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By Nihara Gooneratne · Nov 13, 2024
State of tech in Financial Services: How AI, blockchain, and biometrics are forging the future
Table of contents
How are emerging technologies shaping my industry? What is the current rate of adoption and which use cases show the most promise? Who are the key players leading investments in new solutions? This Insight aims to address these frequently raised questions for the Financial Services sector, encompassing banking, payments, and wealth management.
Our analysis examined product launches, partnerships, and use cases from the past 12 months across multiple technologies such as AI, metaverse, blockchain, IoT, quantum computing, robotics, biometrics, and genomics. The following discussion spotlights key technologies—AI, blockchain, and biometrics—that demonstrated significant potential in use cases and adoption for financial services.
Key takeaways
- Classical AI (predominantly machine learning [ML] and natural language processing [NLP]) has found its footing in backend operations, with 57% of banks having deployed it in fraud detection and 48% in risk assessment. Notable developments included Wells Fargo and Lloyds' AI integrations in trade finance and significant funding rounds like Abound's USD 1 billion raise for international AI lending platform expansion.
- GenAI is gaining momentum across customer-facing operations: Major initiatives included Wells Fargo's Fargo assistant (handling 100 million annual interactions) and NatWest's Cora+ having practical applications of GenAI in this space. Notably, Temenos' launch of “Responsible Generative AI” solutions for core banking operations aimed to address regulatory compliance and data security challenges in financial operations.
- Blockchain and AI-enhanced biometrics appear as active trends across payments: Blockchain is making substantial progress in backend and customer-facing payment applications, with Worldpay reporting a 50% reduction in payment processing time through its stablecoin system and 29% of retail investors using crypto for transactions (up from 23% in 2022). Biometric adoption in financial services has reached 60%–75%—among the highest across sectors—with solutions like Mastercard's Scam Protect combining identity verification and behavioral biometrics.
- AI-driven personalization supports retail investment strategies and back-office automation for wealth managers: Product updates such as Revolut's robo-advisory services and EarnUp's AI Advisor are examples of hyper-personalized investment products. GenAI adoption in wealth management is particularly strong in customer service (69% of firms) and investment research (50%), with BCG estimating potential time savings of up to 30% in areas like customer boarding.
- Open banking data sharing receives big regulatory boost: Relaxation of regulations surrounding open banking has enabled banks to seamlessly share data among themselves, resulting in the emergence of new payment models, such as account-to-account (A2A) and multi-currency payments. Notable developments included HSBC’s launch of Zing, a multi-currency payments app, in collaboration with Visa.
- Asset tokenization regains traction for institutional wealth management: The value of tokenized assets reached USD 15 billion as of September 2024 (excluding stablecoins). Major financial institutions, including BlackRock, Fidelity, and JPMorgan, actively implemented blockchain technology for tokenization, players such as State Street introduced tokenization platforms, and partnerships between companies like AlphaPoint, Polymesh, Archax, and Assetera aimed to enhance and facilitate asset tokenization.
- Quantum computing also showed promising use cases, particularly in portfolio optimization, simulations, and credit analysis. Key players such as Goldman Sachs, JPMorgan, and HSBC were among the major institutions frontlining research into quantum computing in financial services. However, most real-world implementations are still in experimental phases, with 60% of regulators expecting a significant impact within as late as seven years. Notably, D-Wave Systems, a maker of quantum annealing systems, is exploring applications in financial services, a hybrid approach that combines classical CPUs/GPUs with their quantum annealing hardware.
Banking and lending: GenAI gains momentum among banks after late start
Summary of current tech trends
In 2024, the banking sector saw notable developments across three key domains: Traditional AI, GenAI, and the open banking ecosystem. Traditional AI—mainly ML—continues to dominate backend operations, with over 60% of banks utilizing AI in lending and 57% for fraud detection. Notable developments included Wells Fargo and Lloyds' AI integrations in trade finance as well as significant funding rounds like Abound's USD 1 billion raise for international AI lending platform expansion.
GenAI, on the other hand, is disrupting customer-facing banking operations, with the sector poised to achieve up to 30% productivity gains through AI-driven automation according to Accenture. Industry leaders are already making significant strides: NatWest enhanced its Cora+ platform, Wells Fargo's digital assistant manages 100 million customer interactions annually, and Temenos introduced enterprise-grade Responsible Generative AI solutions for core banking functions. The transformation is gaining momentum, with 40% of banking executives expecting GenAI to handle between 6% and 20% of daily operations by year-end, while 65% consider it fundamental to their long-term innovation strategy. Yet obstacles remain, including regulatory compliance requirements, a critical talent shortage (cited by 55% of banks), and the constraints of legacy systems (noted by 38%).
However, despite the banking sector's high potential for AI-driven automation, many institutions have yet to begin their AI journey. This hesitancy is particularly striking compared with the more aggressive AI adoption rates among FinTechs and Financial Services sectors, such as insurance, suggesting that traditional banks risk falling behind more technologically agile competitors.
AI progression levels between banks, FinTechs, and insurance companies
Citi’s research anticipates AI adding USD 170 billion to global banking profits by 2028, a ~9% increase from baseline estimates of over USD 1.8 trillion to nearly USD 2 trillion. However, these gains may be partially offset as AI-enabled clients and competitors drive up transaction volumes. In the longer term, AI-powered banking assistants could fundamentally reshape customer relationships, particularly in retail banking. As consumers prioritize AI capabilities over traditional banking relationships, they may choose their AI assistant first and their bank second, potentially disrupting long-standing business models.
Notable activity across banking and lending
Tech deep dives
1. AI/ML: ML-based solutions remain preferred to optimize back-office functions
AI is fundamentally transforming the banking value chain, particularly in financing decisions, risk assessment, and fraud prevention. This transformation is well underway, with over 60% of financial institutions leveraging AI in their lending operations. Banks and FinTechs have seamlessly integrated AI across their core operations, from customer service to credit evaluation and regulatory compliance, while traditional banks have made significant strides in implementing AI solutions to streamline operations and enhance customer support.
Within AI, machine learning (ML) developments have gained the most traction, particularly in enhancing areas like risk assessment and fraud detection. In fact, over 57% of banking institutions now actively use AI for these purposes, marking the highest adoption rate in the sector. This is reflected in a recent case study by DataVisor, which demonstrated how its AI-powered platform helped a global financial institution achieve a 20% increase in fraud detection while maintaining a 94% accuracy rate.
Offerings that leverage classical NLP (which do not involve GenAI) are mostly used within back-office operations. For instance, Lloyds partnered with Cleareye.ai to streamline its trade finance options through NLP and optical character recognition (OCR). Across recent developments, however, companies are increasingly turning to GenAI for similar activities. For instance, while NLP has long been the core technology behind chatbots, recent advancements now use large language models (LLMs) to power these systems.
Although GenAI captured headlines in 2024, traditional AI continued to advance in banking, which saw notable expansions in 2024. UK lender Abound secured USD 1 billion to expand its AI lending platform internationally, while Swift prepares to launch an AI-powered financial crime detection service in early 2025. Brazilian digital bank Nubank strengthened its data analytics capabilities by acquiring Hyperplane and implementing advanced deep-learning models for risk assessment and collections.
Extent of AI use across bank business areas
The future of AI in banking appears promising beyond current applications. According to an EY survey in September 2024, 58% of banking CIOs were implementing AI initiatives, with an expected 77% by 2025. Citi projects AI will increase banking sector profits by USD 170 billion by 2028, though much of this growth may come from GenAI applications.
2. GenAI: Banking sector set for most disruption with GenAI-accelerated task automation
GenAI has emerged as a powerful force in banking, with major financial institutions actively developing and implementing various applications. These solutions promise to streamline operations, enhance customer interactions, and significantly reduce costs. A recent Accenture study highlighted the US banking sector's exceptional potential for GenAI adoption, suggesting productivity improvements of up to 30% through automation and process augmentation.
Share of work time by industry with potential of GenAI disruption
GenAI is transforming banking operations across customer service, personalization, and operational efficiency. Leading banks are upgrading their traditional chatbots to GenAI-powered solutions, as demonstrated by NatWest's Cora+ and Wells Fargo's Fargo assistant, which now handles 100 million customer interactions annually.
A significant advancement in enterprise banking technology came with Temenos' launch of “Responsible Generative AI” solutions for core banking operations. This implementation addresses key challenges in AI adoption, particularly regarding regulatory compliance and data security in financial operations.
The banking sector's embrace of GenAI continues to accelerate. A KPMG survey revealed that 40% of banking leaders expect GenAI to handle between 6% and 20% of daily tasks by year-end, while 65% consider it crucial for their innovation strategy. This adoption is expected to increase as AI governance frameworks mature.
Notable use cases of technology across banking and lending
Payments: Biometrics boost security with new tech; blockchain meets its match in cross-border payments
Summary of current tech trends
Biometrics has become a standard security feature in payments, with 60%–75% of financial services now using it. This high adoption rate stems from advances in AI that make services safer and easier to use. The technology is popular with customers, too; a Visa study found that 86% of people are interested in using biometrics to verify their payments. Companies like Mastercard are leading the way, creating systems that check identity through multiple factors, including behavior patterns and constant monitoring.
Blockchain continues to transform internal banking operations and consumer payments. Banks are using it to speed up international transfers; Worldpay's stablecoin system has cut processing time in half. More people are using crypto for everyday purchases through special payment cards, with usage rising from 23% in 2022 to 29%. Major companies like Visa and Mastercard are working with blockchain startups to let customers spend cryptocurrency in stores.
Open banking, while not as cutting-edge as AI or blockchain, is growing rapidly in Europe thanks to new regulations like SPAA. This technology enables direct A2A payments that are faster and cheaper than traditional methods. It works especially well for online shopping, bills, and subscription payments, with major payment networks actively adopting these solutions. According to Juniper Research, the use of open banking payments is expected to grow by more than 5x between 2023 and 2027.
Notable activity across payments
Tech deep dives
1. Blockchain: Customer-facing applications rise following successful back-end deployments
Major financial institutions are rapidly integrating blockchain technology into their payment infrastructure. For example, JPMorgan's platform (recently rebranded to Kinexys) facilitates cross-border payments, while Worldpay achieved 50% faster processing through blockchain adoption. UBS and Citi have launched private blockchain networks and Ripple's RippleNet now serves over 175 banks globally.
Consumer-facing blockchain applications are gaining traction, particularly in crypto-to-fiat payment solutions. According to a 2024 EY survey, 29% of retail investors use crypto for transactions, up from 23% in 2022. Visa has partnered with dtcpay and Avalanche, while Mastercard collaborated with MetaMask to enable direct crypto spending. Revolut also launched crypto cards in the UK, allowing seamless crypto-to-fiat conversions at point of sale (POS).
The impact of blockchain on payments is expected to be substantial, with businesses projected to save USD 10 billion globally by 2030 through improved cross-border transactions. Major payment providers like Visa and Mastercard are expanding their blockchain initiatives, creating an integrated ecosystem that bridges traditional and digital currencies. This convergence suggests a future where DeFi solutions become increasingly common in everyday transactions.
2. Biometrics: Combining with complementary technologies to secure transactions
According to facial recognition software provider Oloid, the adoption rate of biometrics in financial services currently stands at ~60%–75%, among the highest compared with other sectors, with the most widespread use case being biometrics for authentication.
Differences in biometric adoption across sectors
The growth in AI is enhancing security and convenience throughout the payment process. Mastercard's Scam Protect, launched in April 2024, exemplifies this trend by combining identity verification, behavioral biometrics, and real-time monitoring in partnership with Verizon, NatWest, and the Global Anti-Scam Alliance. Consumer demand is strong; a Visa survey indicated that 86% of consumers expressed interest in biometric payment authentication.
Key industry developments included IDEX Biometrics's USD 6.4 million investment and its Visa certification for biometric cards. Strategic partnerships are expanding rapidly, with JPMorgan rolling out facial recognition payments through PopID and Alphabet collaborating with checkout.com to enhance Google Pay's biometric capabilities.
The biometric payments market shows strong growth potential, with increasing adoption of multi-modal authentication methods combining facial recognition, fingerprint scanning, and palm verification. Our market estimates place the total addressable market at over USD 16 billion, with the current market at USD 2.1 billion and projected growth of 15.6% annually over the next five years.
Notable use cases of technology across payments
The open banking ecosystem: A key AI beneficiary gains additional regulatory support
The US open banking landscape reached a pivotal moment in October 2024 with the release of Section 1033 of the Dodd-Frank Act. This rule requires financial institutions to provide consumer financial data access upon request. At the same time, AI technologies are enabling real-time analysis, personalized advice, and predictive insights.
Meanwhile, open banking APIs are also advancing payment systems, especially in real-time A2A payments and cross-border transactions. By enabling secure data exchange between banks and third-party providers, APIs enable direct, seamless transfers from bank accounts without card networks, reducing fees and improving settlement speed. European regulatory frameworks like the SEPA Payment Account Access (SPAA) Scheme have supported these innovations by promoting secure, interoperable systems between banks and FinTechs.
A2A payments are also gaining traction in Europe, as consumers and businesses opt for lower-cost, faster direct transfers, which are particularly useful in ecommerce, bill payments, and recurring transactions. Additionally, open banking has fueled multi-currency and cross-border payment apps, enabling real-time, direct international transfers and enhancing convenience for global users.
Major institutions like JPMorgan and Wells Fargo are leading the charge by enhancing their API infrastructure for secure data sharing. Meanwhile, key payment providers like Mastercard and Visa continue to form partnerships to integrate open banking solutions, suggesting broader industry alignment toward API-driven, direct payment solutions. According to Juniper Research, these regulatory changes and growing consumer demand are expected to drive a 4.7x increase in open banking usage over the next four years.
Wealth management: AI-driven personalization continues to grow as GenAI unlocks significant savings for wealth managers
Summary of current tech trends
AI and ML are reshaping wealth management by enabling personalized investing and streamlining operations. Recent data from the 2024 Advisor Outlook Study show that 62% of investment advisors are focusing on automating tasks, while 39% are using AI for risk management and compliance. New AI-powered services launched in 2024 included Revolut's robo-advisor and EarnUp's AI Advisor platform. PwC expects AI-driven digital platforms to manage USD 6 trillion in assets by 2027, more than doubling from 2022.
GenAI and blockchain are driving the next wave of industry innovation. Most firms are embracing GenAI, with 69% using it for customer service and 50% for investment research. BCG research suggests this could reduce time spent on customer service tasks by up to 30%. Blockchain use is also growing, especially in asset tokenization, which reached USD 15 billion by September 2024. Major players like BlackRock, Fidelity, and JPMorgan are adopting blockchain technology, with McKinsey forecasting tokenized assets to reach USD 2 trillion by 2030.
Notable activity across wealth management
Tech deep dives
1. AI/ML: Enabling hyper-personalized investment strategies with efficiencies across the investment value chain
AI enables hyper-personalized investment strategies in retail wealth management by analyzing vast amounts of market data, identifying patterns, and making rapid investment decisions based on individual client profiles.
Asset and portfolio managers are mainly adopting AI to enhance operational efficiency. For example, having an AI-based risk and portfolio analytics solution affords them quick reactions to market changes. AI and GenAI also have the potential to support other areas of the value chain, such as sales and marketing, trade execution, IT, and business management.
Asset manager efficiency gains across the value chain
The 2024 Advisor Outlook Study by Schwab Advisor Services found that task automation emerged as a leading AI application in wealth management, with 62% of independent investment advisors identifying it as a primary focus area, followed by risk management and compliance applications at 39%.
Extent of AI use across wealth management
A recent LSEG survey shows strong investor acceptance of AI in investment processes. Over 90% welcome AI for financial product research, while more than 80% support its use in portfolio management. The retail wealth management landscape is shifting, as startups introduce direct-access platforms that offer personalized investment services without traditional intermediaries. Though major firms like JPMorgan and Morgan Stanley have launched digital investment tools, startups continue to lead innovation in this space.
Within the branches of AI, ML-based solutions were dominant across wealth management and were seen in several new product launches in 2024. Revolut introduced robo-advisory services in the EEA, while EarnUp released its AI Advisor. BrightPlan and Brighty App launched AI-powered financial wellness coaches and investment tools to meet growing demands for personalized guidance. This trend of combining AI with traditional advisory services is exemplified by platforms like “SigFig Engage,” which enables AI and human advisor collaboration.
Recent mergers and acquisitions show the growing importance of AI capabilities. Robinhood's purchase of Pluto Capital and Betterment's acquisition of Marcus Invest demonstrate how firms are expanding their AI-driven services. According to a PwC survey, AI-enabled digital platforms are expected to manage nearly USD 6 trillion in assets by 2027, double that of 2022.
2. GenAI: Middle-office functions face disruption as use cases evolve from basic customer service
GenAI in wealth management primarily powers personalized, on-demand financial advisory services. While its integration lags behind banking sector implementations, growth potential remains strong. A 2023 EY survey found that 69% of wealth and asset managers adopt GenAI services primarily to enhance client experience.
The impact of GenAI spans customer support, marketing, research, and analysis. A March 2024 Celent Wealth Management survey revealed that 69% of firms have implemented GenAI for customer service in front-office operations. Middle-office adoption follows closely, with 50% of firms using GenAI for investment research. Recent developments have focused on middle-office functions, particularly in data retrieval and generating insights.
Extent of GenAI use across wealth management
A July 2024 report by BCG estimates GenAI solutions to result in efficiency gains across all areas of the wealth management value chain, particularly in customer boarding and servicing, with potential time savings of up to 30% in these areas.
GenAI applications across the value chain
Incumbent players such as Wells Fargo have launched initiatives to roll out the firm-wide adoption of GenAI solutions. Given the growing interest in GenAI solutions to streamline middle-office functions, this layer will likely be further impacted by GenAI solutions. Additionally, potential cost savings from GenAI solutions are likely to propel GenAI adoption, with PwC anticipating savings of up to 15% of asset managers’ cost base.
3. Blockchain: Tokenization regains momentum after a slow start
Blockchain technology is rapidly transforming institutional wealth management, with asset tokenization emerging as the leading application. The value of tokenized real-world assets reached USD 15 billion by September 2024, attracting major players like BlackRock, Fidelity, and JPMorgan, who are actively implementing blockchain solutions for their client offerings.
Industry momentum is evident through significant developments, including State Street's new tokenization platform and WisdomTree's WisdomTree Connect. According to industry research, market enthusiasm is reflected in recent surveys, where 88% of investors are advancing tokenization plans and 91% are interested in tokenized products.
Outlook-wise, McKinsey estimates the tokenized market capitalization to reach ~USD 2 trillion by 2030, excluding cryptocurrencies and stablecoins. This growth will primarily be driven by increased adoption across mutual funds, bonds, and alternative investment vehicles.
Tokenized assets by 2030
Notable use cases of technology across wealth management
Appendices
Recent developments: Banking
1. AI/ML
Notable activities
2. GenAI
Notable activities
3. Open banking ecosystem
Notable activities
Recent developments: Payments
1. Blockchain
Notable activities
2. Biometrics
Notable activities
Recent developments: Open banking
Notable activities
Recent developments: Wealth management
1. AI/ML
Notable activities
2. GenAI
Notable activities
3. Blockchain
Notable activities
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