FinCEN’s new beneficial owner rules take effect May 11, impacting banks and the program managers and similar companies that help banks comply with the Bank Secrecy Act, including FinTech companies that provide AML on-boarding and monitoring services. Under the new rules, banks and other covered financial institutions will be required to identify and verify the identity of the beneficial owners of their legal entity customers. These rules will add to your regulatory burdens, particularly over the next several weeks.
By Cameron Abbott and Sarah Goegan
Technology company IOT Group announced this week that it has signed an Australian first energy and blockchain deal. In the agreement with Hunter Energy, IOT Blockchain will build a blockchain centre at the Redbank coal-fired power station in the Hunter Valley, two hours north of Sydney.
The UK All Party Parliamentary Group (APPG) on FinTech and APPG on Alternative Lending will be hosting an invite-only roundtable on Open Banking, taking place on 31 January from 9:00-10.30am at the Houses of Parliament.
Open Banking went live in the UK on 13 January. From this date, the high street banks were required to make their customers’ bank transaction data available to third party businesses when instructed to do so by the customer. This is the first major milestone in a multi-year programme to open all payment products to the market for financial services. Over time, it is expected to revolutionise the way consumers and small businesses use and access financial services.
Open Banking was the main remedy mandated by the UK Competition and Markets Authority (CMA) following its investigation into the supply of personal current accounts and banking services in 2016. The CMA concluded that UK banks do not compete hard enough for customers’ business; and that technology should be employed to enable customers to compare and access better deals from new providers.
The Roundtable will be an opportunity to hear the latest from the Trustee of Open Banking, Imran Gulamhuseinwala, two weeks after the new services went live; and to raise any concerns about the potential for consumer detriment. You can register your interest here.
As one year has drawn to a close it is time to look forward to 2018 and our tips for the most important 5 regulatory changes for the FinTech industry in Australia.
- Increased access to bank data.
The Government has announced its intention to introduce an open banking regime in Australia under which customers will have the ability to give third parties such as FinTechs access to the customer’s banking data. Treasury is currently conducting a review into open banking models, with the report which was due at the end 2017 yet to be released.
Also planned to come in to effect by 1 July 2018 is mandatory comprehensive credit reporting which will give lenders access to deeper and richer sets of data on consumers to base their credit decisions on. Comprehensive credit reporting is currently voluntary.
Rob Gruppetta, Head of the Financial Crime Department at the UK Financial Conduct Authority (FCA), recently gave a speech at the FinTech Innovation in Anti-Money Laundering (AML) and Digital ID regional event, London about “Using artificial intelligence to keep criminal funds out of the financial system”. He considered whether machine learning and artificial intelligence (AI) techniques could help. Better transaction monitoring is not the only way AI can aid the fight against money laundering. The Financial Stability Board (FSB) published a report on 1 November about the impact of AI that identified other ways it can help. Examples include AI-driven anti-impersonation checks that evaluate whether photos in different identity documents match, and using machine learning to identify customers that may pose a higher risk and so warrant, say, a deeper probe into the sources of their wealth.
The Australian Government has announced its intention to mandate that ADIs provide open access to customer and small business data with a commencement date still to be determined. Treasury has been tasked with undertaking a review of the proposals put forward by the Productivity Commission, and is due to report back to the Government by the end of 2017 as to its recommendations on implementation of the proposals and recommended timeframe.
While everyone is excited about the benefits that will flow from open banking, there have been concerns raised about the security and privacy risks raised by an open banking regime. In relation to privacy, the Productivity Commission has suggested that the solution is to amend the existing Privacy Act to include a new class of protected information known as “consumer data”. However there are significant gaps in the existing Privacy Act that would pose real problems in connection with the protection of customer data. For instance, the Australian Privacy Principles do not apply to small businesses with turnover of less than $3.0m and this may exempt many FinTech players from any privacy obligations.
By Cameron Abbott and Olivia Coburn
Oracle has finally realised that it wants to hang out with the cool FinTech kids on the block, having recently announced the release of its Oracle Banking Payments application programming interface (API) service.
Oracle’s move recognises the value of offering better ways for its banking clients to collaborate with FinTechs and other third parties.
The Australian Treasury has announced an independent review into open banking in Australia. Open banking will require banks to share product and customer data with customers and third parties with the consent of the customer. The Government previously announced that the open banking regime would be introduced in 2018 to help customers seek more suitable products and increase competition.
By Cameron Abbott and Ling Zhu
No great surprises arising from the EY FinTech Adoption Index 2017 which has revealed impressive growth in consumer uptake of FinTech products and services, with 33% of 22,000 digitally active consumers using FinTech firms – doubling from 16% in 2015. With less brand loyalty and reduced trust in traditional organisations, consumers are increasingly turning to FinTech firms as better alternatives.
Money transfer and payment services are the most popular FinTech category, with 50% of consumers using these services. This has been driven by the increasing popularity of mobile phone payments and online digital-only banks. Insurance is the second most popular service, with insurance premium comparative services simplifying the process of acquiring insurance.
FinTech has particularly excelled in emerging markets, with an adoption by digitally active consumers across China, India, South Africa, Brazil and Mexico averaging 46%. The growing middle class have embraced FinTech to meet the growing demand for financial services, encouraged by cooperative regulators and policymakers.
EY anticipates that FinTech adoption will increase to 52% globally as consumers become more aware of the products and services on offer.
Read the full report here.
On 21 June at the OpRisk North America 2017 conference in New York, Scott W. Bauguess, Acting Director and Acting Chief Economist of the U.S. Securities and Exchange Commission’s (“SEC”) Division of Economic and Risk Analysis (“DERA”) gave a keynote speech on the use of artificial intelligence by regulators. A transcript of the speech can be found here. Bauguess provided some interesting background on the utility and use of big data and machine learning at the SEC to identify potential misconduct by market participants and investment managers, and the emerging use of artificial intelligence.
Bauguess’ speech discussed the SEC’s use of AI in its regulatory framework, initially discussing machine learning. The SEC currently applies topic modeling methods, such as Latent Dilchlet Allocation (“LDA”). LDA reviews text-based documents (e.g., registration disclosures) and reports on where, and to what extent, particular words appear in each document. This occurs either by: analyzing the probability of words across documents, and within documents, to define the topics they represent (“unsupervised learning”); or incorporating human judgement and direction into the programming of the machine’s algorithms (“supervised learning”).