As ChatGPT is still all the rage and has seen one million registrations in the first couple of days after its release, OpenAI has released their latest language model GPT-4, the long awaited successor of GPT-3. GPT-4 is a further development of GPT-3, or GPT3.5, bringing with it a range of new capabilities and enhancements […]
The Case
As a leading credit bureau, Creditreform publishes credit risk analyses to provide banks with auditing and scoring reports. However, analysts spent a lot of time in creating these reports manually.
The Challenge
Analysts had to spent many hours creating credit risk analyses and scoring reports. The creation of these reports included many repetitive tasks.Their goals:
- Relieve employees
- Generate high-quality reportings and analyses
The Solution
Creditreform knew they had to find a way to automate the creation of credit risk audits. That's why they chose AX Semantics. Thanks to the automation, analysts have more time for other important tasks and are relieved of the creation of analyses with repetitive components. As content automation relies on structured data and statements initially texted by the employees of Creditreform, the analyses are of high-quality, as possible human errors are eliminated.
Example of a detailed rating on the Creditreform website
The Results
The analysts of Creditreform are saving hundreds of hours they would need to create reportings and analyses. As the reportings are now created automatically, they have a standardized high-quality level, as human errors are eliminated. They also increased the turnaround times of the creation process thanks to automation. Because of these positive developments, Creditreform has built an internal team to provide NLG (Natural Languages Generation) services for banks based on their expertise and the AX Semantics technology. Creditreform uses content automation as a core element for the creation of MaRisk reports (Minimum Requirements for Risk Management), certified by the German Federal Financial Supervisory Authority.
