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Contract analytics: Modern contract management in the cloud

How contract analytics works and the potential of AI-powered risk identification.

Andreas Dangl

Created on 21. December 2020

Contracts govern our business relations in both the national and the international arena, whether between individuals or between companies. The accelerating momentum behind globalization and the worldwide digital revolution, coupled with high standards for risk management, transparency, and legal certainty have made it imperative to manage contracts efficiently and in compliance with prescribed procedures.


Decisions have to be made rapidly and flexibly. Over time it can become a challenge, particularly for larger organizations, to keep an overview of all the contracts. Failing to do so, however, can expose a company to needlessly high business risks. Contract analytics, a process arising from the field of artificial intelligence, is one solution to this problem. The method provides support for contract handling and management throughout the entire contract lifecycle by focusing specifically on the qualitative analysis of textual content.


But how does contract analytics work and what is the true potential of AI-based risk identification?


How does contract analytics work?

Contract analytics is not a specific technology, but rather a combination of several methods in one process. AI-based contract analytics generates a comparison between target states and actual states, uncovering contractual risks in the process. As an example, the method detects deviations from standard clauses, allowing businesses to respond proactively and to control processes reliably to mitigate risks. This is accomplished by integrating various models derived from computational linguistics, statistics, and data science. Using AI, these models are trained to process different types of contracts by analyzing them to find common patterns. This enables the system to recognize written texts and to assign meaning to individual words based on semantic analysis.


Neural models are used to classify contracts, extract metadata and clauses, and to provide the basis for reliable analysis. Companies seeking to launch the contract analytics process and leverage this approach to its fullest potential, however, they need to start with a high-quality data base. Most businesses are still managing their contracts as hardcopy files, making digitalization and data retrieval a pivotal part of the process. To make contracts machine-readable, a process called optical character recognition (OCR) is used to recognize text characters. Following an OCR conversion, artificial intelligence is used to analyze the data.


The contract analytics process

1. Digitalization and readability with OCR

OCR refers to a process that converts images into their text equivalents. This means that OCR begins by generating machine-readable text from a contract. Any commercially available scanner can be used to capture the file. The OCR engine then analyzes the file, a PDF for example, in terms of its components at the text character level. The program recognizes the text and inserts it into the source file.


2. Classifying the contracts

The second step is to classify the contracts by means of neural networks. Artificial intelligence identifies specific categories based on the content, such as maintenance and service contracts.


3. Understanding and extracting contract data

Specific contract data is extracted using the textual data base generated by OCR and the subsequent classification. Neural models ensure that general information about terms such as the duration of the contract and the notice periods, as well as more concrete information – like the location of the plant and the required tasks in a maintenance contract or the starting salary in an employment contract – is identified.


4. Identifying contract clauses

Companies frequently formulate standard clauses that have been reviewed from a legal perspective and optimized for their own purposes. When analyzing third-party contracts, AI recognizes what type of clause is being analyzed (such as a confidentiality clause or a liquidated damage provision) and evaluates the degree of deviation from the standard clause.


5. Mitigating risks

In the final process step, contract data such as deadlines is displayed in a clearly structured format, and a reminder feature ensures compliance. Generated processes make sure that obligations (such as performing the scheduled maintenance in compliance with the contractual obligations in a maintenance contract) are fulfilled and logged. Proof of compliance with contractual obligations occurs automatically.


After evaluating the discrepancies between clauses and standard clauses, AI suggests processes providing for, say, a review of the deviations and for new negotiations where necessary.


Why contract analytics pays off for any business

The potential for optimization offered by AI-based technology permeates every division of a business and facilitates a marked increase in efficiency. By intelligently automating routine tasks, contract analytics delivers enormous time savings.


A key benefit resulting from applying artificial intelligence is the more streamlined risk assessment that intelligent dashboards facilitate by providing a clear overview of all relevant data.


For one, a structured and consolidated view of all commercial contract data supports budget compliance. Secondly, contract analytics helps to ensure that contract requirements are fulfilled on time and prevents agreements from being inadvertently prolonged or terminated.


Categorizing contracts according to status, contract type, and contract party provides a concise overview of the individual phases in the contract lifecycle. Automated processes and a preformulated repository of clauses ensure consistency in the contract drafting process.


If a business chooses a state-of-the-art solution based on the cloud of an independent European cloud provider, the contracts are available to authorized persons at any time and from any location. In addition, contract analytics solutions feature a sound and robust role and authorization concept and are certified for data security and compliance with data protection regulations according to the GDPR.


Now, nothing stands in the way of state-of-the-art contract management!


Test now and experience how contract analytics optimizes your contract lifecycle management.