customized to a company's policies to align its AI's document generation capabilities with proprietary safety standards and requirements.

CyberRiskAI.com is a website that is currently under development and is registered at Dynadot.com. The website is expected to offer services related to cyber risk management and artificial intelligence in the future. With a focus on cybersecurity and risk assessment, CyberRiskAI.com aims to provide innovative solutions to help businesses mitigate cyber threats and protect their digital assets. The platform is designed to leverage AI technologies to analyze and predict cyber risks, enabling users to make informed decisions to enhance their security posture.

Cleerly is a digital healthcare company transforming the way clinicians approach the treatment of heart disease. Our clinically-proven, AI-based digital care platform works with coronary computed tomography angiography (CCTA) imaging to help clinicians precisely identify and define atherosclerosis earlier, so they can provide personalized, life-saving treatment plans for all patients throughout their care continuum. We measure atherosclerosis - plaque build-up in the heart's arteries - not indirect markers such as risk factors and symptoms of disease. Our AI-enabled digital care pathway offers simpler, faster, more accurate heart disease evaluation and reporting that's tailored to each stakeholder, improving overall clinical and financial outcomes.

Archistar is a leading property research platform in Australia that empowers users to make confident and compliant property decisions with the help of data and AI. It offers a range of features, including the ability to find and assess properties, generate 3D design concepts, and minimize risk and maximize return on investment. Archistar is trusted by over 100,000 individuals and 1,000 leading property firms.

CUBE3.AI is a real-time crypto fraud prevention tool that utilizes AI technology to identify and prevent various types of fraudulent activities in the blockchain ecosystem. It offers features such as risk assessment, real-time transaction security, automated protection, instant alerts, and seamless compliance management. The tool helps users protect their assets, customers, and reputation by proactively detecting and blocking fraud in real-time.

Lumenova AI is an AI platform that focuses on making AI ethical, transparent, and compliant. It provides solutions for AI governance, assessment, risk management, and compliance. The platform offers comprehensive evaluation and assessment of AI models, proactive risk management solutions, and simplified compliance management. Lumenova AI aims to help enterprises navigate the future confidently by ensuring responsible AI practices and compliance with regulations.

ClearAI is an AI-powered platform that offers instant extraction of insights, effortless document navigation, and natural language interaction. It enables users to upload PDFs securely, ask questions, and receive accurate responses in seconds. With features like structured results, intelligent search, and lifetime access offers, ClearAI simplifies tasks such as analyzing company reports, risk assessment, audit support, contract review, legal research, and due diligence. The platform is designed to streamline document analysis and provide relevant data efficiently.

ISMS Copilot is an AI-powered assistant designed to simplify ISO 27001 preparation for both experts and beginners. It offers various features such as ISMS scope definition, risk assessment and treatment, compliance navigation, incident management, business continuity planning, performance tracking, and more. The tool aims to save time, provide precise guidance, and ensure ISO 27001 compliance. With a focus on security and confidentiality, ISMS Copilot is a valuable resource for small businesses and information security professionals.

Clarity AI is an AI-powered technology platform that offers a Sustainability Tech Kit for sustainable investing, shopping, reporting, and benchmarking. The platform provides built-in sustainability technology with customizable solutions for various needs related to data, methodologies, and tools. It seamlessly integrates into workflows, offering scalable and flexible end-to-end SaaS tools to address sustainability use cases. Clarity AI leverages powerful AI and machine learning to analyze vast amounts of data points, ensuring reliable and transparent data coverage. The platform is designed to empower users to assess, analyze, and report on sustainability aspects efficiently and confidently.

Castello.ai is a financial analysis tool that uses artificial intelligence to help businesses make better decisions. It provides users with real-time insights into their financial data, helping them to identify trends, risks, and opportunities. Castello.ai is designed to be easy to use, even for those with no financial background.

DataSnack is a real-time, AI-driven due diligence platform that helps you make better decisions faster. With DataSnack, you can access a wealth of data and insights on companies, industries, and markets, all in one place. Our AI-powered platform analyzes data from a variety of sources, including news, social media, and financial filings, to provide you with the most up-to-date and relevant information. With DataSnack, you can:

Jumio is a leading digital identity verification platform that offers AI-driven services to verify the identities of new and existing users, assess risk, and help meet compliance mandates. With over 1 billion transactions processed, Jumio provides cutting-edge AI and ML models to detect fraud and maintain trust throughout the customer lifecycle. The platform offers solutions for identity verification, predictive fraud insights, dynamic user experiences, and risk scoring, trusted by global brands across various industries.

Power PM AI is an advanced project management tool that leverages artificial intelligence to streamline project planning, execution, and monitoring. It offers a user-friendly interface with powerful features to help project managers optimize their workflows and make data-driven decisions. With intelligent automation and predictive analytics, Power PM AI enhances project efficiency and reduces risks. The tool is designed to cater to various industries and project sizes, making it a versatile solution for teams and organizations seeking to improve project outcomes.

Underwrite.ai is a platform that leverages advances in artificial intelligence and machine learning to provide lenders with nonlinear, dynamic models of credit risk. By analyzing thousands of data points from credit bureau sources, the application accurately models credit risk for consumers and small businesses, outperforming traditional approaches. Underwrite.ai offers a unique underwriting methodology that focuses on outcomes such as profitability and customer lifetime value, allowing organizations to enhance their lending performance without the need for capital investment or lengthy build times. The platform's models are continuously learning and adapting to market changes in real-time, providing explainable decisions in milliseconds.

BCT Digital is an AI-powered risk management suite provider that offers a range of products to help enterprises optimize their core Governance, Risk, and Compliance (GRC) processes. The rt360 suite leverages next-generation technologies, sophisticated AI/ML models, data-driven algorithms, and predictive analytics to assist organizations in managing various risks effectively. BCT Digital's solutions cater to the financial sector, providing tools for credit risk monitoring, early warning systems, model risk management, environmental, social, and governance (ESG) risk assessment, and more.

Quantifind is an AI-powered financial crimes automation platform that specializes in Anti-Money Laundering (AML) and Know Your Customer (KYC) solutions. It offers end-to-end automation impact, best-in-class accuracy, and powerful APIs and applications for risk screening, investigations, and compliance in the financial services and public sector industries. Quantifind's Graphyte platform leverages AI and external data to streamline AML-KYC processes, providing comprehensive data coverage, dynamic risk typologies, and seamless integrations with case management systems.

Flagright is an AI-native AML compliance and risk management solution designed for EU and UK fintech startups. It offers a comprehensive platform for screening, monitoring, and investigating AML compliance and fraud cases using AI technology. The platform provides real-time transaction monitoring, automated case management, AI forensics for screening, customer risk assessment, and sanctions screening. Flagright also offers integrations, notifications, bad actor database, CRM, KYB & ID verification, and professional services for tailored AML program design and support. Trusted by financial institutions across 6 continents, Flagright is a modern standard for financial crime compliance.

Shufti Pro is an award-winning global identity verification platform that provides businesses with a suite of tools to verify the identities of their customers. The platform uses artificial intelligence (AI) to automate the identity verification process, making it faster, more accurate, and more secure. Shufti Pro's solutions are used by businesses in a variety of industries, including banking, fintech, crypto, forex, gaming, insurance, education, healthcare, e-commerce, and travel.

CISO Assistant is a tool that helps organizations manage their cybersecurity posture and compliance. It provides a centralized platform for managing security controls, threats, and risks. CISO Assistant also includes a library of pre-built frameworks and tools to help organizations quickly and easily implement best practices.

FinRobot is an open-source AI agent platform designed for financial applications using large language models. It transcends the scope of FinGPT, offering a comprehensive solution that integrates a diverse array of AI technologies. The platform's versatility and adaptability cater to the multifaceted needs of the financial industry. FinRobot's ecosystem is organized into four layers, including Financial AI Agents Layer, Financial LLMs Algorithms Layer, LLMOps and DataOps Layers, and Multi-source LLM Foundation Models Layer. The platform's agent workflow involves Perception, Brain, and Action modules to capture, process, and execute financial data and insights. The Smart Scheduler optimizes model diversity and selection for tasks, managed by components like Director Agent, Agent Registration, Agent Adaptor, and Task Manager. The tool provides a structured file organization with subfolders for agents, data sources, and functional modules, along with installation instructions and hands-on tutorials.

The 'Awesome AI Guidelines' repository aims to simplify the ecosystem of guidelines, principles, codes of ethics, standards, and regulations around artificial intelligence. It provides a comprehensive collection of resources addressing ethical and societal challenges in AI systems, including high-level frameworks, principles, processes, checklists, interactive tools, industry standards initiatives, online courses, research, and industry newsletters, as well as regulations and policies from various countries. The repository serves as a valuable reference for individuals and teams designing, building, and operating AI systems to navigate the complex landscape of AI ethics and governance.

Fairlearn is a Python package designed to help developers assess and mitigate fairness issues in artificial intelligence (AI) systems. It provides mitigation algorithms and metrics for model assessment. Fairlearn focuses on two types of harms: allocation harms and quality-of-service harms. The package follows the group fairness approach, aiming to identify groups at risk of experiencing harms and ensuring comparable behavior across these groups. Fairlearn consists of metrics for assessing model impacts and algorithms for mitigating unfairness in various AI tasks under different fairness definitions.

Dioptra is a software test platform for assessing the trustworthy characteristics of artificial intelligence (AI). It supports the NIST AI Risk Management Framework by providing functionality to assess, analyze, and track identified AI risks. Dioptra provides a REST API and can be controlled via a web interface or Python client for designing, managing, executing, and tracking experiments. It aims to be reproducible, traceable, extensible, interoperable, modular, secure, interactive, shareable, and reusable.

R-Judge is a benchmarking tool designed to evaluate the proficiency of Large Language Models (LLMs) in judging and identifying safety risks within diverse environments. It comprises 569 records of multi-turn agent interactions, covering 27 key risk scenarios across 5 application categories and 10 risk types. The tool provides high-quality curation with annotated safety labels and risk descriptions. Evaluation of 11 LLMs on R-Judge reveals the need for enhancing risk awareness in LLMs, especially in open agent scenarios. Fine-tuning on safety judgment is found to significantly improve model performance.

Do-Not-Answer is an open-source dataset curated to evaluate Large Language Models' safety mechanisms at a low cost. It consists of prompts to which responsible language models do not answer. The dataset includes human annotations and model-based evaluation using a fine-tuned BERT-like evaluator. The dataset covers 61 specific harms and collects 939 instructions across five risk areas and 12 harm types. Response assessment is done for six models, categorizing responses into harmfulness and action categories. Both human and automatic evaluations show the safety of models across different risk areas. The dataset also includes a Chinese version with 1,014 questions for evaluating Chinese LLMs' risk perception and sensitivity to specific words and phrases.

Academic_LLM_Sec_Papers is a curated collection of academic papers related to LLM Security Application. The repository includes papers sorted by conference name and published year, covering topics such as large language models for blockchain security, software engineering, machine learning, and more. Developers and researchers are welcome to contribute additional published papers to the list. The repository also provides information on listed conferences and journals related to security, networking, software engineering, and cryptography. The papers cover a wide range of topics including privacy risks, ethical concerns, vulnerabilities, threat modeling, code analysis, fuzzing, and more.

PyRIT is an open access automation framework designed to empower security professionals and ML engineers to red team foundation models and their applications. It automates AI Red Teaming tasks to allow operators to focus on more complicated and time-consuming tasks and can also identify security harms such as misuse (e.g., malware generation, jailbreaking), and privacy harms (e.g., identity theft). The goal is to allow researchers to have a baseline of how well their model and entire inference pipeline is doing against different harm categories and to be able to compare that baseline to future iterations of their model. This allows them to have empirical data on how well their model is doing today, and detect any degradation of performance based on future improvements.

The LLMEvaluation repository is a comprehensive compendium of evaluation methods for Large Language Models (LLMs) and LLM-based systems. It aims to assist academics and industry professionals in creating effective evaluation suites tailored to their specific needs by reviewing industry practices for assessing LLMs and their applications. The repository covers a wide range of evaluation techniques, benchmarks, and studies related to LLMs, including areas such as embeddings, question answering, multi-turn dialogues, reasoning, multi-lingual tasks, ethical AI, biases, safe AI, code generation, summarization, software performance, agent LLM architectures, long text generation, graph understanding, and various unclassified tasks. It also includes evaluations for LLM systems in conversational systems, copilots, search and recommendation engines, task utility, and verticals like healthcare, law, science, financial, and others. The repository provides a wealth of resources for evaluating and understanding the capabilities of LLMs in different domains.

Awesome-LLM-in-Social-Science is a repository that compiles papers evaluating Large Language Models (LLMs) from a social science perspective. It includes papers on evaluating, aligning, and simulating LLMs, as well as enhancing tools in social science research. The repository categorizes papers based on their focus on attitudes, opinions, values, personality, morality, and more. It aims to contribute to discussions on the potential and challenges of using LLMs in social science research.

Giskard is an open-source Python library that automatically detects performance, bias & security issues in AI applications. The library covers LLM-based applications such as RAG agents, all the way to traditional ML models for tabular data.

PIXIU is a project designed to support the development, fine-tuning, and evaluation of Large Language Models (LLMs) in the financial domain. It includes components like FinBen, a Financial Language Understanding and Prediction Evaluation Benchmark, FIT, a Financial Instruction Dataset, and FinMA, a Financial Large Language Model. The project provides open resources, multi-task and multi-modal financial data, and diverse financial tasks for training and evaluation. It aims to encourage open research and transparency in the financial NLP field.

OpenShield is a firewall designed for AI models to protect against various attacks such as prompt injection, insecure output handling, training data poisoning, model denial of service, supply chain vulnerabilities, sensitive information disclosure, insecure plugin design, excessive agency granting, overreliance, and model theft. It provides rate limiting, content filtering, and keyword filtering for AI models. The tool acts as a transparent proxy between AI models and clients, allowing users to set custom rate limits for OpenAI endpoints and perform tokenizer calculations for OpenAI models. OpenShield also supports Python and LLM based rules, with upcoming features including rate limiting per user and model, prompts manager, content filtering, keyword filtering based on LLM/Vector models, OpenMeter integration, and VectorDB integration. The tool requires an OpenAI API key, Postgres, and Redis for operation.

This repository provides a curated list of papers, datasets, and resources related to the detection and mitigation of hallucinations in large language models (LLMs). Hallucinations refer to the generation of factually incorrect or nonsensical text by LLMs, which can be a significant challenge for their use in real-world applications. The resources in this repository aim to help researchers and practitioners better understand and address this issue.

A repository that lists papers related to Large Language Model (LLM) based agents. The repository covers various topics including survey, planning, feedback & reflection, memory mechanism, role playing, game playing, tool usage & human-agent interaction, benchmark & evaluation, environment & platform, agent framework, multi-agent system, and agent fine-tuning. It provides a comprehensive collection of research papers on LLM-based agents, exploring different aspects of AI agent architectures and applications.

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