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STORYBOOK OÜ: Science-based Credit Score – an Internationally Recognised Credit Management Tool at Everyone’s Command!

Inforegister’s Credit Score is now an internationally recognised credit management tool in use in a number of foreign credit insurance groups. The Credit Score was developed in co-operation of data scientists from Softwade Development and Applications Competence Center and the University of Tartu. We used machine-learning methods in developing the model, including unsupervised learning algorithms that can discover hidden connections and based on these predict whether a company is likely to become insolvent. The model is highly accurate – 99.5%!

The data model constantly takes into account changes in input (tax arrears, problems with companies related to board members, paid taxes etc).

The Credit Score predicts the possibility of the company becoming insolvent or facing compulsory dissolution within the next 12 months and expresses the maximum probability of the company not meetings its obligations to creditors. The Credit Score is always on a scale of 0 to 1, where 0 means low credit risk and 1 means high credit risk. To help make credit assessment easier and decision-making faster, all scores have been divided up into five credit risk classes.

These classes work like the traffic lights: green for ‘go’, the road is clear for making a deal; yellow for ‘slow down’ and check the situation, and red for ‘stop’ and do not extend credit.

Class 1 – Reliable (0 – 0.31) consists of companies that have submitted all their reports and have no tax arrears or these are small in comparison to other companies; sales on standard terms is recommended.

Class 2 – Neutral (0.32 – 0.41) is made up of companies that may have unsubmitted annual reports and may have tax arrears. Companies with a negative reputation may be connected to members of the management board. You can sell to this company on standard terms but we recommend you closely follow payment patterns.

Class 3 – Borderline (0.42 – 0.52) has many starting companies that are still ‘green’ (less than two years in business) belong to this category. Reports are incomplete or not submitted properly. The company may have tax arrears. When selling to this client, it might be beneficial to seek additional information. Adjust payment terms or request prepayment to a level that will mitigate any risks.

Class 4 – Problematic (0.53 – 0.73) entails companies with missing annual reports or delays in submitting them. The company displays substantial and/or persistent tax debts. With this client, only prepayment should be accepted or additional guarantees should be requested.

Class 5 – Risky (0.74 – 1) comprises companies that routinely have not submitted annual reports for several years and have accumulated significant debts. Usually, several tax declarations are missing as well, and a number of companies with a bad reputation may be related to the members of the management board. With this client, only prepayment should be accepted. If a client in this credit risk class has overdue invoices, then repayment is unlikely.

You can use the Credit Score for:

  • Pre- and post-sales checks
  • Setting credit limits and payment deadlines
  • Creating a unified credit policy within the company
  • Integrating with sales/accounting systems with instant updates
  • Get weighted average Credit Score of board member’s companies as a csv file
  • List of machine-readable data: Register API

See how The best leaders make Credit Score Work for Them ke uidas parimad juhid Krediidiskoori on enda heaks tööle pannud.

‘Precise and intelligent credit management every day. Where it is needed most.’

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STORYBOOK OÜ

07.01.2019

Uus ettevõte lisatud.


Registrikood "14636888".
Nimi "STORYBOOK OÜ".

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STORYBOOK OÜ

07.01.2019

Juhatuse liikme lisamine.

Juhatuse liige Marie Rosin (04.05.1970) lisatud ettevõtte juhatusse

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