Best AI tools for< Fraud Investigator >

Emotion Logic Ltd is an AI application that specializes in genuine emotion detection from voice data. Their technology elevates applications across diverse sectors, including fraud investigations, healthcare, education, and customer service. Emotion Logic provides valuable insights into users' genuine emotions through voice analysis, surpassing tone, language, and cultural barriers.

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.

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 the user's requirements, cutting through noise to deliver essential information. Users can build custom monitoring solutions for various intelligence areas and benefit from intuitive data visualizations, executive summaries, and free-form chat with news data. Overwatch Data aims to save time and enhance decision-making by providing contextualized intelligence for fraud, security, and insights teams.

AI Voice Detector is an advanced tool designed to protect individuals and businesses from audio manipulation and AI voice scams. It offers a high model accuracy of 92% in identifying whether an audio is real or AI-generated. The tool can be used to detect AI voices in various platforms like YouTube, WhatsApp, TikTok, Zoom, and Google Meet. With features such as multilanguage support, background noise removal, and browser extension integration, AI Voice Detector stands out as a reliable solution for authenticating audio files.

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.

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.

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.

SafeSpeak is an AI-powered mobile security solution that protects users from phone scams, SIM swaps, and other malicious activities. It uses advanced machine learning and large language models to detect and block threats in real-time. SafeSpeak offers a range of features for both personal and business use, including malicious behavior detection, community immunity, SIM swap detection, weekly and monthly reporting, quick and easy setup, admin dashboard, extensible API, custom reporting, and visibility into tactics, techniques, and procedures (TTPs).

AI or Not is an AI-powered tool that helps businesses and individuals detect AI-generated images and audio. It uses advanced machine learning algorithms to analyze content and determine the likelihood of AI manipulation. With AI or Not, users can protect themselves from fraud, misinformation, and other malicious activities involving AI-generated content.

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.

ScamAlert is an AI-powered application designed to help users avert scams in a smarter way. By adopting the power of AI and building smart systems, ScamAlert protects users from being scammed by analyzing risks, conducting manual reviews, providing timely alerts, and fostering a social community to prevent similar scams. The application enhances the online experience by taking care of risky aspects while empowering users to make well-informed decisions.

Rank One Computing (ROC) is an American-made provider of multimodal biometrics and computer vision solutions, specializing in face recognition, fingerprint recognition, and artificial intelligence technologies. Trusted by the U.S. military, law enforcement, and leading FinTech brands, ROC offers top-ranked software for identity proofing and threat detection. Their suite of products includes ROC SDK, ROC Watch, and custom enterprise AI development services. With a focus on security and efficiency, ROC aims to make the world safer and more convenient through unbiased and privacy-conscious applications.

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.

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.

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.

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.

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.

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.

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, ...

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.

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.

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.

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.

Chronon is a platform that simplifies and improves ML workflows by providing a central place to define features, ensuring point-in-time correctness for backfills, simplifying orchestration for batch and streaming pipelines, offering easy endpoints for feature fetching, and guaranteeing and measuring consistency. It offers benefits over other approaches by enabling the use of a broad set of data for training, handling large aggregations and other computationally intensive transformations, and abstracting away the infrastructure complexity of data plumbing.

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.

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).

The collection is actively updated with the help of an internal literature search engine.

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

Hopsworks is a data platform for ML with a Python-centric Feature Store and MLOps capabilities. It provides collaboration for ML teams, offering a secure, governed platform for developing, managing, and sharing ML assets. Hopsworks supports project-based multi-tenancy, team collaboration, development tools for Data Science, and is available on any platform including managed cloud services and on-premise installations. The platform enables end-to-end responsibility from raw data to managed features and models, supports versioning, lineage, and provenance, and facilitates the complete MLOps life cycle.

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.

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 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.

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

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Aid for banking account recovery issues.

Access the mind of the world's greatest detective

stunspot's advisor for all things Financial Cybersec

Unearths digital footprints

Analyzes emails for phishing risks.

Expert on Governement functional standards

Based off of reddit thread r/scambait. Spam Jester is a role playing bot that engages with spam/scam messages to waste scammer's time with funny replys. Upload a spam message to generate a funny reply!

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

Your AI OSINT assistant. Our tool helps you find the data needle in the internet haystack.

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

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

Checks if domains/emails are disposable using an API

A helpful guide for identifying unknown callers and missed calls.

Security-focused GPT offering advice on personal and online safety.

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An unyielding champion against predatory financial practices, adept at analyzing and exposing complex financial mechanisms, and relentless in advocating for consumer rights and transparency.