Judging the risk associated with an entity based on profiling may provide statistically viable results, but results in unwanted false-positive and false-negative results, which business impact may be unbearable.

True risk needs to take into account the ability to dynamically defined what is an entity, how it relates to other entities, and more importantly, how does these entities impact the risk associated with the original entity. For example, John Smith may be a perfectly legitimate business person, but being the son in low of a notorious Mafia boss, is likely to significantly increase his indirect risk. A bank may want to be informed of such relationship, so guaranties can be used to mitigate that risk.

Element of Risk supports:

  • Dynamically defining what are monitored entities (people, organizations, assets, structures, etc.)
  • Identifying and quantifying direct risk of any monitored entity (customer, supplier, individuals, payment instruments, etc.) using customer specific Ontologies
  • Detecting unreported relations between entities, quantifying their quality, and analyzing their indirect risk implications on monitored entities
  • Identifying clusters and centrality of entities in networks, and analyzing their aggregated risk impact
  • Analyzing risk associated with specific transactions and events, qualifying the aggregated risk of each entity, network, transaction, event, or process according to the organization policies, automating risk
  • Recommending policies for risk avoidance, mitigation or management, and promoting offerings to address them. and more.