Best AI tools for< Fraud Detection Specialist >

Flagright Solutions is an AI-native AML Compliance & Risk Management platform that offers real-time transaction monitoring, automated case management, AI forensics for screening, customer risk assessment, and sanctions screening. Trusted by financial institutions worldwide, Flagright's platform streamlines compliance workflows, reduces manual tasks, and enhances fraud detection accuracy. The platform provides end-to-end solutions for financial crime compliance, empowering operational teams to collaborate effectively and make reliable decisions. With advanced AI algorithms and real-time processing, Flagright ensures instant detection of suspicious activities, reducing false positives and enhancing risk detection capabilities.

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.

ClicKarma is an AI-driven defense tool designed to protect Google Ads from click frauds. It maximizes ROI by ensuring authentic interactions and eliminating wasted spend from bots and dishonest competitors. The tool offers advanced AI features to proactively identify and block disruptive click fraud, operates on auto-pilot, and provides real-time protection. ClicKarma significantly improves campaign metrics, increases genuine interactions, and enhances ROI for Google Ads campaigns.

Clickmoat is an AI-based ad fraud and click-fraud detection software. It protects Google Ads and Facebook campaigns by using industry-leading detection algorithms to block fraudulent IPs automatically. Clickmoat's services include identifying worthless clicks, providing full control over protection, offering extensive analytics, and ensuring a user-friendly interface. With its reasonable pricing and 24/7 support, Clickmoat helps businesses safeguard their advertising campaigns and maximize their return on investment.

AI Voice Detector is an advanced tool designed to protect individuals and businesses from audio manipulation and AI voice scams. It offers features such as identifying real vs. AI-generated audio, integrated background noise and music removal, and browser extension support. The tool helps users detect fake audio, prevent AI scams, and verify the authenticity of voice messages and calls. With a proven track record of accuracy and effectiveness, AI Voice Detector is a market leader in voice analysis and fraud prevention.

Peslac AI is an intelligent document processing solution that leverages advanced AI technology to transform complex documents into structured data, streamline document-heavy workflows, and automate data extraction and form processing. It offers insights through document analysis, workflow automation, and tailored solutions for various industries such as insurance, finance, healthcare, legal, and more. Peslac aims to enhance operational efficiency, accuracy, and speed by automating document-heavy processes and providing seamless integration with existing systems.

Attestiv is an AI-powered digital content analysis and forensics platform that offers solutions to prevent fraud, losses, and cyber threats from deepfakes. The platform helps in reducing costs through automated photo, video, and document inspection and analysis, protecting company reputation, and monetizing trust in secure systems. Attestiv's technology provides validation and authenticity for all digital assets, safeguarding against altered photos, videos, and documents that are increasingly easy to create but difficult to detect. The platform uses patented AI technology to ensure the authenticity of uploaded media and offers sector-agnostic solutions for various industries.

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.

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.

SymphonyAI NetReveal Financial Services is an AI-powered platform that offers solutions for financial crime prevention in various industries such as banking, insurance, financial markets, and private banking. The platform utilizes predictive and generative AI applications to enhance efficiency, reduce fraud, streamline compliance, and maximize output. SymphonyAI provides a fundamentally different approach to AI by combining high-value AI capabilities with industry-leading predictive and generative AI technologies. The platform offers a range of solutions including transaction monitoring, customer due diligence, payment fraud detection, and enterprise investigation management. SymphonyAI aims to revolutionize financial crime prevention by leveraging AI to detect suspicious activity, expedite investigations, and improve compliance operations.

nSure.ai is a cutting-edge AI tool that specializes in payment fraud prevention solutions for industries such as Crypto, Gaming, Prepaid & Gift Cards. The platform offers a range of features including high transaction approval rates, chargeback guarantee, real-time decisioning, and innovative fraud prevention protocols like SoftApproval®, StingBack®, and DynamicKYC®. nSure.ai is backed by leading insurers and provides dedicated API and SDK for seamless integration. The tool aims to deliver guaranteed net incremental profit to clients while taking 100% liability for fraud-related chargebacks.

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.

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.

The website offers AI solutions for enterprises, focusing on cutting-edge technology and business acumen. They provide services from discovery and strategy to development and integration of custom AI solutions. The team consists of technologists, business experts, and product specialists who work closely with clients to optimize AI strategies for time, cost, and security. The application specializes in AI solutions for various business functions such as sales, marketing, operations, HR, finance, legal, risk, and IT. They emphasize an AI-first approach, co-creating roadmaps with clients to deliver impactful projects. The website also highlights their expertise in AI for IT, including code review, test generation, DevOps, monitoring, alerting, and security audits.

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.

Overwatch Data is a comprehensive intelligence platform that provides real-time, global understanding for cyber, fraud, security, supply chain, and market intelligence needs. The platform offers concise, actionable insights tailored to specific intelligence requirements, cutting through noise to deliver crucial information. Users can customize monitoring for various categories, access intuitive data visualizations, receive real-time executive summaries, and engage in free-form chat with news data. Overwatch Data aims to streamline intelligence gathering and decision-making processes for businesses and organizations.

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.

Fusemachines is an AI company that offers AI products and solutions to democratize AI. Their AI Studio platform provides various AI engines for different use cases, such as GenAI Engines for predictive analytics and Fraud Detection, Forecast AI for demand forecasting, and more. The company aims to empower enterprises with tailored AI solutions and seamless integration of tools to enhance value across specific industries like Retail, Healthcare, Technology, Banking & Insurance, and Media & Entertainment.

Nametag is an identity verification solution designed specifically for IT helpdesks. It helps businesses prevent social engineering attacks, account takeovers, and data breaches by verifying the identity of users at critical moments, such as password resets, MFA resets, and high-risk transactions. Nametag's unique approach to identity verification combines mobile cryptography, device telemetry, and proprietary AI models to provide unmatched security and better user experiences.

Ref Hub is an AI-powered online reference checking software based in Australia. The platform offers automated reference checks, fraud detection, lead generation tools, survey builder, and mobile app for managing reference checks on-the-go. With AI assessments, users can test candidates' skills at scale. Ref Hub provides flexible solutions for businesses of all sizes, from startups to large enterprises, streamlining the hiring process with reliable reference checks and smart assessments.

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 a comprehensive collection of 63 must-know Large Language Models (LLMs) interview questions. It covers topics such as the architecture of LLMs, transformer models, attention mechanisms, training processes, encoder-decoder frameworks, differences between LLMs and traditional statistical language models, handling context and long-term dependencies, transformers for parallelization, applications of LLMs, sentiment analysis, language translation, conversation AI, chatbots, and more. The readme provides detailed explanations, code examples, and insights into utilizing LLMs for various tasks.

The MiniAiLive Face Liveness Detection Android SDK provides advanced computer vision techniques to enhance security and accuracy on Android platforms. It offers 3D Passive Face Liveness Detection capabilities, ensuring that users are physically present and not using spoofing methods to access applications or services. The SDK is fully on-premise, with all processing happening on the hosting server, ensuring data privacy and security.

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.

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.

A massive list including a huge amount of products and services that are completely free! ⭐ Star on GitHub • 🤝 Contribute # Table of Contents * APIs, Data & ML * Artificial Intelligence * BaaS * Code Editors * Code Generation * DNS * Databases * Design & UI * Domains * Email * Font * For Students * Forms * Linux Distributions * Messaging & Streaming * PaaS * Payments & Billing * SSL

The edge2ai-workshop repository provides a hands-on workshop for building an IoT Predictive Maintenance workflow. It includes lab exercises for setting up components like NiFi, Streams Processing, Data Visualization, and more on a single host. The repository also covers use cases such as credit card fraud detection. Users can follow detailed instructions, prerequisites, and connectivity guidelines to connect to their cluster and explore various services. Additionally, troubleshooting tips are provided for common issues like MiNiFi not sending messages or CEM not picking up new NARs.

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.

Mobius is an AI infra platform including realtime computing and training. It is built on Ray, a distributed computing framework, and provides a number of features that make it well-suited for online machine learning tasks. These features include: * **Cross Language**: Mobius can run in multiple languages (only Python and Java are supported currently) with high efficiency. You can implement your operator in different languages and run them in one job. * **Single Node Failover**: Mobius has a special failover mechanism that only needs to rollback the failed node itself, in most cases, to recover the job. This is a huge benefit if your job is sensitive about failure recovery time. * **AutoScaling**: Mobius can generate a new graph with different configurations in runtime without stopping the job. * **Fusion Training**: Mobius can combine TensorFlow/Pytorch and streaming, then building an e2e online machine learning pipeline. Mobius is still under development, but it has already been used to power a number of real-world applications, including: * A real-time recommendation system for a major e-commerce company * A fraud detection system for a large financial institution * A personalized news feed for a major news organization If you are interested in using Mobius for your own online machine learning projects, you can find more information in the documentation.

OpenAGI is a framework designed to make the development of autonomous human-like agents accessible to all. It aims to pave the way towards open agents and eventually AGI for everyone. The initiative strongly believes in the transformative power of AI and offers developers a platform to create autonomous human-like agents. OpenAGI features a flexible agent architecture, streamlined integration and configuration processes, and automated/manual agent configuration generation. It can be used in education for personalized learning experiences, in finance and banking for fraud detection and personalized banking advice, and in healthcare for patient monitoring and disease diagnosis.

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, ...

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.

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.

Intel® Extension for Transformers is an innovative toolkit designed to accelerate GenAI/LLM everywhere with the optimal performance of Transformer-based models on various Intel platforms, including Intel Gaudi2, Intel CPU, and Intel GPU. The toolkit provides the below key features and examples: * Seamless user experience of model compressions on Transformer-based models by extending [Hugging Face transformers](https://github.com/huggingface/transformers) APIs and leveraging [Intel® Neural Compressor](https://github.com/intel/neural-compressor) * Advanced software optimizations and unique compression-aware runtime (released with NeurIPS 2022's paper [Fast Distilbert on CPUs](https://arxiv.org/abs/2211.07715) and [QuaLA-MiniLM: a Quantized Length Adaptive MiniLM](https://arxiv.org/abs/2210.17114), and NeurIPS 2021's paper [Prune Once for All: Sparse Pre-Trained Language Models](https://arxiv.org/abs/2111.05754)) * Optimized Transformer-based model packages such as [Stable Diffusion](examples/huggingface/pytorch/text-to-image/deployment/stable_diffusion), [GPT-J-6B](examples/huggingface/pytorch/text-generation/deployment), [GPT-NEOX](examples/huggingface/pytorch/language-modeling/quantization#2-validated-model-list), [BLOOM-176B](examples/huggingface/pytorch/language-modeling/inference#BLOOM-176B), [T5](examples/huggingface/pytorch/summarization/quantization#2-validated-model-list), [Flan-T5](examples/huggingface/pytorch/summarization/quantization#2-validated-model-list), and end-to-end workflows such as [SetFit-based text classification](docs/tutorials/pytorch/text-classification/SetFit_model_compression_AGNews.ipynb) and [document level sentiment analysis (DLSA)](workflows/dlsa) * [NeuralChat](intel_extension_for_transformers/neural_chat), a customizable chatbot framework to create your own chatbot within minutes by leveraging a rich set of [plugins](https://github.com/intel/intel-extension-for-transformers/blob/main/intel_extension_for_transformers/neural_chat/docs/advanced_features.md) such as [Knowledge Retrieval](./intel_extension_for_transformers/neural_chat/pipeline/plugins/retrieval/README.md), [Speech Interaction](./intel_extension_for_transformers/neural_chat/pipeline/plugins/audio/README.md), [Query Caching](./intel_extension_for_transformers/neural_chat/pipeline/plugins/caching/README.md), and [Security Guardrail](./intel_extension_for_transformers/neural_chat/pipeline/plugins/security/README.md). This framework supports Intel Gaudi2/CPU/GPU. * [Inference](https://github.com/intel/neural-speed/tree/main) of Large Language Model (LLM) in pure C/C++ with weight-only quantization kernels for Intel CPU and Intel GPU (TBD), supporting [GPT-NEOX](https://github.com/intel/neural-speed/tree/main/neural_speed/models/gptneox), [LLAMA](https://github.com/intel/neural-speed/tree/main/neural_speed/models/llama), [MPT](https://github.com/intel/neural-speed/tree/main/neural_speed/models/mpt), [FALCON](https://github.com/intel/neural-speed/tree/main/neural_speed/models/falcon), [BLOOM-7B](https://github.com/intel/neural-speed/tree/main/neural_speed/models/bloom), [OPT](https://github.com/intel/neural-speed/tree/main/neural_speed/models/opt), [ChatGLM2-6B](https://github.com/intel/neural-speed/tree/main/neural_speed/models/chatglm), [GPT-J-6B](https://github.com/intel/neural-speed/tree/main/neural_speed/models/gptj), and [Dolly-v2-3B](https://github.com/intel/neural-speed/tree/main/neural_speed/models/gptneox). Support AMX, VNNI, AVX512F and AVX2 instruction set. We've boosted the performance of Intel CPUs, with a particular focus on the 4th generation Intel Xeon Scalable processor, codenamed [Sapphire Rapids](https://www.intel.com/content/www/us/en/products/docs/processors/xeon-accelerated/4th-gen-xeon-scalable-processors.html).

This repository is a part of the 13th iT Help Ironman competition, focusing on exploring explainable artificial intelligence (XAI) in machine learning and deep learning. The content covers the basics of XAI, its applications, cases, challenges, and future directions. It also includes practical machine learning algorithms, model deployment, and integration concepts. The author aims to provide detailed resources on AI and share knowledge with the audience through this competition.

The 'crazyai-ml' repository is a collection of resources related to machine learning, specifically focusing on explaining artificial intelligence models. It includes articles, code snippets, and tutorials covering various machine learning algorithms, data analysis, model training, and deployment. The content aims to provide a comprehensive guide for beginners in the field of AI, offering practical implementations and insights into popular machine learning packages and model tuning techniques. The repository also addresses the integration of AI models and frontend-backend concepts, making it a valuable resource for individuals interested in AI applications.

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

Friendly bot analysing scams, user-friendly and safe.

يقدم نصائح للكشف عن الاحتيال

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

Expert in payment methods and financial transactions

stunspot's advisor for all things Financial Cybersec

Spam expert with comprehensive scam detection and education.

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

Friendly scam guide with threat level indicator.

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

一切的骗局在我面前将无所遁形

Analyzes emails for phishing risks.

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

Un détective privé qualifié, parle couramment le français et habile dans les enquêtes en ligne. GPTseek.com=G0LWETXGGL

Your AI Detective for piecing together puzzles and solving any mystery.

Play as a detective to investigate the case and find out the truth.

A master detective GPT, adept in analysis, deduction, and intuitive problem-solving.

Access the mind of the world's greatest detective

迷探偵がSNSをプロファイリング分析します🧐調べたいユーザーのXアカウント名＠以下を入力してください。

Expert on Governement functional standards