Firms we have worked with in the past
In the BitSight proof of concept, we tested BitSight’s tool that assesses a firm’s cyber resilience based on publicly available data.
BitSight proof of concept
Anomali and ThreatConnect
We asked these companies to create a searchable database where intelligence on cybersecurity threats can be optimised and stored.
Anomali and ThreatConnect proof of concept
Distributed ledger technology
Our project with PwC looked at possible applications of blockchain and distributed ledger technology.
PwC proof of concept
We carried out a proof of concept with Ripple to explore the synchronised movement of two different currencies across two different real-time gross settlement systems linked using Ripple Connect and the Interledger protocol. We wanted to demonstrate how this kind of synchronisation might lower settlement risk and improve the speed and efficiency of cross-border payments.
Ripple proof of concept
This proof of concept explored how distributed ledgers could be configured to enable privacy amongst participants whilst keeping data shared across a network.
Chain proof of concept
MindBridge Analytics Inc
MindBridge’s artificial intelligence (AI) auditor detects anomalies in financial transactions and reports using data science, machine learning and other AI techniques. In this proof of concept we asked the firm to prove the analytical value of the tool for detecting anomalies in anonymised credit union datasets.
MindBridge Analytics Inc proof of concept
BMLL’s machine-learning platform provides access to historic limit order book data – trading exchanges’ records of buyer and seller interest in particular trades – with the aim of making it easier to analyse and check anomalies in the data. We tested the alpha version for the BMLL proof of concept.
BMLL proof of concept
Enforcd’s enforcement database holds publicly available UK regulatory enforcement actions and news, along with commentary written by Enforcd’s own regulatory lawyers, and insights from City law firms and chambers. In this proof of concept we wanted to understand the benefits and the influence on decision-making of viewing publically available regulatory enforcement action from different perspectives.
Enforcd proof of concept
This proof of concept applied Experimentus’ ORB tool to analyse historic Bank of England projects to visualise how they had performed against a range of standard key performance indicators.
Experimentus proof of concept
For this proof of concept, we tested Privitar’s software on a manufactured dataset to examine the analytical value of the desensitised data. We did this to establish whether we could provide Bank researchers with wider access to data.
Privitar proof of concept
NTT DATA and Reportix
This proof of concept investigated an innovative processing solution for XBRL based datasets to support the evolution of the One Bank Data Architecture initiative of the Bank’s Strategic plan.
NTT DATA and Reportix proof of concept
This proof of concept involved using a machine learning solution to ingest and classify large amounts of weakly-structured data. The aim was to assess the effectiveness of the software in drawing out sentiment and qualitative insights from publicly available information to support of the Bank’s supervisory approach.
Digital Reasoning proof of concept