The Digital Sandbox Pilot has been launched by the FCA and the City of London Corporation. It provides innovators with access to a suite of tools to collaborate and develop financial services Proofs of Concept.
Find out about the 28 teams that will participate in the Digital Sandbox Pilot to test and develop innovative products and services in response to challenges presented by the Covid-19 pandemic.
28 teams took part in the Digital Sandbox Pilot to test and develop innovative products and services in response to challenges presented by the Covid-19 pandemic. Between 8-10th February, the teams presented their progress throughout the pilot.
Click the links below to view the presentations:
The applications were assessed against four primary criteria:
- Genuine innovation – is the solution significantly different from what already exists in the market?
- In scope – Will the solution benefit UK consumers of financial services firms by solving one of the use cases?
- Need for a Digital Sandbox – Does the solution require the features of the digital sandbox features to be developed or improved?
- Testing – Does the solution have defined development objectives with a pathway to production?
The pilot ran from November 2020 through to February 2021. An evaluation process is currently being undertaken by an independent consultant. The pilot will be assessed against the 5 success criteria:
- Innovation – role played in encouraging innovation in financial services to the Covid-related challenges detailed in the use cases
- Speed – role played in enabling quicker testing and development of proof of concepts
- Collaboration – role played in fostering collaboration, facilitating diversity of thinking and creating an ecosystem of key organisations
- Pilot features – the effectiveness of the key features of the pilot (see below) in stimulating and accelerating innovation
- Sustainable future – role played in informing and assisting the design and future operating model of a permanent digital sandbox
Firms or individuals who are not testing or developing a solution in the pilot but who want to observe, offer their expertise or potentially be involved with a team, can register an account by clicking ‘Register now’.
A solution which uses an algorithm to identify suspicious behaviours in transactional data.
An AML solution that allows financial institutions to securely share knowledge about clients or transactions without disclosing any underlying data or information.
A solution that creates digital synthetic twins of real financial data which can then be used to detect fraudulent patterns and complex problems that are being experienced during Covid-19.
A solution to protect customers’ digital identities by tackling the rising issue of online banking fraud, without compromising on customer experience.
Financial Network Analytics
A solution that uses neural networks to establish the usual patterns of behaviour between organisations and individuals to highlight anomalies in order to detect fraudulent payments.
A solution that uses transactional data in close to real time to determine a risk score to aid in the identification of account push payments fraud.
A solution that uses a Privacy Enhancing Technology (PET) known as Secure Multi-Party Computation (MPC) to run risk scores on a transaction network of data from multiple banks.
A solution that provides a real-time risk assessment across a network to detect consumer behaviour indicative of fraud and scams.
A solution that uses blockchain to allow for a secure and GDPR-compliant sharing of verified KYC files across multiple institutions in real-time to create a single profile per customer.
An open source solution to detect fraudulent and money laundering activity within a financial ecosystem – in real time for selected typologies.
IT2 Fraud Signals - Trust Stamp, Cifas, Lloyds & OneBanks
A solution that uses biometric data to create an identity token that can be used to match, de-duplicate and verify across institutions while protecting the users personal identity information.
A solution that will combine machine learning with the development of rules by experts to identify types of fraud.
PrinSIX is focusing on detecting vulnerability within credit applications, testing and deploying dynamic onboarding journeys that identify applicant vulnerability flags and trigger highly personalised digital assessments to improve customer outcomes.
A digital assistant focused on financial wellbeing, powered by Open Banking, that automates financial decision for consumers.
A solution to create a two-app ecosystem to allow users to share their financial data with debt advisors and for debt advisors to directly send their solutions to the consumer via an app.
Automated Regulatory Monitoring
An AI platform aimed at SME’s that identifies the drivers and characteristics of vulnerability and provides a series of preventative measures to avoid negative outcomes for consumers.
A solution to create a ‘Freelancer Risk Score’ that fairly represents independent workers who might miss out on financial inclusion because they are not well served in typical markets.
A solution to assist vulnerable young people who have borrowed money from friends and family in managing and repaying these loans.
A solution to allow a range of lenders to assess the credit risk of a borrower without requiring direct access to private and sensitive financial data by using privacy-preserving technologies.
A solution that uses transactional data to predict the probability of default based on an individual’s historical and predicted cash flow.
A solution using financial transaction data to identify indicators of impaired financial decision-making and to help firms more efficiently and quickly allocate resources to support vulnerable consumers.
A solution that uses a ‘cognitive risk engine’ to assess the level of comprehension of information and apply a ‘cognitive risk score’ to a consumer.
A solution that uses natural language processing AI to interpret and analyse financial applications and claims handling processes in order to automatically interpret new applications and claims.
OBR creates analytical assessments, metrics, forecasts, network and threat models for SMEs and lenders to build successful businesses.
A solution to signal risk in a business’s financial condition to reduce uncertainty and create greater confidence in a lending counterparty.
A solution to enable finance funding providers to predict, analyse and risk assess the ability of a small business to repay credit within certain time periods.
A solution that uses Open Banking to create a cashflow forecast in order to help assess the eligibility of SME’s for small working capital loans.
A solution using tokenised assets on a blockchain to enable simple, cost-effective and transparent ways to securitise SME loans and invoices.
