Fraud is a high profile and often under reported crime. The unprecedented circumstances brought about by Covid-19 have caused disruption to daily and working life, which has been taken advantage of by fraudsters.
Technology presents the opportunity to improve the detection and prevention of these types of financial crimes to protect consumers.
How can financial services firms more efficiently and effectively use advanced data analytics to analyse and detect payments or transactions which are fraudulent, or between mules? What alternative datasets could be made available to improve the models?
How can the network of relevant bodies, both public and private, readily share data in real-time relating to perpetrators of fraud? This data could include suspected account details, fraudulent websites, known scam typologies, scam emails and calls, and social media approaches. To what extent could improved data sharing be enabled by Privacy Enhancing Technologies?
How can technology be better deployed to detect patterns or other indicators of consumer behaviour which may indicate a fraud or scam is taking place and generate friction in the customer journey? Could feedback loops be built in so customers can validate or verify a warning about their transaction?
People from all walks of life are experiencing fluctuating and challenging financial circumstances, leading to many experiencing financial vulnerability. Improved use of technology and analytics has the potential to provide support to these consumers, with greater accuracy, efficiency, or scale than ever before, at a time when it is needed most.
How can advanced analytics be better deployed to identify and manage the risk that a customer may be in a vulnerable state, or about to transition to one? How can those customers be better supported through human intervention, or other methods?
How can technology be used to provide or augment bespoke debt management advice to consumers, who may be experiencing, or about to experience debt challenges in order to improve; the quality of advice; the scalability of advice channels to meet unprecedented demand; or overcome the challenge of unavailability of face-to-face debt advice support?
How can technology and/or advanced analytics be used to better manage risk and improve lending and credit services in a world of uncertain and unprecedented income fluctuations?
Ensuring that there is effective support for SMEs is an important driver for economic recovery. Understanding the impact that Covid-19 has and will continue to have on SMEs and their financial health is crucial. We want to support financial services innovation that could improve how SMEs access finance.
How can existing processes be made digital, to effectively support small and medium enterprises which may be impacted by social distancing or other remote working situations?
How can advanced analytics and data science be used to improve modelling, risk assessment or credit scoring of small and medium enterprises in an unprecedented environment?
How can technology be used to improve the speed and efficiency of decision making when considering access to finance for a small or medium enterprise?
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