Financial regulators have access to increasingly large and complex datasets which need to be operationalised into ongoing monitoring and risk analysis.

Supervisory Technology (SupTech) analytics encompass a set of technologies that enable financial authorities to investigate the increased volume of data now available, to refine policy, identify regulatory concerns and mitigate systemic risk.

Who are our typical clients

• Central banks & prudential regulators
  • Financial stability
  • FMI oversight
  • Banking supervision
  • Research
• Conduct regulators
  • AML / financial crime
  • Market surveillance

Challenges

• Manual processes of data collection, cleansing, entity resolution, visualisation and analytics are slow, complicated and expensive.
• Large amounts of new supervisory data is currently underused. This includes data for Derivatives TRs, SFTRs, Payments TRs, CCAR/SST and MIFID.
• Limited visibility into indirect risk exposures across increasingly complex networks.
• Limited ability to interactively model and  “stress test” systemic and concentration risks.

Outcomes

• Automation of analytics and monitoring allow oversight and supervisory personnel to free time up for more important work.
• Views of relevant financial networks can be automated and created in real-time from underlying transactions enabling early identification and mitigation of emerging risks.
• Systemic risk exposures and risk concentrations are reduced and managed by understanding the holistic network rather than just a component.
• Advanced analytics, including stress testing, improve targeting of policy interventions.