The financial services industry must continually adapt to new regulations and evolving business needs, requiring frequent updates to automated systems. A common challenge is integrating new types of extracted information and data into these systems, such as the need to add extracted information from letter of instruction, which facilitate bulk salary transfers.
In our previous blog post, "Simple Steps to Build a Model for Bulk Salary Transfers with Datasaur Dinamic", we outlined the process of building an extraction model to enhance bulk salary transfer processes with Datasaur Dinamic. Now, let's explore how this technology can assist in expanding labels to accommodate new requirements, such as transitioning from single-currency to multi-currency transactions.
Imagine a bank that previously handled single-currency bulk transfers moving forward to process multi-currency transactions. This requires the system to recognize and extract new details like different currencies and their exchange rates. To achieve this, the existing model needs to be updated. This involves re-labeling the dataset to include these new entities and re-training the machine learning models for accurate recognition.
Updating your system doesn’t have to be cumbersome. Datasaur’s ML-Assisted labeling simplifies the re-labeling process significantly. Here’s how you can effortlessly integrate new data entities into your model:
Once your data is fully labeled, re-training is simple with Datasaur Dinamic. Follow these steps to update your model:
This straightforward process allows you to develop an updated model, ready to handle new requirements efficiently.
In our previous blog post, "Simple Steps to Build a Model for Bulk Salary Transfers with Datasaur Dinamic", we demonstrated how an extraction model could enhance bulk salary transfer systems at Indonesia's largest bank. By adopting Datasaur's automated data extraction technology, the bank improved operational efficiency by up to 60%. This substantial enhancement allowed staff to focus on verifying and validating data, reducing human errors by over 60%.
Imagine extending this improved efficiency to manage multi-currency transactions. The system requires updates to identify and extract essential details such as various currencies and their exchange rates. Datasaur streamlines this transition through:
With Datasaur Dinamic and ML Assisted Labeling, upgrading automated bulk salary transfer systems becomes a streamlined process. This empowers financial institutions to manage complex tasks with greater accuracy and reduced processing times.
Adapting automated systems to new requirements is crucial for banks to stay competitive and compliant. Datasaur Dinamic, combined with ML-Assisted Labeling, offers a powerful and efficient solution for updating machine learning models. This ensures smooth upgrades, like moving from single-currency to multi-currency transactions, without hassle.
Ready to enhance your labeling efficiency or boost your NLP capabilities? Contact us at sales@datasaur.ai to find out how our solutions can streamline your operations. Book a demo today and experience the benefits of efficient, automated data management and advanced NLP solutions.