Ludaciti

So far, the currently available technologies have not been able to provide insights to prevent white-collar crime. The mere accumulation of data (Big Data) and its analysis has only led to more control and ex post punishment, with overall disappointing results.

That is why Ludaciti concentrates on advanced analytics to develop a technology, which serves human mankind in solving one of the most urgent problems of our times: white-collar crime.

Our approach is to analyze how individual decision-making takes place in the business area. For this reason, Ludaciti has developed a technology to better understand and improve individual decision-making of people who have to deal with complex situations, high risks, growing ethical demands and changing conditions - such as different legal systems.

As of today prevention is still understood as top down communication of rules which have to be applied. Threat of punishment shall help to deterre transgression. Whistleblowing shall help to detect crime and misdeeds. But, a resounding success to prevent and manage compliance risk has not yet been achieved.

Nevertheless, without effectiveness evidence of their Compliance Management Systems (CMS) the industry invests year after year in cost-intensive e-learning and face-to-face programs that according to around half of the CCOs are doubtful or poor in results. This assumption is underlined by the fact that white-collar crime has not changed significantly since 2014.

PWC concludes in its study on white-collar crime 2018: "The qualitative enterprise surveys show that the implementation still has significant weaknesses. You can see that the pure training and its repetition is not really effective." The Department of Justice (USA) recognized 2018 that firms might be spending a lot and creating all the components of compliance programs but actually producing hollow facades.

Why is that?

Every crime or misconduct is preceded by a human decision. A system needs rules without question but its effectiveness will only unfold if the people who make decisions within this system also adhere to it. Since the existence of a set of rules does not guarantee application, e-learning and classroom training have their advantages, but are far from sufficient. Thus, businesses that rely solely on these prevalent education models face significant risk. Our empiric data can proof that mere rules teaching provides moderate to near zero effect in practice.

A good decision needs a rule, skills and a will. And as moral compasses are to a high degree a cultural thing and best practice in their respective environments, Ludaciti subscribes to the view that: „There is nothing more impractical than commanding free people to do things that strike them as absurd and that run counter to their most basic motivations.“

This is the main reason why the current classical education (e-Learning, face-to face) approach of right or wrong is not sufficient. „False beliefs, once they’ve become culturally entrenched, once the’ve become tribal badges of honor are very difficult to change and changing them is no longer simply a matter of norm teaching.“ Thus, any training without knowing and internalizing the individual background of the decision-maker is almost meaningless.

Proof and improve effectiveness of your compliance management system (CMS)

• Empower your leaders to make better decisions without losing sight of the company's mission
• Manage compliance from a risk and integrity perspective and thus provide state-of the-art prevention
• Use empirical granular data to proof adequate risk management for authorities
• Decrease fines, avoid monitor. We meet requirements of the U.S. Department of Justice.

Deployment process and supported infrastructure

Our solution needs no implementation on premise, no maintenance costs, no supervision by client. 

Data Security

We host our solution as an independent SaaS instance. We address data privacy and security needs.

Ethics

• Complete anonymity for employees
• We are committed to high ethical standards. Our approach is based on the ethic of responsibility
• Generated data will only be evaluated with regards to corporate/ institutional compliance risk
• Scientifically sound and proven methods are used to generate and validate data
• We do not manipulate. Results are not biased. No human influence on validation process. No nudging.
• Data generation and validation process complies with required assessment rules and data protection rules
• No clinical questioning, no intelligence test. No measurement of backward behavior