Like brakes to a bicycle, fintech must exist within the realms of regulation if it is to ditch its ‘wild west’ persona. Indeed, the adoption of various elements of the industry, like cryptocurrency, has ultimately suffered due to the lack of regulation that surrounds and supports them. Throughout the entire month of May, The Fintech Times will be dedicating its focus to highlighting the most current developments in this ever-perplexing and constantly-changing foundation of regtech.
Open banking headlines the second chapter to our regtech focus of May. Synonymous with industry disruption, open banking quickly became a defining element of the global pandemic. Here, we’ve invited five industry experts to share and discuss how some of the latest technologies, notably natural language processing (NLP) and artificial intelligence (AI), are being incorporated into open banking regtech.
For Tomek Młodzki, CEO of PhotoAiD, the likes of NLP and open banking go hand-in-hand: “Financial regulations are constantly changing (and we experience it hardly in Poland.) It’s especially true for open banking – the new trend that arose in the middle of digital disruption. Because we value agility and want our customers to have more visibility and flexibility in their data, we would like to implement open banking. Since we had perceived its changing regulations as a problem, I can see that more and more automation solutions are available.
“My personal favourite is NLP because it addresses my primary struggle – regulations. NLP solves this challenge because it scans, structures, and analyses vast amounts of data more efficiently than any human being. Therefore, if we implement open banking, we will absolutely include the NLP solution.”
Robert Cruz, vice president of information governance solutions at Smarsh, added to these initial thoughts with: “They are fundamental. Many of the activities that create regulatory frameworks to provide guard rails for cryptocurrency address the underlying use of blockchain and distributed ledger technologies, so that aspect appears to be fundamental.
“The use of AI and NLP seems to be adopted in many elements across the open banking spectrum, including adding intelligence and precision to client-facing service delivery, to back-end infrastructure that is incorporating NLP into risk management approaches to spot potential issues that may arise across multiple heterogeneous data sources.”
Dr. Naushad UzZaman, CTO and co-founder of Blackbird.AI, delves further into the benefits that new technologies hold for open banking regtech: “Open banking is enabling financial inclusion, quickening the pace and speed of transfers as well as removing cross-border barriers. The space is underscored by emerging technologies like AI, blockchain and NLP and each of these individually and combined are pushing this sector forward.
“With traditional banks giving the green light and go ahead on the integration of online services, AI is being used to assess risks, detect and prevent payments fraud, as well as improve anti-money laundering (AML) and know-your-customer (KYC) regulatory checks.
“Blockchain is an added layer on top of this. While AI has greatly elevated the middle of the banking funnel, blockchain technology is serving as the underlying technology to fuel speedier and more secure transactions across a global network, whilst reducing costs and maintaining anonymity.
“Blockchain technology is significantly changing the way assets are transferred, stored and data is recorded. Most importantly, it plays a key in providing financial inclusion to the currently unbanked global population.
“With banks and financial institutions offering an array of online services which are being used across the financial industry – from retail banking to hedge fund investing – NLP techniques have become a core part of delivering an efficient back-end and customer-facing experience.
“NLP is used for sentiment analysis, question-answering activities (chatbots), document classification, topic clustering and more. These activities help to organise unstructured financial data and actively serve a larger and more widespread customer base in real-time.”
Shay Sabhikhi, executive at CognitiveScale, adds further to this by outlining exactly why a company would want to incorporate the use of such technology: “As AI has matured, it is now being leveraged across all facets of business – from customer service to marketing and data analysis. It is being counted on to deliver customer-facing information that is typically needed in near real-time.
“In the financial space, AI applications do not have human bias. These systems can present findings based on neutral and transparent criteria that is set up in the programme. Being able to see where the data is coming from and matching it to the requirements of the institution allows lenders today to make speedy decisions all while helping customers understand how a decision was made. AI is being used for:
“Reduced errors – AI removes the threat of human error. From manual input errors to mistaken calculations, AI allows an institution to be confident in the data they are presenting to its customers.
“Time saved – Market research takes time and when conducted by humans, often misses key data points. Lending teams can now rely on the technology to do mundane tasks while they are able to better engage with customers and focus on providing them with better expert analysis on the opportunities in front of them.
“Better insights – With so much competition in the market, it is near impossible to keep track of who has what rates, who is lending to whom and where new markets are being penetrated. AI-powered data gathering provides lenders with the ability to have the latest information in front of them which they can then turn into actionable insights.
“Improved customer experience – More insights, a personalised approach and expert analysis make customers feel more engaged with an institution. By allowing teams to spend more time with the people, and less on the data collection, customers will have a more positive experience and personalised experience.”
Joseph Lau, director of Mirato, believes now that it would be difficult to imagine open banking regtech without the implementation of the most contemporary technologies: “Only a few years ago, it seemed inconceivable that banking or regulatory technology would use advanced technology such as AI, NLP or blockchain technology as part of its strategy.
“Open banking today makes use of AI in a variety of ways, including AI chatbots with NLP that transform customer requests into information; APIs that connect and correlate data sources, financial data, and credit scores for rapid KYC; and overlay transactional data with financial data for target lending, credit decision, credit monitoring, or instalment loans. Open banking combined with blockchain technology, on the other hand, enables banks to decentralise data while maintaining security, privacy, openness, and integrity.
“In terms of regulatory technology, service providers are blending AI and NLP to process and interpret contextual demands from a variety of lengthy and complicated legal and regulatory documents, as well as to continuously monitor for regulatory changes. Instead of resource-intensive and time-consuming mapping operations, these platforms deliver insights for control mapping and requirements for organisations to focus on.
“In both cases, these technologies aid in the reduction of manual labour, the provision of targeted insights for human decision-making, the elimination of potential human errors, the growth of productivity through continuous processing, and the eventual streamlining of many complicated processes. With these advantages, many people understand that these technologies are crucial tools for staying ahead of the competition.”
