Impact of AI on Financial Processes

AI isn’t just a technology shift — it’s a work shift. And in financial services, that shift is already underway. It starts small: automating tasks. Then it changes how entire jobs function. Eventually, it redefines entire departments. Here’s what that looks like in practice: 🔹 Step 1: AI transforms tasks AI works with you — helping professionals get more done, faster. A loan officer drafts approval notes instantly with AI. An underwriter summarizes 50-page claims files in seconds. A relationship manager personalizes client updates at scale. Most banks and insurers are here today — using AI as a productivity co-pilot. 🔹 Step 2: AI transforms jobs AI works for you — driving outcomes, not just efficiency. A claims agent auto-triages and settles low-risk cases. A KYC bot collects documents, flags risks, and pre-fills onboarding forms. A customer agent handles 70%+ of routine inquiries — end to end. This is where the job itself starts evolving. Less grunt work. More time for strategic judgment and exception handling. 🔹 Step 3: AI transforms functions Entire workflows become agent-led. This shifts how teams are designed. Contact centers turn into experience hubs. Loan ops becomes real-time decisioning. Compliance becomes continuous, not reactive. Role ratios change. Skillsets shift. Firms start hiring for orchestration, design, and oversight — not just execution. What does this mean for growth? Financial institutions can scale smarter — not just by adding headcount, but by rethinking how work happens altogether. AI isn’t replacing jobs. It’s redesigning them — one workflow at a time. And for those who lean in early, that’s a major edge.

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

AI and AI agents are poised to significantly impact Wall Street by automating various tasks, which could lead to job losses in several ways over the next five years: 1. **Algorithmic Trading:** AI-driven algorithms can execute trades at speeds and efficiencies far beyond human capabilities. As these algorithms become more sophisticated, the demand for traditional traders may decrease, as AI can optimize trading strategies, manage massive data inputs, and execute decisions almost instantaneously. 2. **Robo-Advising:** AI-powered robo-advisors can provide financial advice and portfolio management at a fraction of the cost of human advisors. This trend could lead to job reductions in sectors that provide investment advice, particularly for lower-net-worth individuals who might prefer cost-effective, automated solutions. 3. **Data Analysis and Research:** AI systems can process large datasets to generate insights more quickly and accurately than human analysts. This capability may reduce the need for human analysts in roles that involve routine data analysis and reporting. AI can detect patterns and generate predictive models, which could suffice for generating actionable intelligence. 4. **Risk Management:** AI can enhance risk management processes by detecting potential issues and correlations unseen by humans. As AI systems become more adept at assessing risks and making recommendations, there may be less need for large teams in compliance and risk management roles. 5. **Operational Efficiency:** AI can automate routine back-office tasks such as transaction processing, compliance checks, and customer support. This can result in decreased demand for personnel who perform administrative and support roles. 6. **Cost Reduction Pressures:** As AI technologies become more widespread, financial firms may feel pressured to adopt these solutions in order to remain competitive and reduce costs. This drive for efficiency could lead to streamlining and reductions in workforce.

AI just made its move into financial services. Anthropic announced a new tailored offering: Claude for Financial Services. Let’s break it down. • Claude connects directly to your internal data stack: Snowflake, Databricks, S&P, PitchBook, FactSet, and more. • It’s not a consumer chatbot. It’s a task-specific analyst, tuned for high-stakes environment. • It doesn’t train on your data. Privacy and compliance are foundational. • Oh yeah, and it can do Monte Carlo simulations. Where it creates value: • Investment teams can analyze portfolios, trends, and risk exposures in real time, without toggling across 12 dashboards or waiting on data prep. • Compliance and audit functions can use Claude to summarize regulatory updates, track adherence, and flag anomalies, before the next quarterly fire drill. • Client-facing teams can generate custom pitch decks, scenario models, and account insights on demand, without pulling an associate off a deliverable.    For CFOs • Increase visibility into financial drivers by asking natural-language questions across systems and models • Pressure-test scenarios in real time using up-to-date financial and macro inputs • Generate investor-ready insights faster and more consistently For FP&A Transformation leaders • Automate recurring analysis cycles such as forecast variance, budget rollups, and board package creation • Embed Claude into planning workflows to assist with driver modeling, commentary, and contextualization • Scale insight delivery without increasing headcount For GenAI Transformation leads • Operationalize AI within high-stakes workflows without reengineering existing systems • Launch proof-of-concepts with measurable productivity impact in under 90 days • Build a business case grounded in time saved, accuracy improved, and risk reduced Real results: • AIG accelerated underwriting by 80% while increasing data quality from 75% to 90% • Norway’s NBIM saved over 213,000 hours in a single deployment with a 20% productivity lift across finance teams If you’re leading a team inside a Fortune 500 and wondering where to start: Identify high-friction, high-repetition tasks in finance, ops, or risk. Don’t wait for a firm-wide transformation plan. Start small with one workflow Claude could automate or accelerate. Pilot. Measure. Expand. ----------------------- Follow me for GenAI Transformation, Training, and News.

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

At first glance, the numbers might seem modest - we're talking about cost base reductions ranging from 7% to 30% across different functions. But here's where it gets interesting: in financial services, we're dealing with massive cost bases. Let's break this down: Take customer service, showing the highest potential reduction at 20-30%. For a major bank spending $1 billion annually on customer service operations (not uncommon for large institutions), we're looking at $200-300 million in annual savings. From a single function. Even the seemingly modest 7-12% reduction in HR costs can translate to tens of millions for large financial institutions. And this is projected to happen in just 2-3 years - not some distant future. The most striking insight from Bain & Company's analysis is how generative AI's impact varies across functions: Customer-facing operations see the biggest gains (20-30%) Risk and compliance follows closely (15-25%) Middle/back office and marketing share similar ranges (10-15%) IT shows interesting variance (8-20%) HR, while lowest, still promises significant savings (7-12%) What's particularly fascinating is the concentration of higher savings in areas requiring complex decision-making and customer interaction. This suggests AI isn't just automating simple tasks - it's augmenting high-value human activities.

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.  

I’ve got a question for financial advisors: is AI ready to make you money while making you and your clients happier?    We can start to answer that question thanks to a fascinating new paper by Erik Brynjolfsson, Danielle Li and Lindsey Raymond which shows the impact of AI on a call center. They found that an AI assistant increases worker productivity by 15% on average, with the biggest effects accruing to the least experienced.   What might this mean for an advisor? Here are some numbers to play with:   1) If AI can just slightly increase your productivity, and that only gave you the bandwidth for one more $2M client, that’s another ~$20k per year.    2) If AI can just slightly increase the satisfaction of your existing clients, and perhaps get one more successful referral of $2M, that’s another $20k in annual income.  In the call center study, for instance, customers showed a significant spike in satisfaction post-AI, at least among less skilled agents.   3) AI might even make you happier at work, as you can delegate the least fun work to it. This is evidenced by a big reduction in attrition among agents using AI.   It’s worth noting that my estimates are deliberately low. I think AI will have a far larger impact on the financials and job satisfaction of the typical advisor. The only challenge is that our industry, at least according to a recent survey by Anthropic, is far behind. It’s time to catch up. https://lnkd.in/gZpTH2bt