Market Research In Finance

Everyone is talking about agentic AI and yet the next frontier is already in the making: Multi-Agent Systems (MAS). AI didn’t arrive all at once – although in many cases it might seem it did. It evolved in distinct phases, each unlocking new capabilities and changing how work gets done: 𝟭. 𝗧𝗿𝗮𝗱𝗶𝘁𝗶𝗼𝗻𝗮𝗹 𝗔𝗜 (𝗣𝗿𝗲𝗱𝗶𝗰𝘁𝗶𝘃𝗲 𝗔𝗜): - Systems powering rule-based models and statistical inference to detect fraud, recommend investments, and process documents - all in response to human prompts. - Financial Services (FS) example: Credit scoring models and fraud detection engines improved efficiency, but remained passive tools waiting on human input. 𝟮. 𝗚𝗲𝗻𝗲𝗿𝗮𝘁𝗶𝘃𝗲 𝗔𝗜 (𝗚𝗲𝗻𝗔𝗜): - LLMs and foundation models that brought language fluency and contextual understanding. These systems can create, explain, and summarize - moving from data crunching to content generation. - FS example: Chatbots that summarize regulatory filings, generate client reports, or support advisors with contextual investment narratives. 𝟯. 𝗔𝗴𝗲𝗻𝘁𝗶𝗰 𝗔𝗜: - Systems that can interpret goals, plan actions, and operate independently within constraints. These agents shift the human role from executing tasks to defining intent. - FS example: AI agents that autonomously rebalance portfolios based on client preferences and market movements - no human intervention required. 𝟰. 𝗠𝘂𝗹𝘁𝗶-𝗔𝗴𝗲𝗻𝘁 𝗦𝘆𝘀𝘁𝗲𝗺𝘀 (𝗠𝗔𝗦): - MAS represent the next leap. Multiple agents - each specialized - work together, negotiate, and adapt in real time to achieve shared outcomes across environments. - FS: Agents handling client onboarding, AML checks, credit assessment, and regulatory filings collaborate seamlessly to approve new clients in minutes. 𝗪𝗵𝘆 𝘁𝗵𝗶𝘀 𝗺𝗮𝘁𝘁𝗲𝗿𝘀: MAS enable distributed, intelligent systems that can self-organize, learn continuously, and respond dynamically to change. They reduce operational bottlenecks and shift digital architectures from static pipelines to living systems. 𝗜𝗺𝗽𝗹𝗶𝗰𝗮𝘁𝗶𝗼𝗻𝘀 𝗳𝗼𝗿 𝗙𝗶𝗻𝗮𝗻𝗰𝗶𝗮𝗹 𝗦𝗲𝗿𝘃𝗶𝗰𝗲𝘀: - Efficiency: MAS collapse multi-day processes into seconds - from KYC to loan origination. - Mass hyper-personalization: Real-time tailoring of product decisions across customer journeys and risk contexts. - Resilience: Distributed agents can recover from local failures, reroute tasks, and maintain service continuity without manual intervention. - Compliance: Agents track regulatory changes and trigger operational updates autonomously. MAS aren’t just the next step in AI - they’re how AI starts to really work like a system. The real transformation won’t be about bigger models anymore, but about smarter collaboration between them. Opinions: my own, Graphic source: Capgemini 𝐒𝐮𝐛𝐬𝐜𝐫𝐢𝐛𝐞 𝐭𝐨 𝐦𝐲 𝐧𝐞𝐰𝐬𝐥𝐞𝐭𝐭𝐞𝐫: https://lnkd.in/dkqhnxdg

🔵 A fascinating report from Moody's on the evolution of GenAI in financial services. Moody`s has been walking the talk since 2022 (see an early article about them in the comments on their GenAI application in the context of Exponential Risk). 🔄 Moody's outlines 4 stages of GenAI maturity: • Assisted Intelligence: Basic chatbots and RAG frameworks • Augmented Intelligence: Context-aware capabilities with human oversight • Automated Intelligence: Task execution and basic recommendations • Autonomous Intelligence: AI that can plan, execute, evaluate, and adapt ⚙️ Key frameworks powering their solutions: - 𝐀𝐮𝐭𝐨𝐠𝐞𝐧: For generating high-quality financial reports - 𝐂𝐫𝐞𝐰𝐀𝐈: Enabling human-AI collaboration - 𝐋𝐚𝐧𝐫𝐚𝐩𝐡: Using graph-based systems for complex financial relationships 🔍 Their 𝐑𝐞𝐜𝐨𝐧𝐀𝐈 platform, integrated into EDF-X, is particularly impressive: - Uses multiple agents to evaluate Early Warning Signals for companies of any size (not only Fortune500) - Real-time monitoring of news, controversies, macroeconomic indicators, and regulatory filings - Customized analysis that scales from small businesses to Fortune 500 companies 🤖 Smart approach to accuracy: They run analyses through multiple LLMs (GPT-4, Claude 2, Llama 3, Gemini, and Moody's fine-tuned models) with majority voting to reduce hallucinations and increase reliability. 💡 Real-world applications: • Automated credit analysis • Enhanced risk management • "Service as software" - agents writing and executing code on demand Moody's was one of the first to market with a GenAI product and is now pioneering agentic platforms in financial services. #FinancialServices #ArtificialIntelligence #GenAI #Innovation #Agents #efiinsights

One consistent finding in economics is that uncertainty reduces irreversible investment. Irreversible investment includes things like capital equipment and employment in that a firm cannot fully recover the value of such investments if a change of course is ultimately needed (e.g., you can’t ship back capital equipment to your vendor, there are fixed costs with hiring workers, etc.). Given all the uncertainty about tariffs (what economists call their second moment effects) beyond the generally negative sentiment (what economists call negative first moment effects), one would expect the tariffs put in place far in 2025 to have a substantial negative impact on future capital investment and current hiring. This is exactly what has occurred based on manufacturing survey data that I’ve aggregated across five Federal Reserve Board banks. Two charts below. Thoughts: •The top chart shows future capital investment intentions across President Trump’s first and second terms. A reading of 0 = the January of the year he was sworn in. The data stretch back to the January of the respective election year (e.g., -13 = January 2016 and January 2024). I’ve mean-centered each series by the January – January averages to make the pre-office trends more comparable. We see trends for capital investment were following nearly identical patterns until President Trump took office in the second term (where a reading of 1 corresponds to February 2025 for the red series with triangle marker). Compared with 2017, 2025’s capital investment intentions have dramatically underperformed. That the nadir was reached in Month 3 (corresponding to April 2025) during the height of the tariff chaos is consistent with my argument. •The bottom chart shows employment at manufacturers. As before, we see very similar patterns prior to President Trump taking office for both terms, but then employment in 2025 dramatically underperforms 2017. •Given parallel behavior of both series prior to the start of each term in office, the only reasonable conclusion for the dramatic differences since being in office is the tariff policies. This can be shown by consulting data on the mentions of ‘tariff’ in the Federal Reserve’s Beige Book or looking at the effective tariff rates on imports over these respective periods. Implication: uncertainty reduces irreversible investments (see this outstanding recent paper https://lnkd.in/gs9ypBp6). We are sadly seeing this play out in 2025. If President Trump would remove all the tariffs he has put in place in 2025 and then further reverse many of the ones he put in place in 2018-2019 that the Biden Administration foolishly kept in place, we would see the economy boom. #supplychain #shipsandshipping #economics #markets #freight #trucking #logistics   

Financial services spend the most on AI and extract the least value from it. Financial services firms lead global AI spending, yet adoption remains low because operating models have not caught up with technical capability. Capital is being spent on models while workflows are still designed for manual reviews and slow approvals because governance has not evolved. The risk is not unused software but delayed decisions that slow revenue and increase compliance cost. Ignoring this keeps institutions operating at higher latency. AI systems now generate real-time signals in areas like fraud detection and customer targeting because data access and computing power have improved. Organizations struggle to act on these signals because approval structures and trust models were built for periodic reports and not continuous decisions. This creates a gap where insight exists but execution stalls. This means: value erodes before it reaches the customer or the balance sheet. AI adoption doesn’t succeed when added to unchanged workflows because people become the constraint instead of the technology. One practical way to begin is to choose a decision that currently takes days, redesign the approval path to work in minutes and avoid using AI where accountability cannot be clearly assigned. #AIInBanking #FinancialServices #AIAdoption #EnterpriseAI #OperatingModel #WorkflowDesign #DecisionLatency #AIGovernance #BusinessOutcomes #DigitalOperations #AIExecution #Leadership

Open Finance: Unlocking Innovation in Financial Services #OpenFinance represents the next evolution beyond #OpenBanking, expanding the principles of #data sharing and third-party access across a broader range of financial products and services. Open Finance aims to give consumers and businesses greater control over their entire financial footprint - including #savings, #investments, #pensions, #insurance, #mortgages and more. Key takeaways from the "Uncovering the true potential of Open Finance" report: 💡 Consumer pain points persist across financial services, from lack of visibility into one's complete financial picture to difficulty comparing products and accessing suitable services. Open Finance can address many of these challenges. 💡 There are already promising Open Finance use cases and solutions emerging across sectors: - Cross-sectoral tools providing holistic financial overviews and insights - Automated savings and investment solutions - More accessible wealth management and financial advice - Consolidated pension dashboards and projections - Personalized insurance products and pricing - Streamlined mortgage application processes - Enhanced cash flow management for SMEs 💡 To realize the full potential of Open Finance, the industry needs to: - Develop consistent standards for authentication and data sharing - Focus on communicating tangible consumer benefits, not technical details - View regulation as an opportunity, not just a compliance burden - Recognize the business case for change and operational efficiencies - Prioritize digitization as a foundational step 💡 Open Finance requires collaboration across the ecosystem - between incumbents, fintechs, regulators and other stakeholders. No single provider can deliver the full vision alone. 💡 Trust and consumer education remain critical. Customers need to understand the value exchange and feel confident in sharing their data. 💡 Open Finance is part of a broader shift towards Open Data across industries. Financial services can help pave the way for data-driven innovation in other sectors. While challenges remain, Open Finance presents a compelling opportunity to create better financial products, improve financial wellbeing, and build a more inclusive financial system. The future is nearly here! #fintech #payments #digitalassets #ai #cloudcomputing #blockchain #embeddedfinance

Not all events that shape the future arrive as breaking news. In 2025, some of the most consequential shifts happened quietly. These were quiet moments of changed direction that will have an impact for long. 1. Renewables reportedly overtook coal in global power generation. For the first time, solar + wind + hydro together probably generated more electricity than coal. Solar alone added more capacity in 2025 than coal and gas combined. 2. Global electricity demand growth hit its fastest pace in decades, driven by AI data centres, EVs and cooling demand. Power demand grew ~3.5–4% globally vs ~2% long-term average. 3. The world crossed 6 billion internet users and 1 billion active digital investors. Retail participation surged across India, Southeast Asia, Africa and LATAM. India alone added ~25–30 million new demat accounts in the year. Capital markets became a mass-participation utility, not an elite activity. 4. The dollar lost ground, not in price, but in usage. While the USD remained dominant, its share in incremental trade invoicing fell. USD share of global FX reserves fell from ~71% in 2000 to ~59% in 2015 and to ~57–58% in 2024–25. Energy trade using non-USD settlement rose from low single digits pre-2020 to ~20–25% of new contracts in selected trade corridors in 2025. 5. Global defence spending crossed $2.6 trillion and became structural rather than cyclical. Defence is now a long-cycle industrial theme like infrastructure or energy. Global defence spending has grown from ~$1.9 tn (2015), to ~$2.2 tn (2021) and to ~$2.6–$2.7 tn in 2025. 6. The private credit market quietly crossed $2 trillion; While public markets grabbed attention, private lending exploded. According to the Financial Stability Board, non-bank financial institutions now hold a larger share of global financial assets than banks. 7. Global fertility rates hit a new low, falling faster than models predicted. Policy incentives failed to reverse the trend. Labour scarcity, automation and immigration have become economic imperatives. 8. Australia is implementing a landmark law banning children under 16 from using social media platforms. If successful, this could fundamentally change the childhood experience for the next generation. 9. The UN warned that over 2.4 billion people faced water stress in 2025. Severe droughts in different parts of the world pushed Governments into emergency rationing, desalination investments and new water-pricing reforms. 10. India successfully tested key technologies toward its first in-space docking capability. Two satellites (SDX-01 and SDX-02) were launched and autonomously met and joined in orbit. SpaDeX is the technological "master key" that unlocks every major space goal India has for the next 20 years. The real story of 2025 is the subtle changes in trajectory in the areas set out above. A decade from now, many of these developments will look obvious in hindsight—and that is usually how structural change announces itself.

This week’s inflation report, though market constructive, continued to underscore the bifurcation taking place between the goods and services sectors of the economy. Key things to note:   *While services inflation remains high in absolute terms, its growth is now downward sloping and is helping to keep core CPI contained. See below, but our forecast is that real incomes are starting to turn positive across a wider swath of U.S. consumers. That is a good thing. That said, we are not out of the woods yet as we expect continued volatility in goods inflation in the coming months, driven by tariffs, wildfires, and outbreaks of bird flu.   *In light of these upward pressures on goods prices, we have adjusted our 2025 headline CPI forecast slightly to 2.8%, up from 2.6% (vs. consensus of 2.5%). Importantly, Fed tightenings and easings are not affecting financial conditions as much as in the past. Key to our thinking is that many of the big corporate capex spenders don’t have as much debt on their balance sheet this cycle. On the interest rate front, we stick with two cuts this year, while we expect the 10-year to trade in the 4.5-4.75% range.    Bigger picture, while our Regime Change thesis does not foresee runaway inflation, we still see a higher resting heart rate this cycle, marked by increased variability due to 1) larger deficits; 2) geopolitical tensions; 3) a complex energy transition; and 4) persistent inflationary trends. At KKR we spend time on longer-term trends, which suggest the following mega-themes:   1. Productivity Enhancements: As input costs, including wages, rise, companies will increasingly prioritize resource allocation toward boosting productivity. 2. Capitalize on Diverse Opportunities: We are strategically targeting both capital-heavy and capital-light investments across sectors such as insurance, consumer receivables, and housing, as well as through corporate carve-outs, particularly in Private Equity and Infrastructure. 3. Supply Chain Resilience: Corporations are seeking greater resilience in global supply chains, emphasizing the security of data, transportation, water, and energy. As the global economy shifts toward more regional models, the need for investment in these areas could reach trillions of dollars. 4. Picks and Shovels of AI: We anticipate substantial government investment aimed at securing energy sources. The demand for data centers, pipelines, cooling technologies, and related services is set to grow significantly, driven by a mega-theme where nearly 25% of total tech capital expenditure originates from the Mag7. 5. Collateral-Backed Cash Flows: We remain positive on investments that generate collateral-based cash flows within Infra, Asset-Based Finance, certain Real Estate sectors, and specific Energy segments. In a rising nominal GDP environment, we expect these assets to appreciate in value, leading to potential multiple expansions across this thematic. Read more at https://go.kkr.com/42dBKkM

AI is transforming financial services. It’s also transforming financial crime. A recent global analysis reported that banks and insurers are now facing a new wave of 𝐀𝐈-𝐞𝐧𝐚𝐛𝐥𝐞𝐝 𝐟𝐫𝐚𝐮𝐝, 𝐜𝐲𝐛𝐞𝐫𝐚𝐭𝐭𝐚𝐜𝐤𝐬, 𝐚𝐧𝐝 𝐭𝐡𝐢𝐫𝐝-𝐩𝐚𝐫𝐭𝐲 𝐯𝐮𝐥𝐧𝐞𝐫𝐚𝐛𝐢𝐥𝐢𝐭𝐢𝐞𝐬 as they digitize core operations. And the risk curve is steep. Deepfake transactions. Synthetic identities. Model-driven phishing. Automated credential stuffing. Real-time manipulation of underwriting or claims workflows. In parallel, IBM’s 2024 Cost of a Data Breach Report found that 𝐟𝐢𝐧𝐚𝐧𝐜𝐢𝐚𝐥 𝐬𝐞𝐫𝐯𝐢𝐜𝐞𝐬 𝐫𝐞𝐦𝐚𝐢𝐧𝐬 𝐨𝐧𝐞 𝐨𝐟 𝐭𝐡𝐞 𝐦𝐨𝐬𝐭-𝐭𝐚𝐫𝐠𝐞𝐭𝐞𝐝 𝐬𝐞𝐜𝐭𝐨𝐫𝐬, with breach costs exceeding 𝐔𝐒𝐃 𝟓.𝟗𝐌 𝐩𝐞𝐫 𝐢𝐧𝐜𝐢𝐝𝐞𝐧𝐭 on average. It implies, AI won’t just accelerate legitimate operations. It will accelerate criminal ones. And this is where leadership matters. Because customers don’t just evaluate financial institutions on product or price. They evaluate them on 𝐭𝐫𝐮𝐬𝐭, the confidence that their data, identity, and money are safe in an increasingly automated world. That’s why AI adoption must move hand-in-hand with: 1. Clear governance frameworks 2. Transparent decision systems 3. Continuous monitoring of model behaviour 4. Strong third-party risk controls 5. Human-in-the-loop safeguards for high-impact decisions AI can make financial systems smarter. But only governance makes them trustworthy. In the next decade, 𝐭𝐡𝐞 𝐫𝐞𝐚𝐥 𝐜𝐨𝐦𝐩𝐞𝐭𝐢𝐭𝐢𝐯𝐞 𝐚𝐝𝐯𝐚𝐧𝐭𝐚𝐠𝐞 𝐰𝐨𝐧’𝐭 𝐛𝐞 𝐀𝐈 𝐜𝐚𝐩𝐚𝐛𝐢𝐥𝐢𝐭𝐲, 𝐢𝐭 𝐰𝐢𝐥𝐥 𝐛𝐞 𝐀𝐈 𝐢𝐧𝐭𝐞𝐠𝐫𝐢𝐭𝐲. #FinancialServices #AIGovernance #CyberSecurity

🌍📈 Surprising Relief in Global Financial Assets in 2023 – Global Wealth report out now. Read ➡️ Despite the backdrop of resilient economies and booming markets amid monetary tightening, global financial assets of private households saw impressive growth in 2023. With a surge of +7.6%, the losses of the previous year (-3.5%) were more than offset, reaching a total of EUR239trn by the end of the year. Yet, growth across the three major asset classes was uneven. Securities (+11.0%) and insurance/pensions (+6.2%) flourished due to the stock market boom and higher rates, while bank deposits saw a modest increase of +4.6%, one of the lowest in the past 20 years: 🔷 Bank Deposits: Fresh savings fell by -19.3% to EUR3.0trn, with banks receiving a mere EUR19bn, a dramatic -97.7% slump. 🔷 Securities: Inflows rose by +10.0%, with a notable shift towards bonds, especially in Western Europe (+84.3%). 🔷 Insurance/Pensions: Showed resilience with a global decline in fresh savings of just -4.9%. 🌐 Broad-Based Recovery: Unlike 2022, 2023 saw a widespread recovery in financial assets across most markets and regions. Notably, Asia and North America both grew by over +8%, with the US (+8.6%) outpacing China (+8.2%). 📉 Three Lost Years: Despite the growth, real financial assets worldwide only matched 2020 levels by the end of 2023. Regional disparities were significant, with Asia seeing a +26.3% increase from 2019, while Western Europe experienced a -4.3% decline. 🌍 Fragmenting World: The growth gap between emerging and advanced economies narrowed to just 2pps in 2023, a stark contrast to the 10pps+ gap seen until 2017. This shift underscores the evolving global economic landscape. 💡 Moderate Growth Ahead: Looking forward, we anticipate global financial assets to grow by +6.5% in 2024, driven by resilient economies and positive stock market trends. However, uncertainties around AI and sustainability, coupled with political volatility, suggest a modest growth rate of +4-5% over the next few years. https://lnkd.in/eCWZrXqK #FinancialGrowth #Securities #Insurance #Pensions #EconomicOutlook #FinancialAssets #Wealth #Ludonomics #AllianzTrade #Allianz

Financial Services Innovators Are Data-Driven, Cloud-Focused, and Customer-Centric Across Their Value Chains 💡 Banking and insurance cloud innovators are: 👨💻 Data-driven: 🔹 FS cloud Innovators actively use data to support their sales and marketing functions by recommending relevant products to their customers through targeted marketing campaigns. During customer onboarding, innovators use AI to process structured and unstructured data they obtain from their customers and maintain it in a database for future reference, enabling a seamless onboarding process. 🔹 On the banking side, innovators actively use data to identify and prevent fraudulent transactions, calculate customer credit scores to evaluate potential risks, streamline the process of loan approvals, and estimate the probability of loan defaults. 🔹 On the insurance side, innovators integrate traditional and third-party data for the underwriting process to help price policies better. Insurance innovators also actively leverage data during claims process to automate claims triage, identify fraudulent claims, and estimate damage value. ☁️ Cloud-focused: 🔹 They actively leverage APIs to facilitate collaboration between different teams during product development to identifyand integrate best practices. 🔹 Innovators actively use intelligent cloud-based CRM systems to manage customer data and effectively support their various business functions. They also use cloud-based systems to automate the customer onboarding process. 🔹 FS cloud innovators drive contact center modernization with the help of the cloud to enable faster resolution of issues and enhance upsell and cross-sell opportunities. 🙋♂️ Customer-centric: 🔹 Furthermore, cloud innovators have optimized KYC processes for onboarding to ensure that their customers have a seamless experience. 🔹 These innovators provide their customers with an omnichannel experience, ensuring they have straightforward and instantaneous access to their services. They offer their customers comprehensive, personalized financial advisory services in addition to their standard products and services. 🔹 Finally, these organizations leverage intelligent chatbots to assist their customers with the challenges they face during their financial journey. Gen AI helps innovators manage data, re-engineer processes, make realtime automated decisions, and drive simulations to delight customers. Some critical uses of generative AI across the value chain include market forecasting, tailored content marketing, personalized credit analysis in banking and premium calculations in insurance, fraud prevention and management, and intelligent chatbots and virtual assistants. Source: Capgemini - https://t.ly/A5cZC #Innovation #Fintech #Banking #OpenBanking #API #FinancialServices #Payments #Loans #Compliance #AI #Data #Cloud #GenAI