The Future Of Fintech: AI
Implementing artificial intelligence (AI) in fintech brings together one of the most important technology trends of the past decade with one of the most innovative and disruptive sectors. AI used by fintech companies promises to change how banks and other financial institutions operate a broad range of mission-critical functions, improving their operations and customer experiences in the process. Such is the opportunity for AI in fintech that the market is forecast to reach $27 billion (USD) in 2026, up from $9 billion (USD) in 2022.
What Is AI In Fintech?
AI is used for a variety of purposes in the fintech industry. Often mixed with machine learning, a method of training AI, AI in fintech involves “intelligent” systems that automate or enable solutions for complex problems and processes, and/or uncover insights in data. Applications include Anti-Money Laundering (AML) processes, fraud checks, credit checks, decision support, risk assessments, and more.
Managing The AI Beast
With great technology comes great responsibility and the application of AI and data collection in financial services is one that raises many questions in terms of management, security, and regulation. The European Union recently introduced rules that will begin to shape the way AI is used, with a particular focus on the financial services sector. Shawn Tan, the chief executive of AI ecosystem builder Skymind, a machine intelligence startup company supporting the open-source deep learning framework Deep learning and the JVM-based scientific computing library ND4J explains, “The new rules include regulations around cases that are perceived as endangering people’s safety or fundamental rights, such as AI-enabled behaviour manipulation techniques. There are also prohibitions on how law enforcement can use biometric surveillance in public places with broad exemptions.”
The Customer Experience
AI has been most effectively employed as a vehicle for customer-centric services. Aside from trouble-shooting chatbots, the technology provides an almost unending array of solutions to make life easier for the customer and incentivise the marketplace. Jenny Hotchin, Legal Practice Lead, iManage, helps law firms with financial services practices and in-house legal teams in organisations (including financial services firms) deliver legal services more effectively using technology, including AI. In her opinion, it is the handling of financial services through AI technology that has taken its usage to a new level.
The advanced nature of AI today already greatly exceeds the average person’s data literacy level, Hotchin says, which is one of the reasons for increased regulation, including the proposed new AI Act. “I was one of those people that would only go and look once my card had been rejected for lack of funds. Even when I had online banking and a banking app in my hand, the experience was such that I checked it no more than once a week.
“Now the user experience I get from challenger banks, products, and services are so rewarding I have totally changed my behaviour. I don’t just know my bank balance. I know what is going on with my mortgage, my savings, my investments, even my pension.” Hotchin points out that consumers are so used to a seamless user experience that if it isn’t provided, they will simply seek it elsewhere. It’s become an expectation of the financial services space. “We get frustrated as the user experience we tolerate in our working lives is often far inferior to that which we enjoy in our consumer lives,” she says. Indeed, Hotchin argues that the increasing reliance on AI is not motivated by technological advancement but rather by human understanding of how best to apply it “usefully across all areas of the firm in a way that is rewarding and therefore adopted.”
The Future Of AI In Financial Services
As AI continues to be a growing force within fintech, experts believe its usage will spread across more sectors, increasing crossovers that will inevitably result in tensions – most specifically in the area of access to data. The pandemic has also caused an accelerated shift away from physical and towards digital communication, affecting the entire financial industry, but the motivation to increase AI within the sector will ultimately be driven by how much financial services organisations invest in upskilling their workforce. This upskilling is required to get real value from democratising insights, says Spencer Tuttle, SVP WW Sales at ThoughtSpot, the AI & search-driven analytics provider.
“According to the data, the industry is at a halfway point when it comes to upskilling their employees, with 49% of respondents saying training initiatives for employees to better understand AI are currently in place.” He adds, “An end goal is to be able to react at the speed of thought to changing conditions, markets, and information: Making the best use of time because getting to understanding has not been a fast process in the history of business intelligence.
In the next 10 years, three key technologies will drive business model reinventions while shaping the competitive landscape of the financial industry.
Technological progress and innovation are the linchpins of fintech development and will continue to drive disruptive business models in financial services. According to McKinsey analysis, seven key technologies will drive fintech development and shape the competitive landscape of finance over the next decade:
1. Artificial intelligence will drive massive value creation
McKinsey estimates that artificial intelligence (AI) can generate up to $1 trillion in additional value for the global banking industry annually. Banks and other financial institutions are tipped to adopt an AI-first mindset that will better prepare them to resist encroachment onto their territory by expanding technology firms.
In financial services, automatic factor discovery, or the machine-based identification of the elements that drive outperformance, will become more prevalent, helping to hone financial modeling across the sector. As a key application of AI semantic representation, knowledge graphs and graph computing will also play a greater role. Their ability to assist in building associations and identifying patterns across complex financial networks, drawing on a wide range of often disparate data sources, will have far-reaching implications in the years to come.
2. Blockchain will disrupt established financial protocols
Distributed Ledger Technology (DLT) allows the recording and sharing of data across multiple data stores, and for transactions and data to be recorded, shared, and synchronized across a distributed network of participants at the same time.
Some DTLs use blockchains to store and transmit their data, as well as cryptographic and algorithmic methods to record and synchronize the data across the network in an immutable manner. DTL will increasingly underpin ecosystem financing by allowing the storage of financial transactions in multiple places at once. Increasingly, cross-chain technology will facilitate blockchain interoperability, allowing chains established on different protocols to share and transmit data and value across tasks and industries, including payments processing and supply chain management.
Technologies such as smart contracts, zero-knowledge proof, and distributed data storage and exchange, which are key to existing fintech innovations such as digital wallets, digital assets, decentralized finance (DeFi), and non-fungible tokens (NFT), will continue to play a prominent role.
3. Cloud computing will liberate financial services players
McKinsey research shows that by 2030, cloud technology will account for EBITDA (earnings before interest, tax, depreciation, and amortization) in excess of $1 trillion across the world’s top 500 companies. Our research shows that effective use of the cloud can increase the efficiency of migrated application development and maintenance by 38 percent; raise infrastructure cost efficiency by 29 percent; and reduce migrated applications’ downtime by ~57 percent, thus lowering costs associated with technical violations by 26 percent.
At the same time, the cloud can improve platform integrity through automated and embedded security processes and controls. Development, Security, and Operations (DevSecOps), or the idea that security is a responsibility that can be actioned across an organization in step with the growth of its development and operations, is a primary example of a cloud-based feature that reduces technical risks through a consistent, cross-environmental technology stack.
Financial institutions should be aware of three major forms of cloud services: public cloud, hybrid cloud, and private cloud. Public cloud means that the infrastructure is owned by cloud computing service providers, who sell cloud services to a wide range of organizations or the public. Hybrid cloud infrastructure is composed of two or more types of cloud (private, public) that are maintained independently, but connected by proprietary technology. Private cloud means that the infrastructure is built for an individual customer’s exclusive use, deployable in the company data centers, or via other hosting facilities.
These key technologies and trends are becoming increasingly intertwined and integrated, giving massive impetus to fintech and financial industry innovation. As it stands, it is niche financial sub-sectors that are most adept at harnessing technological innovations to launch applications, generate value, and shape the competitive landscape. In the future, traditional financial institutions will need to bring their considerable resources to bear to stay on top of the gathering wave of financial industry disruption.