With the number of electronic records increasing every year, organizations are turning to Automatic Categorization and Classification tools to assist their Records Managers. Automated Categorization processes eliminate the possibility of user error brought on by the volume and variety of data.
By automating the decision process, the system maintains a high level of control of the retention program, keeping the organization in compliance for their electronic records without a lot of end user interaction.
Automate the Categorization Process
With Feith, organizations no longer need to ensure that all employees are using the same methods to categorize records. The system does it for them. Auto-categorizer is trained to process records, regardless of whether they are structured.
Records Managers using Feith’s Auto-categorizer can also show a defensible categorization approach based on machine learning. Auto-categorizer features:
Auto-categorizer Provides Context of Records
Before Auto-categorizer is initiated, the organization needs to be certain that its Records Management program is complete. Records classes and retention times should be established across all departments. Data that needs to be protected should be inventoried at this point as a base for identifying sensitive information.
To start, the system is introduced to your business taxonomies. They are the backbone of Auto-categorizer, providing a structure to learn from as well as describing the knowledge of your organization. The machine will learn that lead is a type of metal and that a document containing the word lead could also be referring to the act of guiding a group. Feith will help your business create a taxonomy that will work for both users and the machine.
Synonymous labels are applied to terms while related terms are identified. Auto-categorizer is then fed sample documents identified by the organization as part of the taxonomy. The machine learning algorithm can then determine whether or not the created taxonomy describes the content. Auto-categorizer can also identify any remaining keywords that should be added to the taxonomy. Once the tagging process is configured, rules are applied, and the system can accurately tag content. Accurately tagged content is content that is in compliance with both internal and external regulations.
Auto-categorizer is Defensible & Compliant
Organizations need to retain business records to comply with legal and regulatory requirements for retaining records. Categorizing an organization’s documents means meeting these requirements, supporting internal processes, customer needs, and stakeholder expectations. Categorizing documents also makes an organization defensible, preventing sanctions and legal judgments.
Auto-categorizer is battle-tested and capable of withstanding scrutiny. Feith’s transparent process is easily tuned by Records Managers to meet their compliance initiatives. Auto-categorizer can also demonstrate precision-driven results through either dashboards or reports. By taking that responsibility off the end-user, Auto-categorizer improves the consistency of categorization. As changes in strategy, systems, personnel, and regulations occur, Auto-categorizer’s machine learning rules will update as well.
Automatically categorizing records makes it possible for Records Managers to demonstrate a defensible approach to categorization. This approach is based on both statistical sampling as well as quality control. Risks of fines and sanctions are minimized by the tool’s ability to provide evidence of accuracy.
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Control Security & Privacy
With Auto-categorizer, you can automatically categorize content, put it in a folder, and apply policies to govern security. This content can be moved inside as well as outside of company boundaries. If the content is tagged as sensitive material, firewalls, data loss prevention tools, and information management tools can prevent it from being shared based on your company’s security policies. Sensitive data tags can be used to encrypt emails out of the organization, prevent the copying of content, or prevent the sharing of information altogether.
Organizations must protect all their data due to new privacy regulations, an increase in data breaches, and the importance of protecting business-critical information. Privacy laws require the protection of personally identifiable information (PII) about customers, as well as employees. Auto-categorizer comes with pre-configured tools to identify PII. To train the system further, Auto-categorizer can be configured to identify trade secrets, financial data, and other sensitive business information.
Specify Retention & Disposition
To stay in compliance with regulations, organizations need to retain and dispose of records within their given lifecycles. Auto-categorizer ensures that records are marked for disposition according to laws as well as organizational policies. Disposing of these records at the end of their lifecycle prevents them from being subjected to legal action.
An organization can save on storage costs by disposing of duplicates and records at the end of their retention periods. With Auto-categorizer, a document will be automatically set for a notification to delete according to the organization’s retention requirement. At the end of its lifecycle, the Records Manager responsible for disposal gets a reminder to disposition the document. New rules or regulations will be written, business requirements will change, and case law will evolve. Categorization and retention schedules will need to be updated periodically.
Auto-categorizer’s machine learning rules will always update to meet those changes. Auto-categorizer is a great way for your organization to keep on top of the growing record volumes while also remaining on budget. Users will no longer have to identify the category of every ingested document by hand, which opens their time to focus on more critical tasks.