Best AI tools for< Detect Fraud Patterns >

Sardine is an AI-powered platform for fraud prevention and compliance. It offers a comprehensive suite of products to help banks, retailers, and fintechs detect fraud patterns, prevent money laundering, and stop sophisticated scams. Sardine combines deep device intelligence, behavior biometrics, and identity signals to provide a precise risk score for every customer interaction. The platform also features machine learning models, a rules engine, network graph analysis, anomaly detection, and generative AI capabilities to fight modern threats. Sardine helps reduce fraud rates, decrease false positives, and streamline risk operations with its fully integrated solutions.

Arya.ai is an AI tool designed for Banks, Insurers, and Financial Services to deploy safe, responsible, and auditable AI applications. It offers a range of AI Apps, ML Observability Tools, and a Decisioning Platform. Arya.ai provides curated APIs, ML explainability, monitoring, and audit capabilities. The platform includes task-specific AI models for autonomous underwriting, claims processing, fraud monitoring, and more. Arya.ai aims to facilitate the rapid deployment and scaling of AI applications while ensuring institution-wide adoption of responsible AI practices.

Ai-SPY is an AI audio detection tool that offers a highly accurate Audio AI Detection System. It was trained on tens of millions of samples to discern between genuine and machine patterned waveforms. Users can upload audio files to determine if they were AI or human-generated. Ai-SPY helps authenticate audio content, protect copyright, mitigate reputational risks, and guard against potential fraud.

Fraud.net is an AI-powered fraud detection and prevention platform designed for enterprises. It offers a comprehensive and customizable solution to manage and prevent various types of fraud, such as account takeover, application fraud, and payment fraud. The platform utilizes AI and machine learning technologies to provide real-time monitoring, analytics, and reporting, helping businesses reduce fraud losses and improve customer trust. Fraud.net is trusted by various industries, including financial services, e-commerce, gaming, government, and insurance, to combat fraud schemes and ensure secure transactions.

DataVisor is a modern, end-to-end fraud and risk SaaS platform powered by AI and advanced machine learning for financial institutions and large organizations. It helps businesses combat various fraud and financial crimes in real time. DataVisor's platform provides comprehensive fraud detection and prevention capabilities, including account onboarding, application fraud, ATO prevention, card fraud, check fraud, FinCrime and AML, and ACH and wire fraud detection. The platform is designed to adapt to new fraud incidents immediately with real-time data signal orchestration and end-to-end workflow automation, minimizing fraud losses and maximizing fraud detection coverage.

DataVisor is a modern, end-to-end fraud and risk SaaS platform powered by AI and advanced machine learning for financial institutions and large organizations. It provides a comprehensive suite of capabilities to combat a variety of fraud and financial crimes in real time. DataVisor's hyper-scalable, modern architecture allows you to leverage transaction logs, user profiles, dark web and other identity signals with real-time analytics to enrich and deliver high quality detection in less than 100-300ms. The platform is optimized to scale to support the largest enterprises with ultra-low latency. DataVisor enables early detection and adaptive response to new and evolving fraud attacks combining rules, machine learning, customizable workflows, device and behavior signals in an all-in-one platform for complete protection. Leading with an Unsupervised approach, DataVisor is the only proven, production-ready solution that can proactively stop fraud attacks before they result in financial loss.

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.

Deepfake Detector is an AI tool designed to identify deepfake audio and video content with 92% model accuracy. It helps individuals and businesses protect themselves from deepfake scams by analyzing voice messages and calls for authenticity. The tool offers probabilities as a guide for further investigation, ensuring credibility in media reporting and legal proceedings. With features like AI Noise Remover and easy API integration, Deepfake Detector is a market leader in detecting deepfakes and preventing financial losses.

ChainAware.ai is an AI-powered blockchain super tool designed for both users and businesses. It offers a range of features such as Wallet Auditor, Fraud Detector, and Rug Pull Detector to enhance security and trust in blockchain transactions. The tool provides predictive AI capabilities to prevent fraud and identify potential risks before they occur. Additionally, it offers business solutions including account-based user acquisition, web3 user analytics, and crypto fraud detection with AI. ChainAware.ai aims to revolutionize the way users interact with blockchain technology by providing advanced tools and services powered by artificial intelligence.

Unit21 is a customizable no-code platform designed for risk and compliance operations. It empowers organizations to combat financial crime by providing end-to-end lifecycle risk analysis, fraud prevention, case management, and real-time monitoring solutions. The platform offers features such as AI Copilot for alert prioritization, Ask Your Data for data analysis, Watchlist & Sanctions for ongoing screening, and more. Unit21 focuses on fraud prevention and AML compliance, simplifying operations and accelerating investigations to respond to financial threats effectively and efficiently.

LoginLlama is an AI-powered suspicious login detection tool designed for developers to enhance customer security effortlessly by preventing fraudulent logins. The tool evaluates login attempts based on various ranking factors, historic behavior, AI analysis, request origin, and user agent. It helps combat top login threats like unauthorized access, account takeover, credential stuffing, brute force attacks, phishing attacks, and insider threats. LoginLlama offers easy integration with REST API and official libraries for popular programming languages. It is made with ❤️ in the UK and is 100% independent and self-funded.

FOCAL is an AI-driven platform designed for AML compliance and anti-fraud purposes. It offers solutions for verification, customer due diligence, fraud prevention, and financial insights. The platform leverages AI technology to streamline onboarding processes, enhance trust through advanced customer screening, and detect and prevent fraud using advanced AI algorithms. FOCAL is tailored to meet industry-specific needs, provides seamless integration with existing systems, and offers localized expertise with global standards for regulatory compliance.

Subex is a Telecom AI company that enables Connected Experiences for CFOs, CTOs, and CMOs. With over 25 years of experience, Subex helps Communications Service Providers (CSPs) worldwide maximize revenues and profitability by leveraging AI to create connected experiences in business ecosystems. The company offers AI solutions, including Business Assurance, Fraud and Security management, Network Analytics, Enterprise Cybersecurity, Enterprise Billing, and more. Subex is trusted by over 75% of the world's top 50 telcos and provides a range of industry-leading solutions to enhance operational efficiency and effectiveness.

CARCO is an advanced Mobile AI Fraud Prevention application designed to protect insurance carriers and consumers by identifying and preventing risk events and fraudulent activities. The application streamlines the inspection process through integrated AI and fraud alert validation technology, providing a back-office solution that is easily integrated into mobile platforms, cost-effective, and fraud-detecting. CARCO also offers NMVTIS, a premier system in the U.S. that requires reporting of vehicle title data. With over 50 million transactions completed to date, CARCO has a proven track record in fraud prevention and risk mitigation for the insurance industry.

Brighterion AI, a Mastercard company, offers advanced AI solutions for financial institutions, merchants, and healthcare providers. With over 20 years of experience, Brighterion has revolutionized AI by providing market-ready models that enhance customer experience, reduce financial fraud, and mitigate risks. Their solutions are enriched with Mastercard's global network intelligence, ensuring scalability and powerful personalization. Brighterion's AI applications cater to acquirers, PSPs, issuers, and healthcare providers, offering custom AI solutions for transaction fraud monitoring, merchant monitoring, AML & compliance, and healthcare fraud detection. The company has received several prestigious awards for its excellence in AI and financial security.

hCaptcha Enterprise is a comprehensive AI-powered security platform designed to detect and deter human and automated threats, including bot detection, fraud protection, and account defense. It offers highly accurate bot detection, fraud protection without false positives, and account takeover detection. The platform also provides privacy-preserving abuse detection with zero personally identifiable information (PII) required. hCaptcha Enterprise is trusted by category leaders in various industries worldwide, offering universal support, comprehensive security, and compliance with global privacy standards like GDPR, CCPA, and HIPAA.

SymphonyAI offers AI SaaS solutions for financial crime prevention, helping organizations detect fraud, conduct customer due diligence, and prevent payment fraud. Their solutions leverage generative and predictive AI to enhance efficiency and effectiveness in investigating financial crimes. SymphonyAI's products cater to industries like banking, insurance, financial markets, and private banking, providing rapid deployment, scalability, and seamless integration to meet regulatory compliance requirements.

Onfido is a digital identity verification provider that helps businesses verify the identities of their customers online. It offers a range of products and services, including document verification, biometric verification, data verification, and fraud detection. Onfido's solutions are used by businesses in a variety of industries, including financial services, gaming, healthcare, and retail.

Regula AI, now known as Paxton AI, is an AI tool designed to empower businesses in their compliance journey. It offers advanced AI capabilities to streamline and enhance compliance processes. With a focus on regulatory compliance, risk management, and fraud prevention, Paxton AI provides cutting-edge solutions to help organizations meet their compliance requirements efficiently. By leveraging artificial intelligence and machine learning technologies, Paxton AI enables businesses to automate compliance tasks, detect anomalies, and mitigate risks effectively.

Redflag AI is a leading provider of content and brand protection solutions. Our AI-powered platform helps businesses protect their brands from fraud, abuse, and counterfeiting. We offer a range of services to help businesses protect their online presence, including brand monitoring, content moderation, and fraud detection.

This repository contains custom recipes for H2O Driverless AI, which is an Automatic Machine Learning platform for the Enterprise. Custom recipes are Python code snippets that can be uploaded into Driverless AI at runtime to automate feature engineering, model building, visualization, and interpretability. Users can gain control over the optimization choices made by Driverless AI by providing their own custom recipes. The repository includes recipes for various tasks such as data manipulation, data preprocessing, feature selection, data augmentation, model building, scoring, and more. Best practices for creating and using recipes are also provided, including security considerations, performance tips, and safety measures.

Awesome AI is a curated list of artificial intelligence resources including courses, tools, apps, and open-source projects. It covers a wide range of topics such as machine learning, deep learning, natural language processing, robotics, conversational interfaces, data science, and more. The repository serves as a comprehensive guide for individuals interested in exploring the field of artificial intelligence and its applications across various domains.

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.

This repository contains a collection of AI projects covering various areas of machine learning. Each project is accompanied by detailed articles on the associated blog sciblog. Projects range from introductory topics like Convolutional Neural Networks and Transfer Learning to advanced topics like Fraud Detection and Recommendation Systems. The repository also includes tutorials on data generation, distributed training, natural language processing, and time series forecasting. Additionally, it features visualization projects such as football match visualization using Datashader.

MiniAiLive provides system integrators with fast, flexible and extremely precise facial recognition with 3D passive face liveness detection (face anti-spoofing) that can be deployed across a number of scenarios, including security, access control, public safety, fintech, smart retail and home protection.

The MiniAiLive Face Recognition LivenessDetection Server SDK provides system integrators with fast, flexible, and extremely precise facial recognition that can be deployed across various scenarios, including security, access control, public safety, fintech, smart retail, and home protection. The SDK is fully on-premise, meaning all processing happens on the hosting server, and no data leaves the server. The project structure includes bin, cpp, flask, model, python, test_image, and Dockerfile directories. To set up the project on Linux, download the repo, install system dependencies, and copy libraries into the system folder. For Windows, contact MiniAiLive via email. The C++ example involves replacing the license key in main.cpp, building the project, and running it. The Python example requires installing dependencies and running the project. The Python Flask example involves replacing the license key in app.py, installing dependencies, and running the project. The Docker Flask example includes building the docker image and running it. To request a license, contact MiniAiLive. Contributions to the project are welcome by following specific steps. An online demo is available at https://demo.miniai.live. Related products include MiniAI-Face-Recognition-LivenessDetection-AndroidSDK, MiniAI-Face-Recognition-LivenessDetection-iOS-SDK, MiniAI-Face-LivenessDetection-AndroidSDK, MiniAI-Face-LivenessDetection-iOS-SDK, MiniAI-Face-Matching-AndroidSDK, and MiniAI-Face-Matching-iOS-SDK. MiniAiLive is a leading AI solutions company specializing in computer vision and machine learning technologies.

The Google Cloud Document AI Samples repository contains code samples and Community Samples demonstrating how to analyze, classify, and search documents using Google Cloud Document AI. It includes various projects showcasing different functionalities such as integrating with Google Drive, processing documents using Python, content moderation with Dialogflow CX, fraud detection, language extraction, paper summarization, tax processing pipeline, and more. The repository also provides access to test document files stored in a publicly-accessible Google Cloud Storage Bucket. Additionally, there are codelabs available for optical character recognition (OCR), form parsing, specialized processors, and managing Document AI processors. Community samples, like the PDF Annotator Sample, are also included. Contributions are welcome, and users can seek help or report issues through the repository's issues page. Please note that this repository is not an officially supported Google product and is intended for demonstrative purposes only.

The repository 'Awesome-LLM4Cybersecurity' provides a comprehensive overview of the applications of Large Language Models (LLMs) in cybersecurity. It includes a systematic literature review covering topics such as constructing cybersecurity-oriented domain LLMs, potential applications of LLMs in cybersecurity, and research directions in the field. The repository analyzes various benchmarks, datasets, and applications of LLMs in cybersecurity tasks like threat intelligence, fuzzing, vulnerabilities detection, insecure code generation, program repair, anomaly detection, and LLM-assisted attacks.

InterpretML is an open-source package that incorporates state-of-the-art machine learning interpretability techniques under one roof. With this package, you can train interpretable glassbox models and explain blackbox systems. InterpretML helps you understand your model's global behavior, or understand the reasons behind individual predictions. Interpretability is essential for: - Model debugging - Why did my model make this mistake? - Feature Engineering - How can I improve my model? - Detecting fairness issues - Does my model discriminate? - Human-AI cooperation - How can I understand and trust the model's decisions? - Regulatory compliance - Does my model satisfy legal requirements? - High-risk applications - Healthcare, finance, judicial, ...

ai-collective-tools is an open-source community dedicated to creating a comprehensive collection of AI tools for developers, researchers, and enthusiasts. The repository provides a curated selection of AI tools and resources across various categories such as 3D, Agriculture, Art, Audio Editing, Avatars, Chatbots, Code Assistant, Cooking, Copywriting, Crypto, Customer Support, Dating, Design Assistant, Design Generator, Developer, E-Commerce, Education, Email Assistant, Experiments, Fashion, Finance, Fitness, Fun Tools, Gaming, General Writing, Gift Ideas, HealthCare, Human Resources, Image Classification, Image Editing, Image Generator, Interior Designing, Legal Assistant, Logo Generator, Low Code, Models, Music, Paraphraser, Personal Assistant, Presentations, Productivity, Prompt Generator, Psychology, Real Estate, Religion, Research, Resume, Sales, Search Engine, SEO, Shopping, Social Media, Spreadsheets, SQL, Startup Tools, Story Teller, Summarizer, Testing, Text to Speech, Text to Image, Transcriber, Travel, Video Editing, Video Generator, Weather, Writing Generator, and Other Resources.

last_layer is a security library designed to protect LLM applications from prompt injection attacks, jailbreaks, and exploits. It acts as a robust filtering layer to scrutinize prompts before they are processed by LLMs, ensuring that only safe and appropriate content is allowed through. The tool offers ultra-fast scanning with low latency, privacy-focused operation without tracking or network calls, compatibility with serverless platforms, advanced threat detection mechanisms, and regular updates to adapt to evolving security challenges. It significantly reduces the risk of prompt-based attacks and exploits but cannot guarantee complete protection against all possible threats.

Awesome-AI-SEO is a curated list of powerful AI tools and platforms designed to transform your SEO strategy. This repository gathers the most effective tools that leverage machine learning and artificial intelligence to automate and enhance key aspects of search engine optimization. Whether you are an SEO professional, digital marketer, or website owner, these tools can help you optimize your site, improve your search rankings, and increase organic traffic with greater precision and efficiency. The list features AI tools covering on-page and off-page optimization, competitor analysis, rank tracking, and advanced SEO analytics. By utilizing cutting-edge technologies, businesses can stay ahead of the competition by uncovering hidden keyword opportunities, optimizing content for better visibility, and automating time-consuming SEO tasks. With frequent updates, Awesome-AI-SEO is your go-to resource for discovering the latest AI-driven innovations in the SEO space.

Ludwig is a declarative deep learning framework designed for scale and efficiency. It is a low-code framework that allows users to build custom AI models like LLMs and other deep neural networks with ease. Ludwig offers features such as optimized scale and efficiency, expert level control, modularity, and extensibility. It is engineered for production with prebuilt Docker containers, support for running with Ray on Kubernetes, and the ability to export models to Torchscript and Triton. Ludwig is hosted by the Linux Foundation AI & Data.

This repository contains code and configurations for the LLM - Detect AI Generated Text competition. It includes setup instructions for hardware, software, dependencies, and datasets. The training section covers scripts and configurations for training LLM models, DeBERTa ranking models, and an embedding model. Text generation section details fine-tuning LLMs using the CLM objective on the PERSUADE corpus to generate student-like essays.

This tool is designed to detect and classify Alzheimer's Disease using Deep Learning and Machine Learning algorithms on an early basis, which is further optimized using the Crow Search Algorithm (CSA). Alzheimer's is a fatal disease, and early detection is crucial for patients to predetermine their condition and prevent its progression. By analyzing MRI scanned images using Artificial Intelligence technology, this tool can classify patients who may or may not develop AD in the future. The CSA algorithm, combined with ML algorithms, has proven to be the most effective approach for this purpose.

This competition is organized by Javier Rando and Florian Tramèr from the ETH AI Center and SPY Lab at ETH Zurich. The goal of the competition is to create a method that can detect universal backdoors in aligned language models. A universal backdoor is a secret suffix that, when appended to any prompt, enables the model to answer harmful instructions. The competition provides a set of poisoned generation models, a reward model that measures how safe a completion is, and a dataset with prompts to run experiments. Participants are encouraged to use novel methods for red-teaming, automated approaches with low human oversight, and interpretability tools to find the trojans. The best submissions will be offered the chance to present their work at an event during the SaTML 2024 conference and may be invited to co-author a publication summarizing the competition results.

This repository contains a C++ application that demonstrates face recognition capabilities using computer vision techniques. The demo utilizes OpenCV and dlib libraries for efficient face detection and recognition with 3D passive face liveness detection (face anti-spoofing). Key Features: Face detection: The SDK utilizes advanced computer vision techniques to detect faces in images or video frames, enabling a wide range of applications. Face recognition: It can recognize known faces by comparing them with a pre-defined database of individuals. Age estimation: It can estimate the age of detected faces. Gender detection: It can determine the gender of detected faces. Liveness detection: It can detect whether a face is from a live person or a static image.

AudioSeal is a method for speech localized watermarking, designed with state-of-the-art robustness and detector speed. It jointly trains a generator to embed a watermark in audio and a detector to detect watermarked fragments in longer audios, even in the presence of editing. The tool achieves top-notch detection performance at the sample level, generates minimal alteration of signal quality, and is robust to various audio editing types. With a fast, single-pass detector, AudioSeal surpasses existing models in speed, making it ideal for large-scale and real-time applications.

Slips is a powerful endpoint behavioral intrusion prevention and detection system that uses machine learning to detect malicious behaviors in network traffic. It can work with network traffic in real-time, PCAP files, and network flows from tools like Suricata, Zeek/Bro, and Argus. Slips threat detection is based on machine learning models, threat intelligence feeds, and expert heuristics. It gathers evidence of malicious behavior and triggers alerts when enough evidence is accumulated. The tool is Python-based and supported on Linux and MacOS, with blocking features only on Linux. Slips relies on Zeek network analysis framework and Redis for interprocess communication. It offers a graphical user interface for easy monitoring and analysis.

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Expert in payment methods and financial transactions

The most comprehensive guide to ML theory and applications.

Multilingual financial expert for PDF bank statement analysis ->> Latest Update: Mar 12th, 2024

Expert in simplified financial rule engines.

Finance fact-checker with accuracy scoring, using sources like NerdWallet, Investopedia, BEA, and St. Louis Fed.

A protector and guide in online safety, detecting manipulations and fraud.

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Spam expert with comprehensive scam detection and education.

Friendly scam guide with threat level indicator.

Friendly bot analysing scams, user-friendly and safe.

I'm PhishCatcher, an expert in identifying phishing attempts.

Detailed coding analyst with a focus on overpayment detection and references.

Hone your phishing detection skills! Analyze emails, texts, and calls to spot deception. Become a security pro!

Determines if images are AI-generated or real, and learns from feedback.

stunspot's advisor for all things Financial Cybersec

Analyzes emails for phishing risks.

Checks if domains/emails are disposable using an API

This is a demonstration of GPT Auth™, an authentication system designed to protect your customized GPT.