The Generative AI Revolution: A Profound Transformation in Financial Services

Generative AI (GenAI) remains one of the most transformative forces in technology today, capturing imaginations and redefining industries with unparalleled speed. While traditional AI has excelled in analysis and automation, GenAI is a newer force, capable of creating sophisticated content that mirrors human creativity.

This innovative technology spans multiple modalities—text, audio, video, and beyond—enabling it to summarize extensive documents, craft opinion pieces, generate software code, design visuals, compose music, and even define data quality rules. The applications are virtually limitless.

The rapid evolution of GenAI is driven by continuous advancements in models. Weekly, new models emerge, surpassing their predecessors and intensifying competition among key players.

Key Large Language Models (LLMs):

xAI Grok: Designed for real-time social media interaction.
Anthropic Claude: Prioritizes safety and ethical behavior.
OpenAI ChatGPT: A versatile powerhouse for diverse applications.
Meta LLaMA: Open-source and efficiency-focused.
Google Gemini: Known for advanced reasoning within Google’s ecosystem.
Mistral AI: Combines performance with open-source accessibility.
DeepSeek-R1: Open-source and small operational footprint

Image and Video Generation:

Image Generation: Tools like MidJourney, OpenAI chatGTP / DALL-E, Google Gemini and Stable Diffusion lead the way.
Video Creation: OpenAI’s Sora, Google Veo, and Runway Gen-3 Alpha are revolutionizing content production.

AI’s ability to solve complex problems and surpass human performance in specialized domains has profound implications and AI agents, which empower models to take autonomous actions, mark another milestone in this revolution. The International Monetary Fund (IMF) estimates that AI could impact 40% of jobs globally, worsening overall inequality. For example, translators and transcribers are already being replaced by AI in many firms.

Industry leaders like Sam Altman (OpenAI) and Satya Nadella (Microsoft) predict respectively that AI will significantly disrupt white-collar jobs and that the SaaS industry will disappear as AI agents take over tasks traditionally performed by humans. While these shifts may boost productivity, they also raise ethical concerns and workforce challenges.

As companies pour billions into AI development, ethical debates are intensifying. This is particularly evident as AI models begin to outperform humans, including experts, across many domains, coupled with the rise of AI agents that enable models to take direct actions autonomously. A notable example is the recent leadership turmoil at OpenAI, where concerns over AI safety led first to the temporary firing of the CEO and later to several high-profile departures and the creation of a new startup, Safe Superintelligence. This new venture, driven by several former OpenAI executives, is dedicated to ensuring responsible AI development and secured $1 billion in funding at record speed.

The financial sector has been quick to embrace GenAI. Investments are pouring in as institutions race to unlock its potential, e.g.

Efficiency Gains: The BNPL player Klarna has reduced its workforce by nearly 50%, citing efficiency gains driven by AI. Currently, AI handles two-thirds of the company’s customer service interactions and has contributed to a 25% reduction in marketing expenses. Over the past year, Klarna has downsized from 5,000 to 3,800 employees and plans to further reduce its workforce to 2,000, relying on AI to streamline marketing and customer service operations.
Meanwhile, U.S. financial software provider Intuit announced a 10% workforce reduction, highlighting AI’s ability to automate various manual tasks.
Workforce Expansion: BBVA has doubled its AI team to 400 as it establishes new "AI Factories" in Mexico and Turkey. The bank also launched a GPT store to showcase nearly 3,000 employee-generated adaptations of ChatGPT. Similarly, CIBC plans to hire 200 AI specialists, while Lloyds Banking Group and Wells Fargo have introduced senior director roles dedicated to AI and analytics.
Innovative Products: JP Morgan’s AI chatbot, LLM Suite, is now performing tasks traditionally handled by investment research analysts. Similarly, Lloyds Banking Group has announced the use of AI to automate trade finance checks. Meanwhile, the BIS, ECB, and Deutsche Bundesbank are collaborating to explore the potential of generative AI in improving inflation forecasting.
Specific AI software solution for Financial Services sector: Synthesia leverages an AI platform to produce high-quality video and voiceover content tailored to the needs of financial services. Deriskly offers AI software designed to optimize compliance in financial promotions and communications. Other notable solutions include Reality Defender, a deepfake detection platform that assists banks, insurers, and governments in identifying AI-generated content at scale, and Hyperplane, a data intelligence platform enabling financial institutions to create personalized experiences and predictive models through proprietary large language models.

As financial institutions face rising costs, regulatory pressure, increased competition, declining revenues from traditional income sources and growing consumer demands, Generative AI (GenAI) emerges as a vital lifeline. GenAI is transforming operations by automating repetitive tasks such as data entry and analysis, processing vast amounts of information with unmatched precision, and producing operational content like meeting minutes and summaries. It also enables faster searches of complex data using natural language, saving financial services firms both time and money while optimizing resource allocation to remain competitive.

The potential applications are vast, with primary use cases in customer service—delivering more personalized experiences, higher-quality information, and faster responses—enhancing risk management, and reshaping capital markets. Conversational AI and natural language processing (NLP) empower chatbots to provide banking customers with quick, 24/7 access to account information and services.

The market potential for GenAI in the financial services sector is enormous, with AI assistants, in particular, significantly boosting personal productivity and reducing the number of employees needed to perform the same tasks and redefining the industry’s operational landscape.

According to a report by MarketResearch.biz, the global market size for generative AI in financial services is projected to grow from $847 million in 2022 to $9.5 billion by 2032.
McKinsey estimates that GenAI could contribute $200–$340 billion (2.8 to 4.7 percent) in annual value to the global banking sector through productivity gains.
Daniel Pinto, JP Morgan Chase’s President and COO, has projected that GenAI use cases at the bank could generate up to $2 billion in value. Similarly, Citizens Bank anticipates up to 20% efficiency gains through GenAI as it automates tasks such as coding, customer service, and fraud detection.
Research from the Stanford Digital Economy Lab further highlights GenAI’s potential. In a study on its use at a busy call center, call agents with access to GenAI tools improved their productivity by nearly 14%, with the greatest benefits observed among less experienced workers.

While GenAI’s current hype rivals that of blockchain, its scale and potential impact are significantly greater. Much like blockchain, the true test will however come once the hype settles, as only the most valuable use cases will endure.

The financial services leaders of tomorrow will be those who effectively adopt and scale GenAI applications today.

Comments

Transforming the insurance sector to an Open API Ecosystem

1. Introduction "Open" has recently become a new buzzword in the financial services industry, i.e. open data, open APIs, Open Banking, Open Insurance …, but what does this new buzzword really mean? "Open" refers to the capability of companies to expose their services to the outside world, so that external partners or even competitors can use these services to bring added value to their customers. This trend is made possible by the technological evolution of open APIs (Application Programming Interfaces), which are the digital ports making this communication possible. Together companies, interconnected through open APIs, form a true API ecosystem , offering best-of-breed customer experience, by combining the digital services offered by multiple companies. In the technology sector this evolution has been ongoing for multiple years (think about the travelling sector, allowing you to book any hotel online). An excelle...

RPA - The miracle solution for incumbent banks to bridge the automation gap with neo-banks?

Hypes and marketing buzz words are strongly present in the IT landscape. Often these are existing concepts, which have evolved technologically and are then renamed to a new term, as if it were a brand new technology or concept. If you want to understand and assess these new trends, it is important to reduce the concepts to their essence and compare them with existing technologies , e.g. Integration (middleware) software ensures that 2 separate applications or components can be integrated in an easy way. Of course, there is a huge evolution in the protocols, volumes of exchanged data, scalability, performance…, but in essence the problem remains the same. Nonetheless, there have been multiple terms for integration software such as ETL, ESB, EAI, SOA, Service Mesh… Data storage software ensures that data is stored in such a way that data is not lost and that there is some kind guaranteed consistency, maximum availability and scalability, easy retrieval...

IoT - Revolution or Evolution in the Financial Services Industry

1. The IoT hype We have all heard about the "Internet of Things" (IoT) as this revolutionary new technology, which will radically change our lives. But is it really such a revolution and will it really have an impact on the Financial Services Industry? To refresh our memory, the Internet of Things (IoT) refers to any object , which is able to collect data and communicate and share this information (like condition, geolocation…) over the internet . This communication will often occur between 2 objects (i.e. not involving any human), which is often referred to as Machine-to-Machine (M2M) communication. Well known examples are home thermostats, home security systems, fitness and health monitors, wearables… This all seems futuristic, but smartphones, tablets and smartwatches can also be considered as IoT devices. More importantly, beside these futuristic visions of IoT, the smartphone will most likely continue to be the cent...

PSD3: The Next Phase in Europe’s Payment Services Regulation

With the successful rollout of PSD2, the European Union (EU) continues to advance innovation in the payments domain through the anticipated introduction of the Payment Services Directive 3 (PSD3) . On June 28, 2023, the European Commission published a draft proposal for PSD3 and the Payment Services Regulation (PSR) . The finalized versions of this directive and associated regulation are expected to be available by late 2024, although some predictions suggest a more likely timeline of Q2 or Q3 2025. Given that member states are typically granted an 18-month transition period, PSD3 is expected to come into effect sometime in 2026. Notably, the Commission has introduced a regulation (PSR) alongside the PSD3 directive, ensuring more harmonization across member states as regulations are immediately effective and do not require national implementation, unlike directives. PSD3 shares the same objectives as PSD2, i.e. increasing competition in the payments landscape and en...

Trade-offs Are Inevitable in Software Delivery - Remember the CAP Theorem

In the world of financial services, the integrity of data systems is fundamentally reliant on non-functional requirements (NFRs) such as reliability and security. Despite their importance, NFRs often receive secondary consideration during project scoping, typically being reduced to a generic checklist aimed more at compliance than at genuine functionality. Regrettably, these initial NFRs are seldom met after delivery, which does not usually prevent deployment to production due to the vague and unrealistic nature of the original specifications. This common scenario results in significant end-user frustration as the system does not perform as expected, often being less stable or slower than anticipated. This situation underscores the need for better education on how to articulate and define NFRs , i.e. demanding only what is truly necessary and feasible within the given budget. Early and transparent discussions can lead to system architecture being tailored more close...

Are product silos in a bank inevitable?

Silo thinking is often frowned upon in the industry. It is often a synonym for bureaucratic processes and politics and in almost every article describing the threats of new innovative Fintech players on the banking industry, the strong bank product silos are put forward as one of the main blockages why incumbent banks are not able to (quickly) react to the changing customer expectations. Customers want solutions to their problems and do not want to be bothered about the internal organisation of their bank. Most banks are however organized by product domain (daily banking, investments and lending) and by customer segmentation (retail banking, private banking, SMEs and corporates). This division is reflected both at business and IT side and almost automatically leads to the creation of silos. It is however difficult to reorganize a bank without creating new silos or introducing other types of issues and inefficiencies. An organization is never ideal and needs to take a numbe...

An overview of 1-year blogging

Last week I published my 60th post on my blog called Bankloch (a reference to "Banking" and my family name). The past year, I have published a blog on a weekly basis, providing my humble personal vision on the topics of Fintech, IT software delivery and mobility. This blogging has mainly been a personal enrichment , as it forced me to dive deep into a number of different topics, not only in researching for content, but also in trying to identify trends, innovations and patterns into these topics. Furthermore it allowed me to have several very interesting conversations and discussions with passionate colleagues in the financial industry and to get more insights into the wonderful world of blogging and more general of digital marketing, exploring subjects and tools like: Search Engine Optimization (SEO) LinkedIn post optimization Google Search Console Google AdWorks Google Blogger Thinker360 Finextra … Clearly it is not easy to get the necessary ...

Low- and No-code platforms - Will IT developers soon be out of a job?

“ The future of coding is no coding at all ” - Chris Wanstrath (CEO at GitHub). Mid May I posted a blog on RPA (Robotic Process Automation - https://bankloch.blogspot.com/2020/05/rpa-miracle-solution-for-incumbent.html ) on how this technology, promises the world to companies. A very similar story is found with low- and no-code platforms, which also promise that business people, with limited to no knowledge of IT, can create complex business applications. These platforms originate , just as RPA tools, from the growing demand for IT developments , while IT cannot keep up with the available capacity. As a result, an enormous gap between IT teams and business demands is created, which is often filled by shadow-IT departments, which extend the IT workforce and create business tools in Excel, Access, WordPress… Unfortunately these tools built in shadow-IT departments arrive very soon at their limits, as they don’t support the required non-functional requirements (like h...

AI in Financial Services - A buzzword that is here to stay!

In a few of my most recent blogs I tried to demystify some of the buzzwords (like blockchain, Low- and No-Code platforms, RPA…), which are commonly used in the financial services industry. These buzzwords often entail interesting innovations, but contrary to their promise, they are not silver bullets solving any problem. Another such buzzword is AI (or also referred to as Machine Learning, Deep Learning, Enforced Learning… - the difference between those terms put aside). Again this term is also seriously hyped, creating unrealistic expectations, but contrary to many other buzzwords, this is something I truly believe will have a much larger impact on the financial services industry than many other buzzwords. This opinion is backed by a study of McKinsey and PWC indicating that 72% of company leaders consider that AI will be the most competitive advantage of the future and that this technology will be the most disruptive force in the decades to come. Deep Lea...

The UPI Phenomenon: From Zero to 10 Billion

If there is one Indian innovation that has grabbed global headlines , it is undoubtedly the instant payment system UPI (Unified Payments Interface) . In August 2023, monthly UPI transactions exceeded an astounding 10 billion, marking a remarkable milestone for India’s payments ecosystem. No wonder that UPI has not only revolutionized transactions in India but has also gained international recognition for its remarkable growth. Launched in 2016 by the National Payments Corporation of India (NPCI) in collaboration with 21 member banks, UPI quickly became popular among consumers and businesses. In just a few years, it achieved remarkable milestones : By August 2023, UPI recorded an unprecedented 10.58 billion transactions , with an impressive 50% year-on-year growth. This volume represented approximately 190 billion euros . In July 2023, the UPI network connected 473 different banks . UPI is projected to achieve a staggering 1 ...

Bankloch

Search This Blog