Intelligent Decision Automation

Combine business rules and machine learning to make better decisions in the digital world.

Business Rules & Machine Learning
Expert Knowledge Meets Data Knowledge

Companies rely on Intelligent Decision Automation to automate operational decisions using intelligent technologies. They combine machine learning technology with the business rules management approach to make better, predictive decisions and drive digital transformation through automation.

Unlock valuable insights from your data

Implement business domain knowledge with business rules

Make automated, consistent and traceable decisions

ACTICO Software combines business rules and machine learning




Business Rules and Machine Learning

Intelligent Decision Automation means combining knowledge from subject matter experts with knowledge learned from data to improve and automate operational business decisions. The business rule approach provides a high level of transparency and control, while machine learning generates new insights from data. The machine-learning models are then embedded in business rules and used in a controlled manner.


Intelligent Decision Automation combines business rules and machine learning

Business Rules

Subject matter experts use the business rules approach to comprehensibly define business logic such as policies, calculations or regulatory requirements. They manage the business rule models centrally and can deploy them to production systems at any time without coding.

Machine Learning

Machine learning enables the automated generation of new knowledge from data. This way, organizations can leverage their data to make better predictions, recommendations, and probabilities that are easily orchestrated together with business rules.

Business Decision

Intelligent business decisions combine business rule and machine learning models in an individual way. Whether fraud detection, product recommendation or compliance checks –  decisions are made automatically, consistently and in a traceable way.






Machine Learning Applications in the Financial Industry

The combination of intelligent technologies and automation is driving digital transformation in the financial industry. With their knowledge-intensive business models, banks and insurance companies benefit in a large variety of application scenarios.


Fraud Prevention

The automation and monitoring of financial transactions opens up large potentials to improve fraud prevention. Applying machine learning to payment data helps reduce the number of false positives. New fraud patterns can be recognized and applied automatically through self-learning models.

Market Abuse Surveillance

Machine learning can significantly improve and automate market abuse and insider dealing detection. It is able to recognize complex patterns of abusive conduct across large trading portfolios and include all kinds of information for a more accurate market abuse surveillance.

Money Laundering Detection

Artificial intelligence is able to identify highly complex relationships in data to detect money laundering in financial transactions. It helps minimize the amount of false positives, prioritize suspicious transactions and reduce the efforts for processing and clarifying each case.



Early Warning

Early warning systems allow companies to detect risks and opportunities early on and take the right actions. Using machine learning, companies can uncover new data correlations and thereby predict developments very precisely. Artificial intelligence thus enables them for example to reduce credit defaults and counteract customer churn.

Insurance Underwriting

Insurance companies can leverage existing data to improve and automate underwriting risk decisions. They apply machine learning to create more accurate risk models. By combining artificial intelligence and decision automation, insurers can reduce underwriting costs and drive the digital transformation of their core business operations.

Customer Engagement

To retain customers and increase the customer lifetime value, companies need to stay relevant to their customers and anticipate their needs. With personalized product recommendations and customer care, artificial intelligence enables smart services in real-time that meet customer demands at every digital touch point.






Definitions

What is Artificial Intelligence?

Artificial Intelligence (AI) deals with methods and approaches that enable computers to perform tasks intelligently. Machine learning is considered a key technology to achieve artificial intelligence and to realize intelligent software systems.

What is Machine Learning?

Machine learning is the application of methods to achieve artificial intelligence. Therefore, learning algorithms are used that independently generate knowledge from experience (data) with the help of computers. The result is a model that can be embedded in software systems, giving them intelligence.

What are Business Rules?

Business rules are policies and statements about how to deal with a situation depending on certain criteria. Examples include lending or pricing guidelines, compliance checks, process control specifications, calculations, and more. Most business rules exist as knowledge in the minds of subject matter experts.


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Products
Software for Intelligent Decision Automation
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Software for Intelligent Decision Automation through Machine Learning
ACTICO Machine Learning
Decision automation with artificial intelligence

ACTICO Machine Learning is an integrated software platform for intelligent decision automation. It offers a well-aligned toolset for modeling, managing and automating operational decisions and apply machine learning technology.



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