CREATING DIGITAL TWINS
Our solution creates Digital Twins by observing and learning from decisions being made by human experts.
An Expert works through a series of steps to design, train and test their Digital Twins.
The process is highly intuitive, does not require any prior AI skills and takes less than an hour.
DIGITAL TWINS: THEN vs NOW
Digital Twins have traditionally been created within assets, products, machines and processes.
Supported functions included scenario planning (what if analysis), optimization and training.
Digital Twin technology has evolved to include the modelling of people as assets in the organization. Digital Twins that represent experience and skills are set to enhance processes that rely on decision intelligence.
Our Digital Twins operate in several niche industries including financial services, cybercrime, healthcare, law enforcement and social services.
WHAT CAN IT BE USED FOR?
Employee Fraud & Collusion detection
(SAP EMEA & MEE Hackathon winner)
Employee fraud costs organizations billions of dollars every year. Of all the tactics fraudsters employ collusion remains one of the most difficult to detect.
Digital Twin Technology enables organizations to deploy a digital team of fraud experts – a Digital Fraud Review Panel – within existing payment systems. This Digital Fraud Review Panel acts as an independent “second set of eyes” to monitor payment activity & block suspicious transactions in real-time.
Internal resources cannot interact with the external Digital Fraud Review Panel, therefore any opportunity to collude is removed.
Financial Crime monitoring systems create excessive volumes of alerts.
Regulation prescribes that certified financial crime analysts adjudicate these alerts.
Limited analyst capacity leads to a processing bottleneck, delays and inefficiencies which often result in compliance breaches, fines and penalties, organisational and reputational risk.
Financial Crime Digital Twins replicate the decisions of the human analysts.
These Digital Twins work within the financial services industry as a decision support technology to scale the processing capacity of financial crime analysts.
Cyber security detection technologies have implemented zero trust methodologies resulting in high volumes of alerts.
Despite assistance from SIEM & SOAR technologies security analysts are struggling to cope with ever increasing volumes of alerts.
TOM Digital Twins replicate complex resolution decisions which currently require the domain knowledge of the human analysts.
The SecOps Digital Twins work alongside existing technologies and SecOps analysts alleviating pressure on their human counterparts.
Digital Twins enable organizations to digitally scale the decisioning capacity of their SecOps teams to more efficiently manage the volumes of alerts or incidents.
AI Ethics and Governance
Responsible use of AI (in particular high risk AI) is set to be a regulatory requirement within the next few months.
In order to comply organizations must demonstrate that their AI has passed the conformity assessments and is monitored on an ongoing basis.
Moral and ethical standards are difficult to define using system rules.
TOM Digital Twins replicate the opinion of human experts enabling organizations to consistently and accurately screen and monitor the organizations AI.