Headlining in 2018, the price volatility of bitcoin, cloud computing, and challenger banks stole the show. Funding in the UK from the government in East London Tech City and tech partnerships in Brazil and South Africa, has shown that digitisation and innovation have been front of mind for both private and public sectors.
Looking at the year ahead, emergent technologies around big data analytics will help shape financial services. The fintech community around the world solve looks set to continue to deal with application programming interface (API) communications, as paytech grows, and advances in applications of artificial intelligence continue to gather steam.
Fintech UK: improving efficiency and protection against threats
Conquering translation and amalgamation across source inputs is challenging for many industries, and capital markets is no exception. London Clearing House (LCH) cleared over $1,483bn in swaps; over 1.2 million in overall client trades, a strong demonstration of the depth of the market and value.
- Market fragmentation – The company offers solutions to firms trading bonds, futures, swaps and repos, connecting to over 150 separate venues across 230 different API protocols
- Market speed – co-founders Tom McKee, Steve Toland, and Judd Gaddie have come up with bespoke technology to address the frequency of price updates – where some platforms publish more than 5,000 updates per second during volatility spikes
Expecting further developments in 2019, co-founder Tom McKee said: “To date, we have connected our API to 14 e-trading venues and expect to add 15 to 20 more over the next few months. There are probably 30 core trading venues, which are demanded by all clients and prospects, and once we connect the TransFICC API to these venues we are able to also use them with other clients. The capital markets fintech industry continues to evolve, as large banks become more willing to outsource parts of their business where there is no competitive advantage, and we expect that during 2019 there will be more interest in the cloud, as the technology becomes more mature and banks become more willing to consider its use for less volatile products."
Just over two years old, TransFICC has attracted big-time investors, confirming the strategy and time-saving technology. US-giant Citibank and venture capital firm Illuminate Financial have backed company’s direction.
Security is also a strong focus for London-based fintechs.
“I believe firms tend to focus a disproportionate amount of attention on inbound threats and neglect the biggest threat - human error. The real insider threat is more mundane - employees accidentally sending emails to the wrong recipients and/or deliberately sending unauthorised emails home to their personal email accounts,” said Tim Sadler, CEO of Tessian.
The company’s proprietary technology looks at an organisation's emails, learns from user relationships and helps prevent the most common causes of data loss due to human error - misaddressed emails, unauthorized emails and spear-phishing attacks. Natural Language Processing (NLP) is used to analyse exchanges between employees and email contacts both internal and external to the organization. Extracting communication trends, Tessian automatically detects threats and errors without any delays or end-user burden.
“Greater exploitation of human vulnerabilities will demand a change in how we perceive and protect them,” said Sadler in his prediction for 2019. As one-to-watch for next year, the demand for data protection, cyber-security and increasing regulation underscore even further the importance of Tessian’s protective capabilities.
While 2018 saw the rise of challenger banks and increasingly widespread use of ApplePay, the paytech scene has seen card holders become empowered by low fees, few foreign exchange expenses, and online accounts.
Soldo offers solutions to the ever-present problem of multiple cards. The Soldo card can be used to pay, while the app manages and delegates payments across multiple existing cards. Easily vanquishing the multitude of credit and debit cards in one’s wallet, Soldo can also be used to manage payments across multiple users; budgets and transfers can be set up, and cards can be enabled or disabled. Attractive to small businesses the Soldo card can be managed on the platform or app, enabling real time budgeting - most powerfully, allowing for detailed expense data capture.
Soldo can also integrate with existing accounting and finance functions. “It’s a natural collaboration”, said Darren Upson, vice president, small business Europe at Soldo, and former director of small business at Xero, the accounting system. “Xero can offer transparency into company finances - and we can match it with visibility into spend. This integration puts all the data needed for real-time accounting in one convenient place: letting accountants spend more time advising their clients - and less on frustrating admin tasks.”
In 2019, AI will develop in Asia
Fintech companies in Asia capitalise on the 1.55 billion mobile phones registered in China. Without using traditional banking networks, large payment apps like AliPay are designed to facilitate peer-to-peer payments.
Sesame Credit, or Zhima Credit analyses credit history to produce a peer-warranted credit score. A Zhima credit score allows users to build up a credit history, and eventually, allows a user to build a dossier of evidence to support entrance into the formal banking market.
Asia has also made use of AI. Facial recognition software, a powerful identification tool can be applied cross the compliance and KYC process, enhancing counterparty security.
SenseTime, a Hong Kong based AI technology firm, has determined metrics across faces so that its AI programme can ‘recognise’ people. The company’s proprietary technology has the ability to analyse both static and video components of facial recognition. The prospects of application are vast. Intelligent buildings, enhanced security checks, customer identification, smart gateways – all concepts which the technology can be applied to. Rong360, one of China’s unicorns, uses SenseTime for loan approvals. Being able to quickly identify applicants, Rong360 can support users’ needs for small business and personal loans. Focus Media, another SenseTIme client, also uses the technology in order to identify credit card users for its credit balance management platform.
Reviewing the trends in Asia, it seems that 2019 may look like the year where passwords and finger prints are done away with, replaced with AI and facial recognition to enhance secure finance transactions.
Unbanked Africa, the last frontier
Sub-Saharan Africa’s growth, projected to be approximately 3.6% in the upcoming year, has seen rapid development in fintech investment. CB Insights puts Q2 2018 investment at around $63m.
FinChatBot, can be deployed across websites belonging to financial institutions, engaging potential customers and improving customer retention. FinChatBot’s assistant Holly can be used to support customers across multiple channels, with a single cohesive voice.
Nigeria’s Kudi leverages similar technology but goes one step further. Rather than simply chat with customers, Kudi can make payments, transfer funds, and even effect mobile phone top-ups. Kudi also caters to informal language used across chat channels, and the app responds with action to instructions like ‘Yo pls send money to Dad,’ or ‘I need to pay for my TV subscription’.
Great expectations for 2019
“In my personal view, with the combination of the UK government providing tax benefits and private investment, fintechs are starting to develop and offer voice identification, data quality, advanced analytics and predictive analytics, which improve user experience and understanding. New applications are leading to huge AI markets opening up around data and the value it brings. The potential for AI to transform traditional financial services is huge – from sales, to customer identification, and automated risk and compliance processes,” said Sarah Rench, advanced analytics, robotics and AI senior manager at EY.
Pushing the boundaries between machine and human, further integration of machine intelligence in financial services, more intelligent ‘communication’ from machines, and advanced facial recognition are expected in the years to come.