Technology is undoubtedly changing the way many industries operate, with impaired functions being eliminated or automated for more efficiency, and new delivery channels emerging that allow companies to interact with each other and their customers in ways not imagined even a decade ago. In general, FinTech redefining the banking system, not only from the customer experience side but from many other aspects such as regulations, communications, process automation, or improved operations. This is why we would like to overview key technologies (RegTech, AI, Machine Learning, IoT, Blockchain, Chatbots), changing the landscape of FinTech. In this article presented benefits and innovation of each technology.

 

FinTech probably the most heavily regulated industry, and it’s no surprise that firms are leaning on technology as a prime vehicle to help deal with the myriad of regulatory compliance functions necessary to run the business and stay in regulators’ good graces efficiently and cost-effectively. That’s why regulatory technology (or “RegTech” as it has become known) was one of the hottest topics for compliance and risk officers over the past year. RegTech will continue to evolve as financial firms grapple with staying compliant with new and existing regulations. With this trend gaining momentum, it’s of the utmost importance to understand how RegTech will change your business now and in the future. Regulatory technology is benefiting from recent groundbreaking FinTech software innovations, creating automated solutions to manage regulation monitoring, compliance, and reporting. Keeping track of new restrictions in a single database is a comfortable way of adopting a financial institution to legal requirements.

 

 

The cost of compliance continues to rise for financial firms. Some estimates pin the cost of governance, risk, and respect at 15-20 percent of the total cost of running the business at financial firms. That’s nearly one-fifth of an entire firm’s budget to stay in business and avoid fines from regulators. That’s where RegTech comes in, providing firms with technology to reduce costs associated with compliance and the ability to run compliance operations more efficiently.

 

RegTech permits the removal of one easily mitigated risk – the human element. Technology can reduce exposure to the dangers social interactions produce, allowing organizations to automate compliance without relying on individuals. Human expertise is free to be better utilized in interpreting data rather than collecting it. RegTech solutions offer the promise of making compliance less complicated and freeing up more capital to be spent on other more productive uses.

 

RegTech can also help reduce the amount of data they need to hold overall. All the information required for regulatory compliance often overlaps; a piece of information on a trade or customer may potentially be used to satisfy various regulations. Condensing this information and creating ease of accessibility will help bring significant efficiency gains and will be much needed, given the ballooning amount of laws globally.

 

Initiated cooperation between financial institutions and regulatory organizations to facilitate RegTech development. Government and commercial organizations share their expertise in joint projects, eliminating the skills gap. For instance, the Monetary Authority of Singapore (MAS) and the Financial Conduct Authority (FAC) provide banks with assistance in creating automated regulatory solutions. In 2020, similar practices are likely to develop all over the world. At the moment, there are 150+ RegTech companies. Compared to 300 million pages of existing regulations, this feels like a small number. Non-compliance with mandatory governmental regulations leads to fines and crisis. Financial institutions (FI) management wants to do everything in their power to avoid such problems.

 

The need for a RegTech solution on the market is evident. This niche will soon be filled, and we are likely to see prominent startups by the first half of 2020. RegTech will be indispensable for firms going forward. Not only will it help cut down the ever-increasing costs of compliance, but it will also provide an edge over competitors who have yet to invest in technology to maximize efforts in this critical area.

Last but not least, RegTech by its problematic finds emerging technologies in favor:

  • Intelligent character recognition. Machine learning enhanced character recognition
  • Robotic process automation. Process automation through the user interface
  • Data analytics and visualization. Patterns and visual representation from complex data sets
  • Predictive analytics and machine learning. Patterns and visual representation from complex data sets
  • Low code application platforms. Solutions created through graphical user interfaces and configuration instead of programming
  • Natural processing language. Ability to understand, interpret human languages

Besides, you can find more information about FinTech regulations in one of our articles as we discussed some more aspects of this topic.

 

Businesses are increasingly interested in how big data, artificial intelligence, and machine learning can be used to increase revenuelower costs, and improve their business processes. Machine learning and artificial intelligence are set to transform the banking industry, using vast amounts of data to build models that will enhance decision making, tailor services, and improve risk management.

 

Financial institutions are evaluating and adopting AI for protection against threats, fraud analysis, and investigation intelligence. With the rising popularity of AI for other purposes, such as enhancing customer support and algorithmic trading, the field of financial technology is set to get revolutionized in the coming years. The future of AI in this industry has, even more, to offer, from robotic clerks in banks to super-safe verbal transactions. In such a scenario of fast growth, AI consulting companies will come at the doors of financial institutions every day with new products and offers.

 

The value of machine learning in finance is becoming more apparent by the day. As banks and other financial institutions strive to beef up security, streamline processes, and improve business analysis, machine learning is becoming the technology of choice. Unlike so many exciting technologies and overrated buzzwords, machine learning is not going away — probably ever. The ability of computer programs to learn on their own and improve over time creates new opportunities for industries across the board. While it is true that the naturally conservative financial sector was not at the front of the line for machine learning adoption, machine learning in FinTech is now a common phrase. It offers a new level of service for financial forecasting, customer service, and data security. Here is the list of 15 ways machine learning technology is transforming the financial sector. By all accounts, this list will grow exponentially over the next few years.

  • Fraud prevention
  • Risk management
  • Investment predictions
  • Customer service
  • Digital assistants
  • Marketing
  • Network security
  • Loan underwriting
  • Algorithmic trading
  • Process automation
  • Document interpretation
  • Content creation
  • Trade settlements
  • Money-laundering prevention
  • Custom machine learning solutions

Machine learning is playing an essential role in the FinTech industry and is going to show even more potential in the future. Taking into account all the use cases given above, it seems clear that machine learning algorithms are beneficial for financial institutions.

 

EY defines the Internet of Things (IoT) as a technology that enables physical objects to be connected to the digital world. The EY paper, The actual value of the internet of things for the financial sector, points out that IoT devices do not provide information but instead provide the results of objective observations. In simple terms, IoT delivers data. The massive deployment of sensors will result in unprecedented capabilities for gathering accurate data about the world around us. It can be argued that the application of other technologies like machine learning, deep learning, or artificial intelligence to a vast repository of data courtesy of IoT devices may be used to draw insight leading to data-driven decision-making.

The Internet of Things has been increasingly growing, influencing many industries, including FinTech. Its potential is limitless and has the opportunity to change the way we live and the way we work. The statistics are there: the IoT will contribute to nearly $2 trillion in global economic benefit. One of the main impacts of this huge trend will be on FinTech. Whether it is to make a customer’s ATM experience easier through the usage of smart devices, facilitate risk management in auto insurance, or help manage households and their home insurance, IoT has a definite impact on FinTech’s development. It makes the process of data collection, management, and sharing much more accessible for FinTech companies. On the other side, stand banks; IoT can help with secure payment management and the exchange of information to make the banking industry more efficient than ever. International trade finance decisions and customer authentication can also be influenced by the Internet of Things to make transactions more legitimate. While the Internet of Things has become a widely-known trend, it has a high possibility to grow in the future. IoT platforms and a change in the design of operating systems and device architecture are some of the predicted IoT trends that will take the industry to the next level. One of the most significant possibilities, however, remains security. With the growth of FinTech, comes an increase in security risks and challenges for the industry. The Internet of Things can be utilized to make systems interconnected and protect against information attacks, tampering, and fraud. Another huge opportunity is the generating data – IoT will help manage data streams with a vast number of data entries. Distributed stream computing platforms have emerged as the future of IoT by maintaining with real-time analytics and pattern identification.

 

Initially, the brainchild of Satoshi Nakamoto, who initiated this technology in Bitcoin, and is indeed an incredible invention. Blockchain is a digital ledger of economic transactions that cannot be tampered with or changed. It is programmed to record not just financial, but every other activity to which a value can be attached. This technology allows digital information to be distributed across various nodes but cannot be copied. Any unwarranted change or alteration will change the hash links, and a mismatch can easily be detected. This is due to the intricate and complex cryptography devised behind it. Kate Mitselmakher, CEO, Founder, and General Partner of Bloccelerate predicts the future of blockchain technology and which trend shapes the world by 2030.

 

Most governments around the world will create or adopt some form of virtual currency. The government currency of the future is inevitably crypto. Compared to the traditional fiat alternative, cryptocurrency is more efficient, provides reduced settlement times, and offers increased traceability. Cryptocurrency can also be backed by real assets, similar to fiat currency, and its price can be artificially manipulated by numerous controls (e.g., monetary policy for “printing” more tokens).

 

 

There will be more trillion-dollar tokens than there will be trillion-dollar companies. There is a race among the four most valued companies in the world (based on stock market valuation) as to which one will be the first to reach one trillion dollars in value. Apple, Amazon, Alphabet (Google), and Microsoft are in a race to the “4-comma club.”

These companies are all representative of the new economy — one that should perhaps be called the no-longer-so-new economy. This new-ish economy is one based on the decades-long transition to digital business and online connections. It is the Internet economy or what blockchain advocates call “Web 2.0” (anticipating the next era, the blockchain era, as “Web 3.0”).

What this means is that, in the future blockchain era, trillion-dollar firms will be replaced by trillion-dollar tokens — tokens that support a decentralized ecosystem of entities that together fulfill the role of the mega-corporation. We are in the dawn of that era, and there will be more trillion-dollar tokens in 10 years than there will be trillion-dollar firms.

 

 

A cross-border, blockchain-based, self-sovereign identity standard will emerge for individuals, as well as physical and virtual assets. If e-mail proved to be the “killer app” for the Internet, identity solutions would prove to be the “killer app” for blockchain. Identity systems, as we know them today, are highly dysfunctional, operating in silos, and insecure. Blockchain-based identity systems will solve these problems. These systems will provide a single source of verification for individuals’ identities and assets.

 

 

Most of the world trade will be conducted leveraging blockchain technology. One of the most promising areas where blockchain can provide significant business value is the global supply chain. In its current state, world trade is conducted via a chaotic, fragmented set of business relationships among parties that are untrusted. This results in inefficiencies, errors, and fraud. This is a collection of real-world business problems that are currently unsolved and cannot be fully solved without using blockchain technology.

 

 

Significant improvements in the world’s standard of living will be attributable to the development of blockchain technology. Poverty and income discrepancy are arguably the hardest problems for humanity to tackle. More than 10% of the world population, more than 750 million people, live on less than $2 a day. More than 2 billion people are considered to be unbanked and have no access to financial services. Though the overall living standards increase and the world’s GDP is on the rise, the rich get more productive, and the poor get poorer. Blockchain technology has the potential to shrink the poverty gap. How? It can be done by increasing financial inclusiveness, reducing corruption, and enabling decentralized access to value-creating assets. Here are three examples. The potential applications of blockchain technology are growing exponentially because almost anything involving transactions or digital assets can be put on a blockchain. Our digital lives will likely develop to rely on blockchain technology without many of us, even being fully aware of it. We are experiencing the evolution of how we do business and interact with each other.

 

Robotic process automation (RPA) is an essential enabler in the automation and business transformation journey. On a 24/7 basis, RPA can perform repetitive manual tasks across any system, from a 40-year old legacy to new web-based technology, to make business processes cheaper, faster, and more accurate. Automation does not change what institutions do, but it can help them to accomplish goals in efficient and sustainable ways. RPA speeds up processes, reduces costs, and lets firms re-deploy knowledge workers to higher-value tasks. The result? A leaner, nimbler, more intelligent organization can adapt to industry, regulatory, and customer demands faster.

 

 

Efficiency usually means automating processes to cut costs. Effectiveness is all about consistency and standardization. Compliance ensures companies meet both federal and state requirements for privacy and security improvements. The RPA benefits remain so broad -- and sometimes elusive -- because of the wide variety of implementation cases. According to KPMG, banks and other financial organizations that leverage RPA realize 75 percent cost-savings.

 

Putting RPA at the helm of quantifiable data-driven workflows will be especially crucial for innovation enablement in the years ahead. The Internet of Things is expanding the realm of financial technology services. Customers can now link their financial data to wearable technology and even household appliances. Software bots' ability to interface with the front ends of many application types can help automate the real-time movement of information between systems. Likewise, RPA is an enabler of blockchain technology. Blockchain uses a distributed digital ledger system to verify data inputs through a consensus. No single source controls the ledger, which makes it difficult for any one contributor to commit fraud. For this to work correctly, financial organizations will need to continuously record data entries and attributes such as timestamps, geo-location, and more from many disparate APIs and IT systems. The benefit of RPA bots is that they can operate as fluidly as humans can across IT infrastructure. This means RPA can effectively bridge multiple disparate systems to the blockchain.

 

As tech-savvy consumers ask for more convenience and instant service, traditional financial organizations, like Bank of America or Royal Bank of Canada, and Neo-banks, like Chimes or Revolut, have already deployed mobile apps chatbots and are tapping into the potential of conversational AI technology. Note also that bots and automated services have many times delivered deceptive results and poor user experience. One must take into account that this technology is still in its first stage of deployment and that improvements are being integrated, especially at the user interface and conversational design level. However, bots and automation platforms have made tremendous progress lately, with many AI players either verticalizing their offer (to stay close to user needs in specific markets like banking or e-commerce) or adapting their technology to a particular usage (like customer support or lead generation in the case of Drift). And end-users have taken notice: if only 19% of them are currently making use of chatbots, 95% believe they will be using them more in the future according to SAP. Lydia, for example, is now able to automatically answer more than 65% of its support requests through its virtual help center (they don’t call it a chatbot).  Clustaar predicts three dominant patterns at play, which will influence where Fintech companies will go.

 

Customers often ask the same questions over and over. This pattern is evident by simply typing a query in Google: the suggest feature will propose similar queries typed by people before you. With the Pareto effect in play, it is possible to automate answers to a minority of simple requests that make up the bulk of the volume. A simple example is password resetting or trouble in connecting to WiFi, which in many cases are the most often asked question.


If 24/7 service is a growing desire among consumers, it is even more so with tech-savvy users in mobile-first contexts which where most FinTech and Neo bank companies operate. People carry their smartphones with them all day long and access their mobile apps at any time. FinTech companies have well understood this and have designed their services based on a 24/7 customer engagement framework. To achieve this without some automation is hardly possible. Unless a brand can afford massive call centers to provide 24/7 sales or support lines and pay the price for it, it will, at some point, seriously consider chatbots and conversational AI. Customers have become fond of mobile messaging and live chat interfaces, and this is how they want to interact with brands. Anywhere, anytime.

 

 

According to a report released by Juniper, chatbots will be responsible for over $8 billion annual cost savings by 2022, especially at the support operation level. More precisely, we have found that companies can cut support ticket processing time by 2 to 3 by merely implementing a chatbot scenario that will prequalify customer requests, which, once completed, funnels the requests to human agents. Chatbot technology and conversational AI are already starting to deliver on scaling operations, especially in customer support situations. As many existing and prospective clients have told us, “customer support is the only part of the business that doesn’t scale.” The chatbot can scale these operations by focusing on single level 1 requests, cut costs, and deliver a better user experience at the same time.

 

Fintech companies are influencing market changes by enabling traditional institutions to embrace emergent technologies. These different markets are moving at different speeds for several reasons – legacy system complexities, cost, regulation, and culture, to name a few. With the combination of price and control, there might never be a revolution in the banking industry. But these factors should give these financial institutions ample time to evolve and embrace new technologies that cater to consumers’ ever-changing needs. As technology is becoming ever more central in the finance industry, we tend to consider banks and FinTech startups as opposing forces fighting for their share of the market. The reality is that both sides need each other just as much as they need to compete with each other.

On the one hand, FinTech startups have taken funding from banks and often rely on banking, insurance, and back-office partners to deliver their core products. Banks, on the other hand, have acquired FinTech startups or invested in them to leverage new technology and ways of thinking to upgrade their existing operations and offerings. On another hand, FinTech by itself evolving by building revolutionary technologies. Professors aren’t born: young academics must be nurtured and supported through a long, tough journey into the professoriate. Same with FinTech, we can see a consistent evolution of this enormous body with the scent of revolution.