What is Izengard?
Izengard is the first disruptive enterprise wide forensics platform to unify cyber security, financial crime and IT risk management. It is top-down, starting from organization and process design, designing controls and the utilizing the power of a scalable platform to deliver the processes, the models and controls in an intuitive user friendly design. It works on the same basis as you would transform an entire set of operations and follows a similar paradigm.
- The technology has been built by banking, technology and consulting industry experts with frameworks and a transformational approach to the three domains (financial crime, IT risk management and cyber-security)
- It has state of the art technology, in terms of hybrid-cloud/on-premise computing for processing intensive clouds, a data fabric for federated data and sits on scalable technology with ability to do real time detection in under 30ms.
- It is multi-tenanted and focuses on the organization structure of your business.
- It is verticalized for the industry (banking, payments, insurance, remittance, gambling) and has best in class business processes, controls, typologies and risk indicators for each of the three domains including the interlocks between those areas.
- It is forensically sound, having forensic data preservation techniques and investigation techniques built to quickly get to the root cause of the security hole/backdoors in controls.
- It has the most advanced machine learning (causal AI – due to its practicality for financial crime vs traditional AI methods) and rules mechanisms for detection, with a team of data scientists who specialize in financial crime, cyber security and IT risk management, not just generic data scientists who understand the math/programming only. Our models are contextually rich, with white box explainability and less likely to need constant revision as many of the current machine learning solutions around in the market.
- It is affordable, when you look at the cost of individual siloed solution, the indirect costs in maintaining those and when you look to lower your cost of operations.
What makes Izengard so different?
We respect you have a choice of vendors. To benefit overall, the sum is greater than the parts of the individual. That is the reason why Izengard is not a siloed point solution and integrates by benefiting from a holistic view.
Multi-dimensional Context
A single data point, without a deeper understanding of wider user/device behavior leads to an overall poor risk indicator. The platform combines multiple data points from all three domains (Cyber, Financial Crime and IT Risk Management) with customer and device characteristics from current and historical data to drive rich data points to help figure out contextual anomalies and reduce false positives given by point anomaly contextual solutions.
Entity Centric Profiling with Resolution
The platform takes entity resolution to a different level, with contextual history and by bringing the best practices found under each domain and combined with our experience. Our zero trust resolution, starts with not trusting the identity of anyone. Instead the platform combines digital footprint history with many more data points. The platform learns more about the entity (customer, device, vendor, app, channel, service) all the time.
Onboard the right customers
The platform understands that many government sources (so called UBOs and individual citizen/address registers) are used everyday to register shell entities (shelf companies) or via fake alias' entities (synthetic identities), which don’t actually exist and have sometimes indicate ridiculous capital. Izengard does much more than examining entities registered at multiple addresses or same/similar directors are part of multiple companies.
Fast or Slow Moving Criminal Activity
The platform has horizon scanning capability and is fed from regulatory intelligence, law enforcement and other sources, as well as via experiential learning. Izengard also operates a fully anonymized consortium database of which members can benefit from patterns seen elsewhere. The team behind the platform and our technology partners work hard to keep intelligence in the form of typologies up to date for you and informs you of any potential changes to detection models.
Reduce Operational Risk & Cost of Compliance
Izengard’s contextual approach, intelligent machine learning, resolution mechanisms and intelligent investigations via a forensic approach allows stronger robotic process automation. With this in place, Izengard reduces the cost of level 1 alerts review and when escalated it is more contextually aware, therefore providing supervisors with better context to make their decisions to report with confidence to law enforcement, regulators and their legal team.
Tamper Proof
Internal perpetrators of crime will not get away with subverting the course of an investigation. Izengard having adopted the zero trust paradigm has in-built legal hold, chain of custody and chain of evidence. Data is stored in a tamper proof manner, any changes upstream will be detected and everyone is profiled including Izengard system administrators. Whistleblowing systems are built in for manual as well as automated escalations.
Reduce dependency on team risks of moving to a competitor
Many processes and activities that are typically performed in operations by humans are already automated in Izengard. As an organization you can turn on and off as many automated workers as you need and specify the work allocation amongst them. No need to panic and hire temporary contract labor.
Risk Appetites aligned with Non-Financial Risk
Izengard has been designed to not look at risk assessments stand alone. Izengard aggregates risk assessments, examines duplicate items, examines correlations between risk types/assessments and applies different customizable risk ratings. Izengard then uses advanced calculators for your risk appetite in a similar non-linear way. Your CISOs, CROs, CCOs, Head of Fraud together with internal audit will be happy with the advanced risk management approach. .