Saifr-Language-Suggestion
Version: 1
Companies operating in the financial sector are heavily regulated. Their communications with the public may have to comply with rules governing broker-dealer communications and or investment adviser advertising, or both. Financial regulations are critical as they safeguard investors and maintain the health of capital markets. However, compliance can be manual, time-consuming, and costly. If mismanaged, an organization can face reputational damage and hefty fines. Such regulations often require that content meant for public distribution undergo review, tracking, and compliance verification.
Saifr’s mission is to make regulatory compliance faster, less expensive, and more accurate via human augmentation.
Saifr has created natural language processing (NLP) models that scan content and can highlight potentially noncompliant language as well as suggest more compliant language, thereby helping users reduce regulatory risk exposure.
If you need to access to the model artifacts, please contact contact@saifr.ai
Intended Use
The Language Suggestion Model serves as a powerful tool for communications compliance. Once a sentence has been flagged as potentially noncompliant, this model recommends an alternative sentence structure for consideration. Its aim is to provide a possible rewrite that presents a more compliant, fair, and balanced version helping users better adhere to relevant regulatory guidelines.License
The use of this model is subject to the Saifr License Agreement available at https://saifr.ai/azure-custom-license Use of Saifr’s models is subject in all respects to the custom license agreement between Saifr and the end user. Saifr models are not intended to replace the end user’s legal, compliance, business, or other functions, or to satisfy any legal or regulatory obligations. Note that all compliance responsibilities remain solely those of the end user and that certain communications may require review and approval by properly licensed individuals. Saifr is not responsible for determining compliance with rules and will not be liable for actions taken or not taken based on model use.Sample Inputs and Outputs (REST)
Example Request
You can use cURL or any REST Client to send request. Just add your token and test. curl https://<url.com> -X POST -d '{ "sentence": string }' -H "Authorization: Bearer <TOKEN>" -H "Content-Type: application/json"
Sample Input
{ "sentence": string }
where-
- sentence: A noncompliant sentence (Required)
Sample Output
{
"input_sentence": string,
"output_sentences": string[]
}
where-
- input_sentence: The input noncompliant sentence.
- output_sentences: A numpy array of suggested compliant sentences for the given input sentence.
{
"input_sentence": "This is a test sentence.",
"output_sentences": ["unable to rewrite"]
}
Model Specifications
Context Length2048
LicenseCustom
Training DataSept 2024
Last UpdatedNovember 2024
Input TypeText
Output TypeText
PublisherSaifr
Languages1 Language