In the past few years, non-bank entities, including venture capital-backed fintech startups, have taken the industry by storm and are expected to continue driving the future of fintech innovation.
Unprecedented developments in financial technology and their adoption have seen innovations such as mobile payments, digital currencies, peer-to-peer lending and marketplace lending establish a new standard in the financial sector.
Now, blockchain and distributed ledger, artificial intelligence, machine learning and regulatory technologies are driving the next wave of the fintech revolution.
These fintech innovations are progressively deconstructing the walls that long-surrounded traditional financial entities, causing a radical shift in the conventional value chain, business model and market positioning. Business leaders need to assess and step up to new fintech solutions and deploy fintech strategies that will put their organizations ahead of the competition.
The Emerging Technologies of the Next Fintech Disruption
Fintech innovation is upending consumer experiences by providing a more user-centric approach to financial services. Emerging technologies in fintech are giving startups and financial sector incumbents new opportunities for consumer value creation by gaining a deeper understanding of their needs and designing bespoke solutions.
AI-based analytical tools that collect and integrate structured and unstructured data are supporting process optimization, risk management and strategic decision-making in the fintech marketplace.
Thanks to the widespread reach of data networks and smartphones, fintech is progressively expanding access to financial services for a broader segment of global consumers.
The emerging technologies driving the next wave of fintech evolution include:
Artificial intelligence and machine learning in conjunction with Big Data are using cognitive abilities to process large amounts of unstructured text and data to generate more insights. AI chatbots or virtual assistants that independently manage low-risk operations, such as performing small transactions, explaining financial products and providing basic financial advice to customers, are just the beginning of what AI can do in the financial industry.
Blockchain in fintech is increasingly providing a transparent, secure, immutable and reliable ledger to document contracts, transactions and records. Blockchain Bonds, blockchain clearing and settlement systems are making intra-bank and inter-bank transactions cheaper and faster.
Open Banking Application Program Interfaces (APIs)
Open banking APIs can safely be considered the backbone of fintech innovation, with their disruptive impact being felt in every nook of the financial sector. Thus far, Banking-as-a-Service (BaaS), where fintechs leveraged open APIs to create new services, improve the banking experience and generate value, was the primary way fintechs drove innovation. The next Open API model is Banking-as-a-Platform (BaaP), where banks are collaborating with third parties to provide financial services while still retaining control of consumer data and ensuring the quality of services provided on their platform.
Regulatory Technology (RegTech)
As global financial service regulations become more complex, RegTech solutions are leveraging AI, predictive analytics, cloud computing and Big Data to help financial institutions monitor, report and comply with regulatory requirements. With the help of RegTech, fintech and banks are automating compliance tasks, reducing risk fraud, streamlining authentication and identity management. RegTechs solutions are helping banks increase transparency and consistency and lowering the cost of compliance.
9 Innovative and Popular Fintech Solutions
Fintech startups and enterprises have taken various aspects of the traditional banking services and flipped the way consumers and financial industry incumbents think about them.
The nine most popular fintech solutions are:
1. Alternate credit scoring
Conventional bank loan screenings are stringent and based on outdated credit scoring criteria. Now, fintechs are opening up solutions for people who don’t meet the bank standards by considering alternate data points like social signals and percentile scoring amongst similar borrower groups. Fintechs like Nova Credit are using these qualitative factors and their AI-based self-learning algorithm to arrive at better lending decisions.
2. Alternative insurance underwriting
Traditional premium calculations happen by averaging (referred to as ‘normalizing’) as risk premiums don’t factor data points that aren’t quantifiable. Fintechs like Carpe Data are using AI to build more accurate ways to calculate risk and premiums by considering various alternate data points such as social signals, lifestyle and medical history. These fintechs are also providing customization, such as by adding different terms and conditions and offering co-pay options.
3. Peer-to-peer lending
Peer-to-peer (P2P) lending between individuals and peer-to-business (P2B) lending, where businesses borrow from one or multiple individuals, are making it easier for investors to get better returns than those offered in debt markets. Fintechs like Funding Circle are building platforms that connect borrowers with lenders and taking a fee from the borrower’s repayment.
4. Small ticket loans
Smaller ticket loans involve low margins and high costs, which is why FinServs avoid them. But fintechs like Affirm are delivering buy now & pay later (BNPL), which allow customers to make purchases without authentications. In turn, these fintechs are collecting and sharing customer data with businesses to help determine customer demographics and ensure highly customized marketing offers.
5. Payment gateways
Traditional banks charge enormous fees to handle transactions and payment gateways help bypass that for online businesses. Stripe and Alipay are two of the most popular payment gateways that merchants integrate on their website to deploy convenient payment methods.
6. Digital wallets
Digital wallets like Venmo and Google Wallet are a cross between a bank account and a payment gateway. Users can pre-load money and use it for online or offline transactions with merchants who use these digital wallets.
7. Asset management
Robinhood and companies like it are allowing users to buy stocks and mutual funds without having to pay any fees or commission. In turn, they’re collecting customer data and providing it to high-frequency traders who can then influence the price of the asset.
8. Digital banking
Challenger banks such as N26 are fully digital banks that give consumers and businesses access to no-frills accounts. They act like traditional banks but have no physical offices, leading to low start-up costs, huge overhead savings and reduced rates for consumers.
9. Digital insurance
Fintechs are disrupting the insurance space right alongside financial services. By making use of alternate data points, they offer life and health insurance with better underwriting practices. Fintechs like Lemonade (for real estate) offer much cheaper premiums than traditional companies.
Use Cases of Artificial Intelligence and Machine Learning in Fintech
Fintech professionals have been using AI and ML in hedge funds and trading for many years. But recently, AI/ML applications in finance have bloomedin other areas, such as banking, regulation and insurance. These applications are helping fintech leaders automate time-consuming processes, gain insights from their raw data, personalize customer experiences and uncover insights to solve complex data-rich problems.
Why are business leaders rushing to adopt AI in finance tools?
According to an Economist Intelligence Unit adoption study, 54% of FinServs with 5,000+ employees have adopted AI, and 86% of financial services executives plan to increase their AI-related investments through 2025.
AI and ML applications in finance are helping companies to:
Increase revenue by augmenting productivity and improving user experience
Lower process costs with automation
Improve security and regulatory compliance
9 Use cases of AI and ML in the financial industry
AI/ML algorithms and tools are helping businesses draw out historical customer data, accurately predict their future and launch new solutions. These applications include:
Financial Monitoring: ML algorithms monitor financial systems to detect and flag money laundering techniques, thereby increasing security.
Investment Predictions: Fund managers are using AI/ML tech to identify shifts in the market much sooner than using legacy technology. FinServs like Bank of America, JPMorgan and Morgan Stanley have heavily invested in these applications.
Process Automation: Chatbots, paperwork automation and employee training gamification are few real-life applications of how AI in financial services replaces manual processes. Wells Fargo uses ML-based chatbots that help solve all questions related to a user’s accounts and passwords.
Secure Transactions: Every dollar a bank loses to fraud costs them $2.92. AI tools analyze millions of data points to prevent fraud in real-time.
Risk Management:AI tools can look past essential information like credit card scores to provide more accurate and actionable insights for services related to loan applications and risk scoring.
Algorithmic Trading: Considered the holy grail of AI in Finance, algorithmic trading increases accuracy, helps execute trades at optimal prices, reduces human error and enables automatic and simultaneous checking of multiple market conditions.
Financial Advisory: Robo-advisors can apply traditional data processing techniques to create financial portfolios and solutions such as trading, investments and retirement plans for their users.
Customer Data Management: Efficient data management is at the heart of the financial services industry. AI helps collate, process and secure customer data across channels, from mobile communications to social media activity to transactional details and market data.
Customer Service Level Improvement: Intelligent chatbots and robo-advisors improve customer experiences by providing them quick insights into their monthly expenses, loan eligibility, affordable insurance plans and investment offers.
Future Of Blockchain Technologies In Financial Markets
Blockchain is enabling more open, inclusive and secure financial business models that are leading to efficient processes, reduced costs and new products and services in the finance and banking industry. This technology is also propagating digital financial instruments that can be tailored to investor demands, expand the markets for investors, decrease costs to issuers and reduce counterparty risk.
A study from Juniper Research estimates that blockchain technology will help financial institutions save $1 billion annually till 2024 and $27 billion on cross-border settlement transactions by the end of 2030.
What are the Benefits of Blockchain in Fintech?
Blockchain is a secure, decentralized and transparent tool that records transactions in a distributed ledger. The decentralized nature of blockchain makes it fast and secure while the transaction information remains publicly available. These two characteristics are changing the way money is exchanged globally, solving many of the problems that current financial systems face.
Accountable, transparent governance systems, efficient business models, greater liquidity, lower costs of capital, reduced counterparty risk and access to a broader investor and capital base are some of the benefits of this decentralized technology.
Blockchain is making the financial industry more:
Secure: Blockchain’s distributed, consensus-based architecture removes single points of failures and the need for data intermediaries such as transfer agents. It also enables tamper-proof design, safeguarding against fraud and malicious third parties and making it near impossible to hack and manipulate.
Transparent: Blockchain employs mutually agreed-upon standards, protocols and shared processes, which become a single source of truth for all stakeholders in the network.
Trustworthy: The transparent and immutable distributed ledger makes it easy for different parties on a network to collaborate, manage data and reach agreements.
Programmable: Smart contracts can be created and executed to fit business logic. This tamper-proof, deterministic software automates processes while maintaining trust and efficiency.
Private: Blockchain allows for granular data privacy across every layer of the software stack and allows selective sharing of business data across networks. This dramatically improves trust, efficiency and transparency, allowing better privacy and confidentiality.
High-Performing: Blockchain allows for hybrid networks that can sustain hundreds of transactions per second and periodic surges in activities.
Scalable: Hybrid networks allow interoperability between private and public chains and give businesses a global reach along with tremendous resilience and high integrity.
What are the Use Cases of Blockchain in Financial Services?
Marcel Schmalisch, Head of Financial Industries at consulting group Horváth, says, “By making it easier for everyone to own securities, [blockchain] could broaden inclusion, for instance, by the creation of a new asset class, the inclusion of new customer segments and by facilitating trade.” Ethereum-based blockchain solution provider Consensys have identified the following use cases of blockchain in the financial services industry:
The Role of Regulatory Technology in Fintech Innovation
The rise of fintech innovation has drawn the attention of financial regulators. Fintech solutions face a growing number of risks and complexities related to privacy, personal information and data treatment, customer protection, transparency, and cybersecurity. This is leading to increased regulatory oversight of the fintech industry.
The goal of financial regulators is by no means to thwart innovation but encourage developments in the fintech industry while protecting markets, consumers and investors.
Hence, financial regulations are growing side by side with the maturing fintech ecosystem. Regulators are evaluating existing rules and setting new ones to address the opportunities and challenges presented by emerging financial technologies.
Specifically, the U.S., Europe and the UK are leading the charge in enacting policies targeting fintech innovation. Thus, these changing regulations are becoming critical factors in the fintech industry and could become decisive in its growth and speed of development.
Why do financial institutions need RegTech?
Financial institutions need RegTech to lessen the burden from the growing regulatory policies. Coping with the sheer volume of new regulatory changes, which add to the complexities and resource use for financial institutions can be a considerable challenge. Organizations are starting to turn to regulatory technology solutions to meet those challenges and remain compliant.
RegTech solutions help financial institutions keep up with complex regulations, litigations and regulatory remediations while reducing the cost of non-compliance. Following regulations such as PSD2, MiFID II, 4MLD and GDPR become more manageable when organizations implement RegTech by using open APIs and the RegTech-as-a-Service model.
What are the challenges faced by financial institutions that RegTech can solve?
PwC points to the following challenges faced by financial institutions that RegTech can easily solve:
Frequent additions of financial regulations by governments
Circulars and modifications on existing regulations
High overhead costs on production and deployment of solution to comply with the regulation
High penalty on non-compliance with regulations
Constraints of legacy systems and insufficient automation and digitization to meet the pace of regulatory changes
Non-standardized approach, incompatible systems, insufficient integration of systems
What are the main technologies driving RegTech Solutions?
The emerging technologies that are helping startups build robust RegTech solutions for the fintech industry include:
Artificial intelligence, machine learning, deep learning and predictive analytics
Data mining and analytics
Open banking APIs
How can RegTechs help financial institutions?
RegTechs enable financial institutions to wade through regulations effectively and remain compliant using proactive analysis with “what if” situations.
PwC lists a few areas where RegTechs can help financial institutions:
Remain compliant with regulations
Simplify data management and reporting
Data analytics and decision making
Fraud and risk management
What are the advantages of using RegTech beyond regulatory compliance?
Other than regulatory reporting and fraud management, RegTech solutions help financial institutions by:
Reducing the time needed for client onboarding
Identifying the fraudulent activities
Adapting to new regulations faster
Improving data collection and data analytics
Executive-Level Courses to Prepare for the Future of Fintech Innovation
Esme Learning Solutions is bringing you an executive-level fintech course, an advanced course in fintech and open banking, a blockchain course and a RegTech course to build your foundational knowledge and gain expertise in these emerging areas of the fintech industry.
Oxford Fintech Programme teaches you the foundations of financial technology, the emerging technologies driving the most impactful disruptions, the regulatory changes startups and incumbents face and opportunities for business leaders and fintech innovators.
Oxford AI in Finance and Open Banking Programme teaches you about the criticality of AI and data in financial services, open banking and the data revolution, opportunities for incumbents and startups and building and deploying responsible AI systems.
Oxford Blockchain Strategy Programme teaches you how blockchain protocols work, the blockchain applications and ecosystem, where cryptocurrencies fit in and the legal, ESG and regulatory challenges it faces.
Cambridge RegTech: AI for Financial Regulation, Risk and Complianceteaches you the fundamental concepts of RegTech and how it is evolving, AI-powered tools in managing regulation, scaling machine-readable regulation and building or buying RegTech solutions.