Organizations attempting to implement effective oversight at scale are faced with a number of extraordinarily complex technical challenges. At large commercial enterprises, the activities of tens to hundreds of thousands of employees must be monitored to eliminate waste and prevent rogue activity. Internal operations must be audited to ensure compliance with thousands of pages of constantly evolving regulations. Managers need a unified view of operations across lines of business in order to monitor systemic risk. These problems are only magnified for government institutions charged with regulating entire industries. Palantir Accountability is an open, extensible solution that can be deployed against these technical challenges in a fraction of the time and with none of the risk of bespoke systems. It provides a platform on top of which even the largest organizations can implement effective oversight and internal controls.
Integrate massive-scale, disparate, disconnected data into an intuitive analytic workspace
The Palantir Accountability data layer sits on top of existing systems rather than replacing them, and employs an object model that transforms data of heterogeneous types into the entities, events, and relationships of the analyst’s everyday experience. Analysts and investigators interact with the data from within a single, intuitive user interface equipped with a variety of analytical applications. Public and private data, network traffic, badge data, weblogs, emails, price indexes, transactions, and more can all be searched and analyzed without the need for a specialized query language. Users can ask the questions they need answered in a language they understand, so they can positively identify corporate entities and human networks involved in money laundering, fraudulent transactions, insider trading, rogue trading, data exfiltration, and other insider threats.
Collaborate across operational units within massive organizations
Palantir Accountability enables collaborative analysis across business units or even across enterprises to detect non-compliant or criminal behavior wherever it occurs. What first looks like an isolated case of on-line fraud may, upon further investigation, turn out to be a massive money laundering scheme. Palantir Accountability allows analysts from different operational areas to work together directly and publish their findings to the enterprise knowledgebase, to be leveraged by future analysts when similar patterns recur in the future.
Build comprehensive models of activity to detect suspicious anomalies
With Palantir Accountability, analysts and investigators can build comprehensive models to detect correlations between physical and logical access to sensitive spaces and information, surface relationships between individuals and corporate entities, identify behavioral trends over time, monitor trading activity across all markets and more in order to detect suspicious anomalies. By running algorithms against disparate data from across the enterprise, Palantir Accountability surfaces patterns of suspicious activity for more in-depth, human-driven analysis, allowing financial institutions and government regulators alike to capitalize on the strengths of machine analysis (finding signal in large-scale, noisy data, surfacing complex relationships quickly, etc.) while avoiding the risks of purely automated approaches (high rate of false positives, static in the face of adaptive threats).