ENFINT REPORTING
Automate your company's regulatory reporting process in compliance with your regulator's requirements across any jurisdiction, reduce time spent on report creation and validations and enjoy a user-friendly interface.
ENFINT REPORTING
Automate your company's regulatory reporting process in compliance with your regulator's requirements across any jurisdiction, reduce time spent on report creation and validations and enjoy a user-friendly interface.
Advantages
- Automated values calculation in reports
- Performs automated error validations on report data
- Comprehensive logging of user actions
- Working with large data volumes with excellent system performance
- Automating reporting process for any regulator in any country
- Staying up-to-date with evolving regulatory requirements and changes
CASE STUDY on the example of UAE reporting to the Dubai Financial Services Authority
Choose from two visualization formats, work with forms grouped by meaning into categories, benefit from status indicators and displaying deadlines.
Use the opportunities provided by the Data Quality Control system, which includes source data validations, report results validations and cross-form validations. Manage validations by modifying existing and adding new ones.
Utilize the ability to drill down from the Main report to the transactions/deal level in Detailed report to ensure the accuracy of the results.
Use Report Configurating Manager to change reports generating rules or edit incorrect values directly in the report.
Analyze report data in dynamics in comparison with other reporting periods.
Use a broad range of analytical tools such as Calculation, Data Grouping, Totals Calculation, Control break, Pivot Tables and much more.
Create real-time graphs such as Histogram, Pie chart and Bar chart for management reporting purposes.
Notebooks
To cover model development, training and verification, Dognauts provides managed development environments based on Jupyter, Visual Studio Code and RStudio.
MLflow
To track experiments and register models, integrated MLflow component is ready.
It also provides a web interface allowing users to track logged results and catalog both candidates and production models using MLflow Model Registry.
It also provides a web interface allowing users to track logged results and catalog both candidates and production models using MLflow Model Registry.
Airflow
To orchestrate batch jobs Apache Airflow along with Git integration is used.
The component handles not only model verification but also deploying of complex batch models. Such models may rely on ETL processes, industry-proven frameworks (e.g., Apache Spark) and variety of other solutions.
The component handles not only model verification but also deploying of complex batch models. Such models may rely on ETL processes, industry-proven frameworks (e.g., Apache Spark) and variety of other solutions.
Seldon Core
To run models as online services, Seldon Core component provides quick deployment pipelines.
Target REST service can be deployed with no extra coding, based on previously registered model in MLflow. As an advanced option, an inference graph can be customized additionally to support input and output transformers, ensemble of models or even A\B testing.
Target REST service can be deployed with no extra coding, based on previously registered model in MLflow. As an advanced option, an inference graph can be customized additionally to support input and output transformers, ensemble of models or even A\B testing.
Feature Store
To discover, manage and serve your data, Dognauts has built-in feature store component based on Feast and its API. It allows users to classify and manage data properly within historical storages and online databases.
Feast web interface is helping users by proper visualization of configured features, feature groups and services.
Feast web interface is helping users by proper visualization of configured features, feature groups and services.
Model Monitoring
To cover monitoring part of the lifecycle, Dognauts provides a set of monitoring capabilities based on Evidently, Grafana, Prometheus and Jaeger.
The combination allows to monitor your models continuously from different angles, analyzing tracing data, technical metrics thresholds and various business data through a set of available monitors. Triggers can be configured to notify users when certain conditions are met.
The combination allows to monitor your models continuously from different angles, analyzing tracing data, technical metrics thresholds and various business data through a set of available monitors. Triggers can be configured to notify users when certain conditions are met.
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