How AI Drives Growth in Finance

Fintech isn’t dead.  It’s at a new beginning 🚀     Tech in financial services adapts/ creates large opportunities in every product cycle.  We are just at the beginning with AI. 🖥 Product cycle: PC/Internet era Fintech wave 1: “put it on a website”  👉 LendingClub started to make loans on the internet (vs. in bank branches) 📱 Product cycle: Mobile  Fintech wave 2: Mobile/Full Stack 👉 Chime built full stack bank w/ “get your paycheck early” wedge, Robinhood built free mobile trading w/ fractional shares ☁ Product cycle: Cloud  Fintech wave 3: "Every company is a fintech" 👉 Every layer of the stack “as a service” so companies could monetize/retain customers with fintech (Moov for payments, Sardine for fraud etc.).  🧠 NOW Product cycle: AI Wave 4: “AI inside” (tm Intel:) — we are just at the beginning but will include: 1️⃣ Labor becomes software:  Financial institutions have many of the white collar jobs that will soon have co-pilots & agents (compliance officers, insurance claims adjusters etc.) 2️⃣ Enterprise customers WILL rip and replace legacy software: Banks are full of SW (Black Knight, FIS, FiServ) built 20-30+ years ago.  The AI driven newcos are 10x better.  Banks/insurance cos are already rip/replacing. 3️⃣ Sales/marketing/finance: FIs/Insurance companies have huge sales & marketing teams, large financial back offices.  This labor spend is an opportunity for AI too. 4️⃣ Default global: AI companies cross borders & span multiple industries even earlier in their lifecycles.  They will require more cross border extensibility, flexibility, speed.  New infra cos will be built to support.  Startups from Waves 1,2,3 are best suited (vs. incumbents) to adapt quickly and are "adding AI". New companies are emerging fast. Fintech may need a new name, but the concepts/ investment opportunities are more powerful than ever.  (requisite message from our compliance team: The above is not intended to be investment advise. Please visit a16z.com/ investment-list for a full list of a16z portfolio companies)

Your AI Copilot Isn’t Replacing You — It’s Promoting You 🚀 Remember when Excel first landed in offices? The people who mastered it didn’t get replaced. They got promoted. We’re living through that moment again—only now, it’s with AI. Your AI copilot—whether it’s ChatGPT, Claude, or a custom tool—isn’t here to take your job. It’s here to multiply your impact. Take my week, for example: 🧠 Summarized a 20-page whitepaper in 90 seconds ✍️ Drafted 3 client emails—in my voice, not some generic template 💡 Reframed an investor pitch deck using insights from a different industry None of that replaced me. It amplified me. And what I’m seeing personally? It’s happening at scale in fintech. AI in Fintech: Quiet Revolution, Massive Impact The same AI that’s helping me move faster is now transforming how fintech operates — not someday, but right now. 1. Smarter Risk Management ↳ AI flags fraud in real time, predicts loan defaults before they happen. ↳ JPMorgan cut false positives in fraud detection by 40%. 2. Personalization That Actually Works ↳ Hyper-relevant offers, proactive chatbots, AI-driven wealth advisors. ↳ Result? 5–10% uplift in revenue through more engaged customers. 3. Less Ops, More Innovation ↳ KYC checks, compliance reviews, documentation—automated. ↳ Your team spends less time chasing files, more time chasing growth. PwC predicts over $1 trillion in AI-driven value for financial services by 2030. Deloitte shows major gains in both cost reduction and revenue growth. This isn’t just an upgrade. It’s a shift in how fintech runs. At Netevia, we are already making this a reality. We are currently integrating AI into two core fintech processes: risk assessment and underwriting. These processes are being enhanced with AI to improve accuracy, speed, and decision-making. This integration enables our teams to focus on higher-level insights while AI handles complexity at scale. 💬 If you treat AI as competition, you’ll get left behind. 💡 If you treat it as a collaborator, you’ll move ahead. So let’s make this real: How are you using AI as your copilot? Drop your favorite use case in the comments—let’s crowdsource the next fintech playbook. #AI #Fintech #FutureOfWork #ArtificialIntelligence #ChatGPT #Productivity #CareerGrowth #BankingInnovation

5 Ways AI Is Reshaping Finance Right Now (Banks and financial firms are using AI to cut risks, boost profits, and make smarter decisions.) 1. Fraud Detection ↳ AI scans millions of transactions in real-time, flagging suspicious activity instantly. Banks using AI for fraud prevention have cut losses by 50%. 2. Algorithmic Trading ↳ AI-driven systems execute 60%+ of stock trades, reacting to market shifts in milliseconds. This improves accuracy, reduces human error, and maximizes returns. 3. Credit Risk Assessment ↳ AI-powered credit scoring analyzes thousands of data points, helping banks approve loans 30% faster while reducing default risk. 4. Personalized Banking ↳ AI chatbots and virtual assistants handle 80% of routine banking questions, cutting wait times and improving customer satisfaction. 5. Wealth Management ↳ AI-driven robo-advisors manage over $1 trillion in assets, offering smart investment strategies with lower fees. AI is transforming finance - are you using it to stay ahead? ______________________ AI Consultant, Course Creator & Keynote Speaker Follow Ashley Gross for more about AI

AI's $2.4T Banking Revolution: The Hidden Story Behind 200,000 Job Cuts Here's what's really happening in banking's AI transformation → A deep dive that shocked me: The Scale is Staggering: → $770B value creation in Risk & Legal alone → $642B in Corporate Banking → $612B in Retail Banking But here's the fascinating part ↳ While headlines scream about 200k job cuts, the real story is about value creation: • Banks project 12-17% higher profits by 2027 • 54% of jobs will transform (not disappear) • 80% of banks expect 5%+ productivity surge The Hidden Pattern I Found 🔍 ↳ Back office automation isn't the end game ↳ Banks are using AI for value CREATION, not just cost-cutting ↳ JPMorgan's AI chief confirms: "AI is augmenting, not replacing" The Most Surprising Discovery: Risk & Legal functions → Highest AI value potential This suggests the real revolution isn't in customer service, but in the complex decision-making backbone of banking. Key Insight: We're witnessing the largest transformation of financial services since the 2008 crisis, but this time it's about building value, not just surviving. 🎯 My Prediction: Banks that view this as a transformation opportunity (not just cost-cutting) will capture the lion's share of the $2.4T value creation. 🔥 Want more breakdowns like this? Follow along for insights on: → Building with AI at scale → AI go-to-market playbooks → AI growth tactics that convert → AI product strategy that actually works → Large Language Model implementation Happy Sunday! #AI #Banking #FinTech #Innovation #DigitalTransformation #FutureOfWork

#ArtificialIntelligence in #Banking industry While the buzz around AI and GenAI is widespread, questions persist about realizing AI's value, the impact of reimagining enterprises with AI, and the tangible ROI from AI investments. In the financial services sector, the success of AI-led transformations in banks hinges on balancing immediate financial gains with establishing enduring AI capabilities. By crafting a business strategy with AI at its core and selecting specific domains for AI transformation, banks can drive value by scaling up transformations and leveraging reusable components across various domains. Capturing value from AI transformations requires a fundamental rewiring of how a company operates. This involves 6 critical enterprise capabilities: - A business-led #digital road map - #Talent with the right skills - A fit-for-purpose #operatingmodel - #Technology that’s easy for teams to use - #Data that’s continually enriched and easily accessible across the enterprise - Adoption and scaling of digital solutions While some banks are still experimenting with AI, there are few banks that are successful in AI typically excel in four key areas: 1. Establishing a bold, organization-wide #vision for AI's potential value. 2. Anchoring transformations in #businessvalue by revamping entire domains, processes, and customer journeys rather than focusing solely on narrow use cases. 3. Developing a robust suite of #AI capabilities supported by multi-agent systems. 4. Ensuring sustained value and scalability by implementing critical enablers for AI transformation. Some noteworthy use cases that have been deployed include: - A major bank leveraging AI enterprise-wide to enhance customer and employee experiences, drive efficiency, and increase revenue. - Utilizing AI to provide personalized financial guidance for customers' investments and financial planning. - Using AI to predict potential loan defaults and proactively support clients. - Leveraging GenAI to enhance software developers' productivity by 40% in a regional bank. - Implementing AI in a multiyear transformation to enhance performance and deliver analytics at scale, focusing on hyper-personalization and customer cross-selling. AI has the potential to revolutionize business operations, but successful adoption requires more than mere experimentation. While only a few banks currently derive significant value from AI, more institutions could follow suit in the coming years. McKinsey & Company's article offers a #blueprint to guide financial services leaders in unlocking substantial AI value across their enterprises. p.s. Link to the full article in the comments.

Pleased to share the result of a groundbreaking study I participated recently - "AI Takes Center Stage: Survey Reveals Financial Industry’s Top Trends for 2024" by Kevin Levitt at NVIDIA.   Here are some key insights:   ✅ 91% of financial services companies are either assessing or already using AI to drive innovation, improve efficiency, and enhance customer experiences. ✅ Top AI Use Cases in Financial Services: Portfolio optimization Fraud detection Risk management Generative AI gaining popularity for uncovering new efficiencies. ✅ 55% actively seeking generative AI workflows, with applications ranging from marketing to synthetic data generation. ✅ AI impact across departments: Operations Risk and compliance Marketing ✅ AI is delivering results with 43% reporting improved operational efficiency and 42% gaining a competitive advantage. ✅ Data-related challenges now take the spotlight, including privacy, sovereignty, and scattered global data. ✅ Despite challenges, 97% of companies plan to invest more in AI technologies. Focus areas include identifying additional use cases, optimizing workflows, and increasing infrastructure spending. ✅ 86% report a positive impact on revenue, 82% note reduced costs, and 51% strongly agree that AI is crucial for future success. ✅ To build impactful AI, financial institutions are prioritizing comprehensive AI platforms, collaborative environments, and high-yield use cases.   Download the Full Report: "State of AI in Financial Services: 2024 Trends" for deeper insights and results. Let's embrace the future of finance with AI!   #AITrends #GenerativeAI #FinancialServices #FinTech #CEOs #boardofdirectors   Link to the full report: https://lnkd.in/g3K5yUNV   Subscribe to #CXOSpice newsletter (https://lnkd.in/gy2RJ9xg) and #CXOSpice Youtube channel (https://lnkd.in/gnMc-Vpj) and tune in for the upcoming blog on “Pioneering Women Leadership in Tech – A Journey Through Innovation”. We will be featuring Splunk on "Resilient Customer Experience" in the upcoming episode.