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Entering the Originate-To-Distribute era: Exploring commercial lending and portfolio diversificationFinextra Promoted[On-Demand Webinar] Entering the Originate-To-Distribute era: Exploring commercial lending and portfolio diversification

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Expert opinions

John Adam

John Adam Chief Revenue Officer at Aimprosoft

What is RAG in fintech and how financial services are using it with LLMs to power AI innovation

To operate, organisations in the financial services sector require hundreds of thousands of documents of rich, contextualised data. And to organise, analyse and then use that data, they are increasingly turning to AI. One AI-driven approach to unifying, understanding, structuring and then accessing stores of internal data is the LLM (Large Langua...

/ai Artificial Intelligence and Financial Services

Indra Chourasia

Indra Chourasia Industry Advisor at Tata Consultancy Services (TCS)

Shifting trajectory of financial markets and trading in the AI age

Amid the evolving trading models and market platforms, the fundamental construct of financial markets—to conclude transactions between anonymous or known counterparties—has largely remained unchanged over the years. At the same time, swayed by advanced technology and data-driven innovations, financial markets have witnessed significant changes in ...

/ai /markets Capital Markets Technology

Kuldeep Shrimali

Kuldeep Shrimali Consulting Partner at Tata Consultancy Services

Alternative Investments for Retail Investors – Industry readiness

Background There are over 17,200 private businesses in the United States with annual revenues exceeding $100 million, compared to fewer than 4,060 public companies of the same size. Investors are increasingly exploring opportunities to invest in this sector. While investing in private companies was previously limited mainly to large institutional ...

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Vipin Kumar Sharma

Vipin Kumar Sharma IT and Consulting Delivery Manager at Infosys Ltd

Using AI to Pick ETFs: A Real Investing Use Case

After writing about “How Gen AI Can Help You Pick Stocks & Where It Falls Short”, I wanted to test it in the real world. No theory, practical use case; just me, AI, and the two most talked about ETFs in the moving sectors: the VanEck Semiconductor ETF (SMH) and BlackRock’s iShares Bitcoin Trust (IBIT). The goal? See if AI could help me researc...

/ai /wealth Artificial Intelligence and Financial Services

Anton Roe

Anton Roe CEO at MHR

Empowering finance with AI: why a bottom up approach is key to business success

Despite widespread investment in AI, we are still seeing the adoption of superficial AI initiatives that are failing to deliver tangible value where it matters most. This is particularly true when AI strategies are imposed from the top down, overlooking the insights of those closest to a company’s daily operations. Enthusiastic individuals might e...

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Research

Impact Study

Exploring the rise of originate-to-distribute (OTD) models

Opportunities and challenges for banks in the secondary loan trading market  The lending market has markedly evolved in the last couple of decades. One of the most significant aspects has been the shift from originate-to-hold to originate-to-distribute (OTD) models. Whereas historically, lenders used to originate loans and hold them through maturity, several market factors have necessitated a diversification of risk. Diversification of funds, optimisation of asset management, risk optimisation, as well as a need for increased profitability have catalysed the OTD model— particularly when banks retain the right to service the loans.  However, barriers to adoption remain as banks grapple with infrastructure and data concerns, and regulatory updates in the space are further affecting how banks approach and optimise their OTD models. On top of that, increasing interest rates over the last four years have meant increased risk for banks that are already struggling with regulatory and capital cost. Add to this the rise of private credit institutions that offer direct lending (and face lower regulatory and capital cost), and banks are starting to feel the pressure of decreasing margins.  This Finextra impact study, produced in association with FIS, explores:  The growth of OTD models and the secondary loan trading market;  The challenges banks face in the lending space, including: Increased competition, Inadequate data structures, and Regulatory requirements;  The opportunity that OTD models— combined with artificial intelligence (AI)—offer to help optimise banks’ portfolios and balance sheets.    Register to watch the related Finextra webinar, hosted in association with FIS –  Entering the Originate-To-Distribute era: Exploring commercial lending and portfolio diversification

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Impact Study

Reimagining customer journeys: How can banks upscale experience and boost retention?

To stay competitive and better serve their customer base, financial institutions (FIs) must urgently reimagine their customer journeys — from onboarding to the broader lifetime experience — or risk facing a hit to their market share. Technology has significantly transformed the financial services industry, particularly over the last five years. Challenger banks and fintech firms have rapidly gained popularity thanks to their ability to offer fast, simple, digital services. According to data from Plaid, nearly nine out of 10 consumers were using a fintech application in 2023. This percentage will continue to grow.  Financial institutions (FIs) must urgently reimagine their customer journeys or risk facing a hit to their market share. Indeed, today’s customers are more likely than ever to switch primary banking relationships if they do not receive the services they are looking for. Young, digital natives continue to shape this market, with research revealing that 44% of Gen Z customers have changed their primary banking relationship in the last 12 months. The call to competition cannot be ignored.  But how can FIs innovate to meet these demands, while simultaneously running legacy systems? This Finextra impact study, in association with Hyland, explores how financial institutions can:  Reinvent onboarding and Know-Your-Customer (KYC) processes;  Upscale the overall customer journey;  Look to artificial intelligence (AI) for product enhancement and integration; and  Present real-world case studies for each of these objectives. 

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Future of Report

The Future of European Fintech 2025: A Money20/20 Special Edition

A special edition for Money20/20 Europe 2025. The European fintech space is seeing leaps and bounds in digital innovation, financial technology, and operational resilience. With incoming regulation focused on standarising the sector and disruptive fintech firms challenging banks - the ecosystem is in a transitional period.  Among these challenges, the fintech boom is sweeping the continent. New developments in AI, tokenisation, digital identity, open banking, and more is redefining the banking sector. Europe is primed to act as the epicentre for global fintech innovation.  This Finextra report dives into industry sentiment on what the future holds for European fintech, featuring key insights from NatWest Group, Standard Chartered, BNY Mellon, Magnetiq Bank, GoCardless, Moore Kingston Smith, Stripe, and Augmentum Fintech. It explores:  AI and predictive analytics integration in payments;  Enabling financial inclusion and accessibility in emerging markets;  The role of digital identity and behavioural biometrics in financial services;  Innovation in regulatory practices;  The revolutionary power of smart data and decentralised finance. 

309 downloads

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FinextraTV

How to Drive Banking Innovation with Generative and Agentic AI

Whilst speaking at Temenos Community Forum 2025, Erik Johnson, Global Head of Product Design, Temenos joined the FinextraTV studio to talk about the areas he's most excited about within the development of AI. Discussing product ideation and compliance across both GenAI and Agentic AI, Johnson passionately positions his belief that AI is a tool that enables banks and partners to focus on more innovative and 'fun' day-to-day tasks. Beyond this, Johnson also describes the inherent connection between AI development and co-design.

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Long reads

Hamish Monk

Hamish Monk Senior Reporter at Finextra

What is predictive analysis?

Predictive analytics is a method of data analysis used within the financial services industry – and beyond – to forecast business-related outcomes. It sits on a spectrum, beginning with descriptive analytics, the most basic form of data analysis, then moving to diagnostic analytics, predictive analytics, and finally prescriptive analytics – the mo...

Ram Gopal

Ram Gopal Professor at University of Warwick

AI in fintech: Transforming customer experience and operational efficiency

Why AI—and why now? After two years of explosive progress in generative models, artificial intelligence (AI) has become the defining force behind innovation within financial services. According to NTT Data, a remarkable 91% of banking boards now have generative AI (Gen AI) initiatives on their agendas - a level of executive sponsorship unmatched by...

Hamish Monk

Hamish Monk Senior Reporter at Finextra

What is natural language processing?

The term natural language processing, or NLP, describes a computer’s ability to understand, interpret, or generate human language. It is a type of artificial intelligence (AI) which uses algorithm-backed machine learning (ML) to recognise both the written and spoken word. Testament to its utility, in 2023 the market size of NLP in finance was valu...