Check interest rate change clauses in savings contracts with artificial intelligence
“Interest rate change clauses which grant the credit institution an unlimited power to change the interest rate in the case of long-term savings contracts are invalid.”
– Judgment from the German Federal Court of Justice of 17 February 2004 – XI ZR 140/03
The artificial intelligence semantha® supports German banks in checking existing savings contracts for invalid interest rate change clauses in order to be able to calculate and form appropriate provisions.
In our blog post „Interest rate adjustment clauses: With artificial intelligence, banks quickly gain clarity on their contractual situation“ you will find a detailed explanation.
Legal clarity made simple
With Germany’s Federal Court of Justice’s ruling on premium savings contracts, banks and customers gained legal certainty, but banks are now faced with an enormous additional workload. Heidelberger Volksbank would have had to check a large amount of contracts manually and within a very short period of time to avoid lawsuits.
semantha® helps precisely determine necessary provisions and thus realistically present the risk in the balance sheet. All this in a fraction of the time.
Determine provisions more precisely
“The previous time-consuming review of our contracts and their documentation required 20 working days. The AI-based solution completed the same work in 2 hours. This resulted in a 98.75% reduction in the resources required for this – sensational!”
We can help here, too:
Legal and Compliance Checks
Optimize Retail Banking
The most frequently implemented use cases in finance.
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With semantha we have developed an AI tool that overcomes the weaknesses of conventional matching tools. The application does not compare whether certain terms occur in documents, but reads the documents at the level of meaning. And it does so within a few moments.
- Ranking of top candidates at the touch of a button
- Overview of the best internal candidates for any skills
- More objective selection of candidates
- Acceleration of the selection process by up to 50%
- More time for interviews to ensure human fit
Your company has large masses of unstructured text documents. One of the daily challenges is to search these documents for specific content, whereby normal search functions only offer a simple “keyword search” that does not lead to the desired results. This is particularly due to the fact that, on the one hand, it is not known exactly how a topic was formulated and, on the other hand, the same topics are also formulated quite differently in the various documents.
In your company, many procedures on the same topic are processed. Despite always having similar presentations in the pleas and repetitive correspondence with companies, insurers and clients, these documents have to be read and analysed at great expense. Although content can be divided into certain categories, the problem is that similar issues are formulated in completely different ways, which makes it seem impossible to automate the processes.
You have to reply to numerous pleas, such as lawsuits or statements of defence, and repeatedly come across similar submissions. In most cases, you can use excerpts from past responses as a basis for the new plea. However, the classification of the individual submissions of the newly received pleas is the biggest challenge.