Financial Services Organization Drives Customer Success with Semaphore Cloud-based, Smart Metadata Hub

Whether your organization operates in capital markets, banking or the insurance industry, you need solid information to make decisions that drive positive organization, stakeholder and customer outcomes. As the volume of data flowing into financial organizations continues to explode, the ability to rapidly access, manage and make sense of it is key to managing risk and improving ROI.

Regardless of sector, financial services organizations require innovative solutions that allow them to:

• Unify and harmonize a variety of data types from disparate sources to provide a single view of the organization.

• Provide relevant information to a broad range of internal and external stakeholders in realtime for analysis, reporting and management.

• Better meet compliance requirements with regulatory mandates to decrease risk and avoid sanctions. 

The company realized that key to managing enterprise data is harmonization, the ability to provide a holistic view of all information, structured and unstructured, regardless of location and type. This data is vital to managing the business and providing a robust customer experience in today’s ever-changing environment.

The institution chose Progress^® Semaphore™Cloud because it provides a flexible solution that supports their ability to geographically segregate enterprise data, which allows the organization to better meet search and compliance requirements. The environment is cost effective as it eliminates expenses associated with hardware acquisition, provisioning and maintenance. And it reduces the maintenance hassles of software installation and support of applications on company computers or in data centers.

As part of their initiative to migrate the company intranet to Office 365/SharePoint Online, they identified a need to evaluate the efficacy of manual content classification. Internal users performed manual tagging of information assets, yet the results were not consistent. 

When documents spanned multiple pages, they were broken into smaller documents, which increased the corpus for manual tagging and user workload. The result – an increase in tagging errors.

They began by using Semaphore Knowledge Model Management (KMM) to create a multi-language (French & English) enterprise model to support a broad range of use cases and reflects the policy documents, procedures and end user content throughout the organization. They worked with multiple stakeholders, including human resources, IT, project management and subject matter experts, to enrich the model with synonyms and alternative labels that reflect the content to improve model quality. The model was further enhanced with additional vocabularies and relationships between vocabularies were identified.

The model was published and combined with AI, natural language processing and machine learning strategies to perform bulk classification of site collections as well as ongoing, auto-classification of content stored in SharePoint Online. This robust classification strategy incorporates organizational data, conversations happening throughout the enterprise and end-user content stored in Microsoft repositories.