All Use Cases

Data entry automation

Intelligent data capture to speed credit decisioning
Extract transaction data from prospective borrower’s documents in minutes, eliminating manual data entry and streamlining credit referencing
Logo | Digilytics
#Artificial intelligence
#Data analytics

Revolutionize your processing of documents during customer onboarding

A powerful AI-based solution that validates and extracts data from submitted documents

Benefit from modern credit decisioning tools

Now available as part of the Sopra Financing Platform's Portfolio Management module, Digilytics’ unique technology enables financial data to be extracted from scanned financial documents such as bank statements and tax returns using machine learning and AI, then passed to downstream applications such as credit decisioning tools in their preferred data formats, even emulating open banking data feeds.

By eliminating the need to manually extract and re-key data from documents, the solution can significantly boost productivity and reduce costs whilst enabling more rigorous analysis of income and expenditure in less time.
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    Capture data from multiple sources

    Continuously learning, most bank statements and financial documents can be validated and read with a high degree of accuracy.

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    Extract data in multiple languages

    Even if your staff aren’t familiar with the language or the institution, documents can be validated and data extracted.

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    Integration with existing systems

    As well as SFP Portfolio Management, the solution can deliver formatted data to your existing solutions.

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    Intelligent automation and decision making

    Combine open banking with best-in-class extraction capabilities to process documents at speed and scale.

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    Secure and reliable document handling

    Ensure documents are managed securely, safeguarding client data whilst enabling audit trails.

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    Best-in-class user experience

    A future-proof, AI-powered service that is easy to integrate and tune to the requirements of your business.

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