Bank of England fintech accelerator feels the fourth for innovation
The Bank of England’s (BoE) fintech accelerator has unleashed four new initiatives in the fields of distributed ledger technology (DLT), data storage and analysis, machine learning, and cybersecurity.
The Bank of England’s (BoE) fintech accelerator has unleashed four new initiatives in the fields of distributed ledger technology (DLT), data storage and analysis, machine learning and cybersecurity.
As reported in July, BoE revealed the third stage – such as its work with machine learning Mindbridge AI, DLT darling Ripple, and regtech bouncer Enforcd. Now we’re onto the fourth round and the bank is in bumptious mood with progress and plans so far.
With silky smooth diplomacy, Andrew Hauser, BoE’s executive director for banking, payments and financial resilience, ensured that feathers remained unruffled – evoking the cunning charm of a character from a John le Carré novel: “Our broader interactions with [fintech] firms, even those not successful in their application, have been of great value, allowing us to reach a much wider external audience keen to interact, collaborate, teach and learn with us.”
Sweet. Whatever.
In terms of DLT, Hauser calls it “the poster child for fintech” and says its latest DLT PoC will be done with Chain. The PoC will examine the extent to which DLT based systems can be configured to enable privacy amongst participants, whilst keeping data on a shared ledger – “one of the holy grails of DLT design”.
In the area of data storage and analysis, its latest PoC will be done with Japanese IT software and services provider NTT Data and data management firm Reportix. The PoC will explore ways of storing, organising and combining the bank’s regulatory and analytical data in a more flexible or “multi-dimensional” way based on the XBRL standard, rather than the current “form-centric” (or tabular) format.
For artificial intelligence (AI), it will work with Mindbridge AI again to look at “larger and more diverse” data sets, including transaction data, and a “broader range” of classification and machine learning algorithms.
BoE will also have an AI PoC with Digital Reasoning. This will examine the extent to which analysis of the large quantities of weakly-structured textual data on regulated firms available from multiple public data sources can yield insights on intent and sentiment. The PoC will look at whether those insights are capable of complementing analysis of more formal data reporting.
For the cybersecurity initiative, Hauser cites its PoC with BitSight aimed at assessing the extent to which a firm’s cyber resilience can be evaluated using publicly available data. And it has a PoC with Anomali and ThreatConnect to explore ways of consolidating threat intelligence for “information collation, enrichment and sharing”.
Finally, in terms of the future and fintech challenges, Hauser picks two.
“First, customer acquisition is hard! Households and firms are loyal to their traditional suppliers: they will only switch if the offering is genuinely innovative, not just a good-looking piece of marketing.
“Second, widespread adoption also requires attention to those two traditional characteristics of successful financial systems: scaleability and resilience. It is striking how much our conversations with leading firms have increasingly turned to these issues, even over the short period we have been running our accelerator project.
“These topics are dear to central bankers’ hearts, and will play a central role in shaping the next stage in our engagement with fintech.”
