--- title: Sift Reviews meta_title: 'Sift Reviews 2026: Details, Pricing, & Features | G2' meta_description: Filter 615 reviews by the users' company size, role or industry to find out how Sift works for a business like yours. aggregate_rating: rating_value: 4.6 review_count: 615 scale: '5' date_modified: '2026-08-13' parent_category: name: Web Security url: https://www.g2.com/categories/web-security --- # Sift Reviews **Vendor:** Sift's Fraud Prevention Platform **Category:** [Fraud Detection Software](https://www.g2.com/categories/fraud-detection) **Average Rating:** 4.6/5.0 **Total Reviews:** 615 ## About Sift Sift is the leading fraud prevention platform delivering digital trust to 700+ global brands, allowing them to grow confidently by stopping fraud while enabling excellence in customer experience. Backed by a global data network of over one trillion annual events, Sift helps companies convert risk into revenue and scale without compromise. Brands including Hertz, Yelp, and Poshmark rely on Sift to unlock growth and deliver seamless consumer experiences. Visit us at sift.com ## Sift Pros & Cons **What users like:** - Users value the **ease of use** of Sift, finding it user-friendly and efficient for risk assessment and decision-making. (71 reviews) - Users value the **customizable workflow routes** of Sift, enhancing fraud identification and supporting business growth. (71 reviews) - Users value SIFT's **powerful analytics and real-time monitoring** , enabling early risk detection and effective preventive measures. (46 reviews) - Users value the **effective fraud detection** capabilities of Sift, enjoying its comprehensive data and ease of navigation. (46 reviews) - Users commend Sift for its **effective data analysis** , enhancing user activity review and fraud detection effortlessly. (44 reviews) - Efficiency (41 reviews) - Detection Efficiency (40 reviews) - Analytics (35 reviews) - User Interface (34 reviews) - Accuracy (31 reviews) **What users dislike:** - Users face challenges with **inaccuracy** , leading to false positives and difficulties in data integration for Sift. (29 reviews) - Users experience a **lack of clarity** in direction and decision-making processes, complicating implementation and usage. (20 reviews) - Users find Sift's interface **not user-friendly** , as it is confusing and overly complicated during setup and integration. (18 reviews) - Users experience **false positives** that can hinder legitimate users and disrupt the overall effectiveness of Sift. (17 reviews) - Users experience **false alarms** that frustrate legitimate interactions, impacting overall satisfaction with Sift's accuracy. (16 reviews) - Users find the **complexity of Sift** overwhelming, particularly for non-technical teams and new users unfamiliar with its features. (15 reviews) - Limited Features (15 reviews) - Improvement Needed (13 reviews) - Scoring Transparency (12 reviews) - Complex Setup (10 reviews) ## Sift Reviews ### 1. Powerful Fraud Detection with Robust Automation, But Complex Setup and Cost Concerns **Rating:** 3.5/5.0 stars **Reviewed by:** Kerolos G. | Payment Operations Analyst, Mid-Market (51-1000 emp.) **Reviewed Date:** October 27, 2025 **What do you like best about Sift?** Real-time risk-scoring of bookings (so you can flag quickly which bookings might be fraudulent) and integration with your PG/fraud tool ecosystem. Workflows and rules that allow automation of “high risk → block/cancel” actions, freeing you from manual triage. Dashboards that allow you to monitor fraud decline rates, patterns, and anomalies across your flight & hotel services. Dispute/chargeback management modules that help you gather evidence, view dispute status, and follow up with acquirers. Ability to link behaviour (e.g., account creation, booking patterns, refund requests) with risk scoring, which helps you detect “fraud skipes” (skipping patterns) or evolving fraud schemes. **What do you dislike about Sift?** Complexity and implementation effort Some users report a steep learning curve. The platform offers many capabilities, which means setup, tuning, rule-building, and integration can take time. For smaller teams or organisations without dedicated fraud specialists, the resources needed (for configuration, fine-tuning, monitoring) may be non-trivial. Cost and pricing model Sift uses a custom, quote-based pricing model (often aligned to your transaction volume, the modules you use, and your service level). Because of that, for smaller merchants with limited volume or limited fraud operations budget, it may be less cost-efficient than simpler tools. Transparency of scoring / “black box” concerns Some users note that while the scoring and ML are effective, they don’t always get full visibility into why a decision was made — making explanations to business stakeholders or appeals harder. Also, there are mentions of false positives or misclassification of legitimate users, which can impact revenue or customer experience. Reporting / customisation limitations A few reviews mention that the reporting/analytics could be stronger or more flexible; the rich machine-learning engine is top tier, but viewing, exporting, or fully customising dashboards may be less advanced than desired. **What problems is Sift solving and how is that benefiting you?** Sift offers a full “Digital Trust & Safety” suite that spans payment protection, account defense (e.g., account takeover prevention), content integrity (spam/scams), and dispute/chargeback management. Technology Evaluation Center Because everything is in one platform, fraud operations can see user behaviour, transactions, and risk across different touch-points (not just payment fraud). Their global network reportedly handles 1 trillion events per year, meaning the system benefits from very large-scale data. Technology Evaluation Center Because everything is in one platform, fraud operations can see user behaviour, transactions, and risk across different touch-points (not just payment fraud). Nerdisa Their global network reportedly handles 1 trillion events per year, meaning the system benefits from very large-scale data. Strong machine-learning and real-time decisioning The ML models and real-time scoring allow for risk assessments and automated actions (block / review / accept) very quickly. Nerdisa Many users report that Sift helps reduce manual review burden and allows focusing on high-risk cases. Good for growing / high-volume merchants It is particularly well suited to mid-sized to enterprise-level companies with serious fraud risk, many transactions, or complex cross-channel operations. Technology Evaluation Center It supports integrations with many systems (payment gateways, CRMs, case management). ### 2. Fraud Prevention and Fast, Confident Risk Decisions **Rating:** 5.0/5.0 stars **Reviewed by:** Verified User in Airlines/Aviation | Mid-Market (51-1000 emp.) **Reviewed Date:** January 31, 2026 **What do you like best about Sift?** Sift is especially helpful because it detects and prevents fraud in real time, verifies user identities to help maintain account integrity, and delivers actionable insights and risk scores that enable businesses to make quick, informed decisions. It also reduces operational burden and strengthens overall trust across the platform. **What do you dislike about Sift?** Some downsides of using Sift include the risk of false positives, which can end up frustrating legitimate users. It also relies heavily on accurate input data, and any issues there can affect the accuracy of its scores. In addition, it may have limited ability to detect very niche or newly emerging types of fraud, and for some businesses the integration can be both costly and complex. **What problems is Sift solving and how is that benefiting you?** Sift helps address fraud, account abuse, and transactional risk by detecting suspicious activity, verifying user identities, and assigning real-time risk scores. This can help prevent financial losses, protect your platform’s reputation, and support a more trustworthy user base. It also streamlines decision-making, so you can stay focused on legitimate business operations without constantly worrying about fraud or abuse. ### 3. Very intuitive **Rating:** 5.0/5.0 stars **Reviewed by:** Verified User in Consumer Services | Mid-Market (51-1000 emp.) **Reviewed Date:** December 21, 2021 **What do you like best about Sift?** How it learns from my choises and make decisions base of them.What I like most about Sift is how effectively it combines automation with actionable insights. It allows us to detect and prevent fraud early in the account creation process while still giving our team the flexibility to review and make informed decisions. The risk scoring, rule customization, and clear dashboards make it easy to understand why an account is flagged, which helps us act quickly and consistently while maintaining a good user experience. **What do you dislike about Sift?** Nothing so far, been using it for 4 years.One area for improvement with Sift is that sometimes the system can generate false positives, flagging legitimate accounts for review. While this is understandable given the focus on fraud prevention, it can slow down the onboarding process for real users. Having more granular controls or additional context in the alerts could help reduce these cases and make the moderation workflow even more efficient. **What problems is Sift solving and how is that benefiting you?** Creations of fake accounts in our platform and giving a score to each.Sift helps us prevent fraudulent account creation and detect suspicious activity early, which protects the integrity of our platform and the trust of our users. By automating much of the risk assessment with clear scoring and alerts, it reduces the manual workload for our team and allows us to focus on reviewing only the accounts that need attention. This not only improves operational efficiency but also ensures a safer and smoother experience for our legitimate users. ### 4. Efficient Fraud Prevention with Occasional False Positives **Rating:** 5.0/5.0 stars **Reviewed by:** Rudolf Carlos F. | Risk Investigator, Small-Business (50 or fewer emp.) **Reviewed Date:** October 29, 2025 **What do you like best about Sift?** What I love the most is using sift it is very efficient when checking and preventing fraudulent activity. It provides some insights how the scores affect a certain account and some transactions quickly. The system is very easy to use and helps me to ensure if the transfer is legitimate or not which helps the customers as well. **What do you dislike about Sift?** Sometimes sift provides transactions as bad that it turns out that it is not that can add an extra time for the review on the account of the customer. However, it is very helpful for checking the account of the customer and preventing fraud. **What problems is Sift solving and how is that benefiting you?** Sift is very efficient when solving problems on the account of the customer. It detects a suspicious activity and some bad patterns and maybe a potential risk. Overall, it improves and gives me confidence on my review on every account that I handled. ### 5. Sift can help us resolved our transaction reviews. **Rating:** 5.0/5.0 stars **Reviewed by:** Roma Abegail S. | Risk Investigator, Financial Services, Enterprise (> 1000 emp.) **Reviewed Date:** May 27, 2025 **What do you like best about Sift?** It helps me to easily identify the transaction if there is fraud or leaning to fraudulent activity. **What do you dislike about Sift?** Sometimes it flags things that turn out to be fine, but overall it still works well for us. **What problems is Sift solving and how is that benefiting you?** Sift can solve our reviews by checking on sift to help us identify fraud or if there is someone who is using the customer´s account. ### 6. My Sift Experience **Rating:** 5.0/5.0 stars **Reviewed by:** Sweat L. | Travel Consultant/Fraud Analyst, Enterprise (> 1000 emp.) **Reviewed Date:** August 09, 2025 **What do you like best about Sift?** Dashboards and analytics help fraud teams understand trends, justify decisions, and improve controls over time. **What do you dislike about Sift?** Although it aims to reduce false flags, no system is perfect — legitimate users may sometimes be flagged, especially in edge cases. **What problems is Sift solving and how is that benefiting you?** Sift is really a good platform to help businesses tackle various forms of digital fraud. The tool really help us to determine and identify what is needed to check such as; fake account creation, account takeovers, payment fraud, and chargeback abuse. ### 7. My Sift Review and Experience **Rating:** 5.0/5.0 stars **Reviewed by:** Judy C. | Analyst, Small-Business (50 or fewer emp.) **Reviewed Date:** August 07, 2025 **What do you like best about Sift?** - Easier to detect fraudulent activities & account user **What do you dislike about Sift?** - Auto-Block user that were previously cleared within 1 hour **What problems is Sift solving and how is that benefiting you?** We were able to detect & avoid fraudulent activities & chargebacks ### 8. "Leveraging Sift to Mitigate Fraud and Compliance Risks" **Rating:** 4.0/5.0 stars **Reviewed by:** Lyndon D. | Fraud Investigator / KYC / Transaction Monitoring / EDD / OFAC / Suspension Appeal / Mentor / AML, Enterprise (> 1000 emp.) **Reviewed Date:** May 27, 2025 **What do you like best about Sift?** What I like best about Sift is its powerful machine learning capabilities that allow for real-time analysis of transaction patterns. The platform’s ability to identify subtle fraud trends and provide actionable insights has been incredibly valuable in helping me prevent fraud and mitigate compliance risks efficiently. The user-friendly interface and customizable features also make it easier to tailor solutions to specific business needs, ensuring that I can stay ahead of potential threats. **What do you dislike about Sift?** While Sift is an incredibly powerful tool, one area for improvement could be its complexity for new users. The platform's advanced features can be overwhelming at first, and it can take some time to fully understand how to customize settings to fit specific needs. Additionally, while the machine learning models are highly effective, there can occasionally be false positives that require manual review, which can be time-consuming. However, with proper training and experience, these challenges can be mitigated. **What problems is Sift solving and how is that benefiting you?** Sift solves the problem of detecting and preventing fraudulent activities by using machine learning to analyze transaction patterns in real-time. This allows me to quickly identify suspicious behaviors and reduce false positives, which in turn helps mitigate fraud risks and ensures compliance. By automating these processes, Sift saves me valuable time, reduces manual effort, and enhances overall security in my role. ### 9. Urgency level for each case **Rating:** 5.0/5.0 stars **Reviewed by:** Marie P. | Fraud Specialist, Small-Business (50 or fewer emp.) **Reviewed Date:** August 10, 2025 **What do you like best about Sift?** Sift shows all the detailed information, allowing us to easily determine the urgency of the case. **What do you dislike about Sift?** The thing that I dislike is the False Positive information that can be found in Sift. **What problems is Sift solving and how is that benefiting you?** Since it provides detailed information such as IP, FOP used, addresses, networks, and all necessary company details, it helps me quickly determine what might be wrong with the account and whether it’s legitimate. Having all the information in front of me makes my work a little easier. ### 10. Very helpful tool. **Rating:** 5.0/5.0 stars **Reviewed by:** Verified User in Entertainment | Small-Business (50 or fewer emp.) **Reviewed Date:** November 05, 2024 **What do you like best about Sift?** The most helpful part of Sift is that it will highlight the area of an account to give us a general direction on how to start reviewing. We use this everyday every other hour, to perform our necessary reviews and help us catch a lot of Fraud before it gets worse. **What do you dislike about Sift?** There isn't much to dislike about it, but it does have it's bugs. The main one is, it will reflag accounts that have been previously marked ok, which adds to the workload. **What problems is Sift solving and how is that benefiting you?** It cuts back on review time of certain accounts which helps us review more potential fraudulent accounts. ### 11. Sift Review **Rating:** 2.5/5.0 stars **Reviewed by:** Kehinde A. | Fraud Operations Analyst, Mid-Market (51-1000 emp.) **Reviewed Date:** May 12, 2025 **What do you like best about Sift?** The SDK integration is seamless and well-documented, making it easy to incorporate Sift into our existing tech stack. **What do you dislike about Sift?** The Sift scores don’t always accurately reflect genuine user behavior, which can lead to false positives and unnecessary friction for legitimate users. It would be beneficial to have more transparency or customization in how the scoring is determined. **What problems is Sift solving and how is that benefiting you?** Fraud detection and transactions monitoring ### 12. The Function of Sift in Data Security and Compliance **Rating:** 5.0/5.0 stars **Reviewed by:** Dhruv V. | Customer Support Associate, Enterprise (> 1000 emp.) **Reviewed Date:** February 01, 2025 **What do you like best about Sift?** Sift's use of analytics and machine learning to spot fraud in real time is what sets it apart. It learn continuously from data lowering false positives and helping spot evolving fraud tendencies. Consequently fraud behavior gets blocked more accurately while keeping a smooth user experience. Additionally, Sift offers customizable workflows and tools, letting businesses tailor their fraud prevention methods to meet their unique needs. It's a versatile and efficient way to boost security without interfering with existing systems, and it's also pretty easy to integrate. **What do you dislike about Sift?** Even with all of Sifts advantages, there are not many things that could go against it. For starters, smaller teams may find the wide range of customization choices intimidating if they lack the resources to take full advantage of them. Despite its various features, Sift occasionally misclassifies normal activity as suspicious or malicious, which can have an negative impact on security and compliance as well as user experience. **What problems is Sift solving and how is that benefiting you?** Sift is solving a lot of problems for me as a compliance agent at ActiveCampaign. It automatically detects suspicious behavior in real time, which lowers the risk of fraudulent activities slipping through our checks. It helps me by flagging potentially non-compliant activities, so I can investigate and take action quickly. ### 13. My company uses this to review risky transactions and manual review of select sales. **Rating:** 4.5/5.0 stars **Reviewed by:** Verified User in Fine Art | Mid-Market (51-1000 emp.) **Reviewed Date:** May 17, 2024 **What do you like best about Sift?** I love how we can easily make and edit routes, so we can adjsut based off team's needs. Being able to see the impact that each route has on the team is helping in deciding when to make adjustments based off company needs. I enjoy how quick it is to flag and mark suspicous activity for ATO. **What do you dislike about Sift?** I struggle with looking at long term impact. Being able to review only 90 days back is difficult at seeing long term trends. I wish Sift provided more information like device ID and was able to pull more consise data when reviewing information. There is a lot of data, but it's not all useful and not easily extracted. The user abuse score is not always a great signifyer to understand their risk impact on the buisness. I often have to look at additonal variables that are outside of Sift when deciding to approve/reject a user. **What problems is Sift solving and how is that benefiting you?** Flagging sales that may be fraud or blocking users from our personal data base that are high risk. It is providing my team insight to see where we have the most risk and can limit order friction for our users. ### 14. Potential Drawbacks of Using Sift for Fraud Prevention **Rating:** 4.0/5.0 stars **Reviewed by:** Justin L. | Risk Investigator, Financial Services, Enterprise (> 1000 emp.) **Reviewed Date:** May 27, 2025 **What do you like best about Sift?** The most helpful thing about Sift is: Smart, adaptive machine learning Shared fraud signals across many businesses Customizable rules and automation A focus on user trust and safety Easy integration and a user-friendly interface **What do you dislike about Sift?** I guess the False positives that can block legitimate users and U.S.-centric models may not suit global fraud patterns. **What problems is Sift solving and how is that benefiting you?** The interface, some of the wordings is a bit Jargon for me. ### 15. Sift score review **Rating:** 4.5/5.0 stars **Reviewed by:** Maria R. | Risk investigator, Mid-Market (51-1000 emp.) **Reviewed Date:** February 23, 2025 **What do you like best about Sift?** Sift is a powerful tool, especially when it comes to preventing fraud and managing risk. What stands out about Sift is its ability to leverage machine learning and real-time data to detect fraudulent activity. **What do you dislike about Sift?** Like with any fraud detection tool, there’s a risk of false positives, where legitimate transactions get flagged as fraudulent, which can frustrate customers or lead to loss of business. **What problems is Sift solving and how is that benefiting you?** Sift helps detect account takeovers by analyzing user behaviors like login patterns, device usage, and geographical locations. ### 16. I've learn a lot using Sift **Rating:** 5.0/5.0 stars **Reviewed by:** Verified User in Financial Services | Mid-Market (51-1000 emp.) **Reviewed Date:** August 06, 2025 **What do you like best about Sift?** I like it because it has multiple features and options to complete my assessments. **What do you dislike about Sift?** sometimes links users by IP address that are public and these customers are flagged increasing their risk scores. **What problems is Sift solving and how is that benefiting you?** It gives a better understanding of hiden connections between customers or persons that are sharing payment methods, devices or billing addresses. ### 17. Starting to doubt SIFT is the correct tool for us. **Rating:** 2.0/5.0 stars **Reviewed by:** Berend v. | Small-Business (50 or fewer emp.) **Reviewed Date:** May 16, 2024 **What do you like best about Sift?** We use SIFT a couple of years, it brought our fraud to nearly non-exsitence, what is great, Ease of use is ok from a technical point of view, we can setup lot of different things that we use to prevent and fight fraud. Lot of settings are trial and error. **What do you dislike about Sift?** What we do not like and what worries us, is the fact our whole customer base is getting to a score of 100, according to SIFT all our customers are fraudsters, it does not take long before we cannot use the scoring system anymore. **What problems is Sift solving and how is that benefiting you?** As i stated earlier, SIFT was in the beginning difficult to master and wAs i stated earlier, SIFT was in the beginning difficult to master and we did not get alot of training in the beginning, we always worked with the information we got, turning orders to manual bad and manual good to "train" the system. However, we begin to loose trust in how SIFT is handling our orders and customers to the point we cannot trust the score of SIFT anymore. Our whole customer base seems to be in the right side of the spectrum, all in the 90. Most of our good customers are red, also bad users are bad. We can almost see no difference anymore, and this makes it harder and harder to maintain. For example we have customers with a good reputation with us, that have a score of 100. We also have fraud messages from our payment provider from users that are not scored that high. But the avarage score is getting higher and higher, and we getting frustrated how to solve it, SIFT makes connections that are not trustly anymore. e did not get alot of training in the beginning, we always worked with the information we got, turning orders to manual bad and manual good to "train" the system. However ## Sift Discussions - [How does Sift help detect and prevent account takeover attempts?](https://www.g2.com/discussions/how-does-sift-help-detect-and-prevent-account-takeover-attempts) - 1 comment, 1 upvote - [How does Sift help businesses protect the full customer journey from fraud?](https://www.g2.com/discussions/how-does-sift-help-businesses-protect-the-full-customer-journey-from-fraud) - 1 comment, 1 upvote - [How does Sift help reduce friction for trusted users while maintaining security?](https://www.g2.com/discussions/how-does-sift-help-reduce-friction-for-trusted-users-while-maintaining-security) - 1 comment, 1 upvote - [What is Sift best used for?](https://www.g2.com/discussions/what-is-sift-best-used-for) - 1 comment, 1 upvote - [How does Sift use machine learning to adapt to evolving fraud patterns?](https://www.g2.com/discussions/how-does-sift-use-machine-learning-to-adapt-to-evolving-fraud-patterns) - 1 comment, 1 upvote - [View Sift pricing details and edition comparison](https://www.g2.com/products/sift-s-ai-powered-fraud-decisioning-platform-sift/reviews?filters%5Bsentiment_snippet%5D=1363676&qs=pros-and-cons§ion=pricing&secure%5Bexpires_at%5D=2026-08-14+23%3A21%3A59+-0500&secure%5Bsession_id%5D=6ade2df9-a71b-4c8a-80b0-08d50bd4d7ad&secure%5Btoken%5D=7b5a5561bec11a1842942cb8ce51e08896dde9646737a3e8083fd1799096bdf9&format=llm_user) ## Sift Integrations - 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HIPAA Compliant - AI Copilot - Self-Service Access Request - User Provisioning - Audit Trail - Third-Party Integrations - Real-Time Notifications - Active Directory Integration - Authentication - Compliance Management - Workflow Management - Access Controls/Permissions - Access Management - Secure Login - Customizable Branding - Real-Time Monitoring - Security Auditing - Policy Management - Data Synchronization - Collaboration Tools - API - Unified Directory - Multi-Factor Authentication - Biometrics - Activity Dashboard - Generative AI - Credential Management - Event Logs - Real-Time Analytics - Password Management - Access Certification - Self Service Portal - Mobile Access **Detection** - Real-Time Monitoring - Alerts **Administration** - Policy Management - Application Integrations - Password Synchronization - Password Management - Credential Management - Password Policies **Agentic AI - Accounting & Finance** - Autonomous Task Execution **Transaction Monitoring - Financial Fraud Prevention** - Payment monitoring - Real-time risk monitoring - Threshold Management - Internal Fraud Monitoring - Activity Monitoring - Transaction Monitoring - Access Management - Case Management - Electronic Payments - Compliance Management **Intelligence** - Transaction Scoring - Risk Assessment - Intelligence Reporting - ID Analytics **Analysis ** - ID Analytics - Intelligence Reporting - Incident Reports - Reporting/Analytics **Identity & Authentication - Financial Fraud Prevention** - Identity Verification - MFA - Data Verification **Detection** - Fraud Detection - Alerts - Real-Time Monitoring **Administration** - Fraud Markers - Transaction Scoring - Blacklisting **Behavioral & Analytics Detection - Financial Fraud Prevention** - Behavioral Analytics - Bot Detection - Predictive Analytics - Real-Time Analytics - Anomaly Detection - Check Fraud Detection **Response** - Device Tracking - Fraud Markers - Blacklisting - Bot Mitigation **Agentic AI - Fraud Detection** - Cross-system Integration - Adaptive Learning - Decision Making **Audit & Compliance - Financial Fraud Prevention** - Audit Trail - Reporting **Additional Functionality** - Onboarding - Risk Management - Digital Signature - Workflow Management - Data Capture and Transfer - Consent Management - Customer Data Management - AI Copilot - Mobile Access - For Financial Institutions - Audit Trail - Video Conferencing - Behavior Tracking - API - Compliance Management - Blockchain Support - SDKs - Search/Filter - Geolocation - Generative AI - Multi-Language - Scheduling - Authentication - Case Management - Approval Process Control - Alerts/Notifications - Access Controls/Permissions - Lifecycle Management - Secure Data Storage - Address Validation - Biometrics - Document Management - Forms Management **Additional Functionality** - Data Mapping - Generative AI - AI Copilot - Data Visualization - Risk Assessment - Real-Time Updates - Risk Analysis - Custom Fraud Rules - Real-time Alerts - Data Synchronization - Financial Transaction Approval - Payment Fraud Prevention - Data Discovery - Third-Party Integrations - Financial Analysis - Real-Time Data - Reporting & Statistics - Authentication - Activity Tracking - API - Transaction History - For eCommerce - Activity Dashboard - Risk Alerts - For Banking - AI/Machine Learning - Alerts/Notifications - Data Import/Export - For Insurance Industry - PSD2 Compliant - Data Capture and Transfer - Search/Filter - Alerts/Escalation - Behavior Tracking - Customer Accounts ## Top Sift Alternatives - [Kount](https://www.g2.com/products/kount/reviews) - 4.8/5.0 (111 reviews) - [SEON](https://www.g2.com/products/seon/reviews) - 4.6/5.0 (382 reviews) - [Signifyd](https://www.g2.com/products/signifyd/reviews) - 4.6/5.0 (331 reviews)