Rating Report Automation

Objective



To use the AI technique to improve report writing.
To assist analysts by automating their entire report generation processes.

Pain Points

  • 1

    There were numerous industries & thousands of borrowers associated with the industry which was served by our client.

  • 2

    Creating an industry-specific corpus of words & sentences as we can't have the same types of sentences/words for all industries.

  • 3

    Creating dynamic & industry-specific templates for rationale reports, rating reports & press releases.

  • 4

    Creating industry-specific NLG models and validating the output against each industry.

Solution Given

  • 1

    Natural Language Generation technique to generate the Press Release, Rating Report & Rational report automatically for one of the largest Credit Rating Agencies in India.

Solution Highlights


  • 1

    Uploaded the corpus of words & sentences for various industries.

  • 2

    Created various models and grouped them based on the industry's homogenous characteristics.

  • 3

    Templatized the reports such as rationale report, rating report & press release.

  • 4

    Used models from probabilistic classifiers, deep learning and natural processing to transform the corpus of sentences into a meaningful paragraph.

  • 5

    Trained the models & compared the outputs with the old reports & press releases.

  • 6

    Generated the reports automatically and send them for the analyst's review.

Key Benefits


Benefits of the Case Study to help you understand our Product and reach of Services in a more convenient way

BEST PRACTICES

With the proposed solution, in the first phase, clients were able to automate their entire report generation processes by 60% with an accuracy of around 75%. With multiple rounds of iteration and periodic reviews of the models done based on analyst's review and hyper parameter tuning and corpus updates, we can get the model accuracy of 85%.

Case Studies


Banking

Corporate

Infrastructure

Health

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