Automate & Simplify
What do the following scenarios have in common?
In a hyper-competitive market, a bank needs to expeditiously onboard customers in order to gain market share while ensuring due diligence in order to protect itself from fraudsters and money launderers.
The compliance department at a hospital needs to collate information from various documents to file its quarterly compliance report to the regulatory authority.
A common theme across these scenarios is that each one of them requires data to be extracted from certain source documents for follow-on activities in a time-bound fashion.
Delays and incorrect data entries can lead to various downsides depending on the scenario - delayed vendor payments, impacted supplier relationships, fraudulent customers onboarded, and delayed regulatory filings. In addition, there is the hidden opportunity cost. The time spent on the repetitive, mundane task of data extraction could have been better spent on growth-generating activities.
“How can an organization build efficiencies into the document data extraction process and avoid the above-mentioned pitfalls?”
Enter Xen.AI IDP
Xen IDP provides an elegant and efficient solution that extracts, classifies, and organizes documents into a searchable repository. Its real-time dashboard provides instant intelligence from the processed documents.
Imagine the possibility accorded by the Xen IDP instant data extraction in a scenario where a banker has to perform KYC on a new customer in real time. The banker uses Xen IDP to:
- Extract the data from the customer documents.
- Enrich it with data from external sources.
- Perform validations to ensure data/customer integrity, and applies machine learning models to assess the customer’s risk propensity, all with the click of a button.
In Xen IDP, document organization is not an afterthought. As the documents are uploaded, the application automatically determines the document type, assigns a label, and stores the document in the appropriate folder based on the assigned label. In the ensuing example, the documents are assigned one of the three labels and stored in namesake folders: invoices, receipts, and bank statements. This process helps organize the documents in an ongoing manner and avoids fragmented storage of documents which is a typical scenario in many organizations. The labels in this example are only for demonstrative purposes and can be replaced with scenario-appropriate names.
Machine learning and Analytics are the cornerstones of the Xen IDP solution. From the moment the data arrives in the database, it becomes eligible for inference against pre-trained ML models for detecting anomalies, segmentation, and more depending on the use case. Dashboard provides a real-time view of the aggregate content and how the incoming document stacks against the historical data. In the below dashboard, different perspectives on invoice data are presented. Different dashboards can easily be created depending on the use case.
Xen IDP provides a powerful search engine that can search through different dimensions of the document repository. It can be configured to search through the document content, its associated metadata, PII information, image captions, and more.
Security is paramount consideration behind the Xen IDP design and deployment. User authentication and role-based access ensure that only authorized users get access to the data uploaded into the document repository.
The application instance is deployed in a single-tenant environment ensuring the isolation of each customer's database.
The application is deployed on the Azure cloud leveraging its guarantee of infrastructure reliability. Depending on the customer, it can be hosted on dedicated servers which adhere to various compliance requirements such as HIPPA, CJIS, ISO, and ITAR among others.
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