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Saifr

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About

Saifr is an AI-powered compliance solution for financial institutions. It offers solutions for marketing compliance review, adverse media screening for AML/KYC, and electronic communications surveillance. Saifr's AI models are trained on high-quality, compliance-curated data and are designed to help firms comply with various financial services regulations. The platform is SOC 2 Type 2 certified, ensuring client privacy and security. Saifr's capabilities are available as APIs, allowing integration with existing systems.

Platform
Web
Task
compliance assisting

Features

api access

electronic communications surveillance

adverse media screening for aml/kyc

marketing compliance review

risk management automation

client support

adobe integration

ai compliance models

FAQs

What is RegTech?

Short for regulatory technology, RegTech is the application of technology—including AI, automation, and data analytics—to simplify, enhance, and assist regulatory compliance.

Why should I use AI for compliance?

AI can be an extra set of eyes, helping expand and deepen compliance oversight. Its ability to rapidly process huge volumes of data can give compliance teams easy access to real-time analytics and risk reporting.

What are the different types of AI?

Artificial intelligence (AI) is an umbrella term for many techniques that enable machines to mimic human behavior. Types of AI include: Rules-based, Machine learning, Natural language processing, Generative AI...

What are some risks of using AI?

AI risks range in significance, including inaccuracy, model drift, data privacy risks, and lack of model transparency. Most risks associated with AI can be mitigated with appropriate human oversight and controls.

How were Saifr’s AI models trained?

SaifrReview and SaifrScan were trained on high-quality, compliance-curated data that represents over 20 years of work by thousands of marketing and compliance experts in various lines of business within the financial services industry.

Which regulations can Saifr help address?

Across three product areas, Saifr helps firms comply with aspects of numerous financial services regulations: Public communications: FINRA 2210, SEC 482, SEC Marketing Rule; Adverse media screening: Anti-money laundering regulations...

How does Saifr’s AI stay up to date with regulations?

When regulations change, our compliance and data science teams work together to fine-tune and validate our AI models with our SME team.

How does Saifr use AI ethically/responsibly?

Saifr’s human-centric approach to AI recognizes the need for transparent, explainable, unbiased, and representative systems. There’s a whole team of humans in the loop throughout model development...

How does Saifr protect client privacy and maintain security?

SaifrReview, SaifrScan, and SaifrScreen are SOC 2 Type 2 certified, which involves an annual, independent audit including testing and validating of security and privacy controls.

Can Saifr integrate with existing systems?

Yes, all Saifr’s capabilities are available as APIs.

What industries and regions does Saifr serve?

SaifrScan, SaifrReview, and Saifr eComms are designed for financial institutions in the U.S. SaifrScreen helps U.S. and multinational firms, including those in financial services and other industries, with their AML/KYC and Trust & Safety programs.

How can I get started with Saifr?

Request a demo. We’ll start with a conversation about your needs, then show you how we can help.

Is Saifr owned by Fidelity Investments/Labs?

Saifr is part of Fidelity Labs, Fidelity Investments’ in-house software incubator.

What is adverse media screening?

Adverse media screening reviews online and offline sources to uncover information about the data entity that may introduce regulatory and reputational risks to a business.

What is unstructured vs. structured data?

Unstructured data make up 80% of internet data and are active, real-time data that can provide a wealth of information. Structured data represent just 20% of available data and are found in a predefined format in curated databases.

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