Fintech Industry Trends

What is the current level of AI adoption in insurance? That's what KPMG explores in this report. The 40-page document starts with a reminder of the technology itself, split between AI and Generative AI. Then it highlights several use-cases where these technologies could benefit the insurance value chain (e.g. actuarial processes, page 10) to automate routine tasks, enhance underwriting accuracy and personalize customer interactions. It also tackles the make or buy dilemma, unveiling that almost half of insurers have kicked-off internal initiatives so far, mixing business and tech employees (see page 13). KPMG also offers a framework to assess incumbents' maturity levels in these AI roadmaps (see page 19). And of course, there is a full section dedicated to risks c-level perceive from these AI technologies, starting with finding the right balance between technology and... people (starting at page 29). In case you don't have time to read the full report, I highly suggest you have a look at page 3 which summarizes key learnings. Basically: 1/ If insurers are running many initiatives, it takes time to switch from trial to production. 2/ Incumbents need to find the right balance in risk taking: innovation requires taking risks while regulation requires to meet standards. 3/ Key success factors stand in both data management and mastering HR challenges. ✍️ If the roadmap is not a surprise - enhance data management and balance HR & tech requirements - I found the overview quite interesting as it lists use-cases incumbents have already initiated and shares figures about where the market stand in terms of both adoption, perspectives and fears. This should help startups - and investors - spot opportunities and faster go-to-market strategies ! #insurance #insurtech #artificialintelligence

📢 For the past 18 months I have been serving on a Government Taskforce - looking at how we can supercharge Women-led *High Growth* Businesses (inc. a few trips to Number 10 Downing Street)... 📈 This builds on much of the great work already started by The Rose Review & Rose Review Board which looks at *all* women led businesses, and the valuable data collection led by the British Business Bank, British Private Equity & Venture Capital Association (BVCA), Diversity VC Level 20 and The Treasury with the Investing in Women Code. This Taskforce was specific to *High Growth* Women-Led Businesses - and was led by one - the indomitable Anne Boden. Anne founded Starling Bank in 2014 and has since scaled it to 3.6m customers, £353m in revenue last year and £195m in profit.* She truly embodies the potential of High-Growth Women-Led Businesses and we need 10,000x more Starlings in order to power our economy forward. Being on this Taskforce was not without its challenges as the topics we're tackling are so vast and complex. I wish we had the time and resources to do much more. However - today we launch our (92 page!) final report, including recommendations on how to break down barriers and support the economy. The key recommendations are: Recommendation 1: Investors should better monitor the proportion of funding they invest in female founded businesses. Recommendation 2: Firms should set their own voluntary targets for the number of women in senior investment professional roles and report against them on their websites. Recommendation 3: Increase signatories to the Investing in Women Code, particularly for private debt funds and Limited Partners, to boost investment in women-led enterprises. Recommendation 4: Drive inclusive behaviour in the investment ecosystem. The FCA should reduce the threshold for companies below 251+ employees to incorporate venture capital firms to drive greater diversity in the companies and, thus, their decision making. Recommendation 5: Roll out Female Founder Growth Boards across England. Recommendation 6: Inspire girls and women to become high-growth entrepreneurs. Recommendation 7: Improve data collection on the number of female founders. Thanks to my fellow Taskforcers ●     The Chair, Anne Boden MBE, founder of Starling Bank ●     June Angelides MBE: Investment Manager, Samos, and CEO and Founder, Mums in Tech ●     Judith Hartley: former CEO of British Patient Capital and British Business Investments, British Business Bank ●     Zandra Moore: CEO and Co-founder, Panintelligence ●     Deepali Nangia, Partner, Speedinvest and Co-founder Alma Angels ●     Jan Putnis: Partner, Slaughter and May ●     Angela Scott: Founder, TC BioPharm Ltd ●     Helen Steers: Partner, Pantheon ●     Sam Smith: Founder and former CEO at finnCap Cavendish Group Plc I couldn't have been part of this Taskforce without support from Matt Penneycard the team at Ada Ventures. 🙏 *Figures at at March 23. Link below.

But what if insurance worked more like Netflix? Netflix tracks your viewing behavior and adapts recommendations instantly. If insurance products adapting the same way, premiums adjusting dynamically to fitness levels, coverage expanding with life stages, benefits rebalancing as goals evolve. McKinsey estimates AI-led personalization could lift insurer revenues by 10–15%, while lowering claims costs through early risk detection. And The technology already exists. Wearables generate 250+ daily data points per user around heart rate, sleep, activity. PwC reports 63% of consumers are willing to share health data if it results in cheaper or more personalized premiums. And Personlaized premiums is not a distant reality. It can be achieved by: 𝟏. 𝐈𝐧𝐭𝐞𝐫𝐨𝐩𝐞𝐫𝐚𝐛𝐥𝐞 𝐝𝐚𝐭𝐚 𝐩𝐢𝐩𝐞𝐥𝐢𝐧𝐞𝐬 that allow secure ingestion of health and behavioral data at scale. 𝟐. 𝐑𝐞𝐠𝐮𝐥𝐚𝐭𝐨𝐫𝐲 𝐬𝐚𝐧𝐝𝐛𝐨𝐱𝐞𝐬 that encourage innovation while protecting privacy. 𝟑. 𝐀𝐈 𝐞𝐱𝐩𝐥𝐚𝐢𝐧𝐚𝐛𝐢𝐥𝐢𝐭𝐲 𝐟𝐫𝐚𝐦𝐞𝐰𝐨𝐫𝐤𝐬 to ensure transparent pricing and avoid hidden bias. 𝟒. 𝐄𝐜𝐨𝐬𝐲𝐬𝐭𝐞𝐦 𝐩𝐚𝐫𝐭𝐧𝐞𝐫𝐬𝐡𝐢𝐩𝐬 with health-tech, fintech, and wellness players to broaden value delivery. Insurance is likely evolve from a once-in-a-decade purchase to a living product. #DigitalIndia #Fintech #AI #technology #Fintech #AI #technology

Women-led teams make up nearly 14% of UK startups. But they receive just 2.4% of the £10M+ investment rounds. These stats don’t surprise me. But they still sting. The Startup Coalition’s latest report on funding for female founders is essential reading - not because it’s shocking, but because it confirms what so many of us already know, and have lived. As someone who became an entrepreneur in my 40s - while juggling motherhood, a mortgage, and a corporate career, I’ve seen the difference access to funding, networks, and belief can make. This report does something I think is vital: it goes beyond pointing out the problem, and lays out the structural barriers clearly - from investor bias and legal grey zones, to angel investment thresholds and childcare costs. What stood out to me most: The quiet toll that fundraising can take when you’re constantly questioned, underestimated, or simply overlooked. I’ve mentored many women who’ve faced this. Brilliant founders, building great businesses - but having to defend their ambition in rooms where their ideas are undervalued. Progress won’t happen by accident. It requires pressure, policy, and persistence. Let’s use this moment to push further and ensure the next generation of female founders doesn’t just survive the system, but reshapes it from the ground up.

𝟭 𝗶𝗻 𝟰 𝘃𝗲𝗻𝘁𝘂𝗿𝗲 𝗰𝗮𝗽𝗶𝘁𝗮𝗹𝗶𝘀𝘁𝘀 𝘁𝗵𝗶𝗻𝗸 𝘄𝗼𝗺𝗲𝗻’𝘀 𝗽𝗮𝗿𝘁𝗶𝗰𝗶𝗽𝗮𝘁𝗶𝗼𝗻 𝗶𝗻 𝗳𝗼𝘂𝗻𝗱𝗶𝗻𝗴 𝘁𝗲𝗮𝗺𝘀 𝗶𝘀 𝗼𝘃𝗲𝗿𝗿𝗮𝘁𝗲𝗱. 𝟭 𝗶𝗻 𝟭𝟬 𝘀𝗮𝘆 𝘁𝗵𝗲𝘆 𝗱𝗼𝗻’𝘁 𝘄𝗮𝗻𝘁 𝘁𝗼 𝗶𝗻𝘃𝗲𝘀𝘁 𝗶𝗻 𝘄𝗼𝗺𝗲𝗻. Together with Laura Koch and Elisabeth Berger (JKU - Institute for Entrepreneurship), I surveyed 361 international VCs using a randomized response technique to bypass social desirability bias. The results aren't unconscious bias. The results are open discrimination. And it’s personal. Some of the strongest startups I’ve seen at the University of Hohenheim were women-led, such as Holiroots or Viva la Faba. What a waste of potential. We knew gender bias existed in venture capital. Now we know how much — and where. 𝗪𝗵𝗮𝘁 𝗻𝗼𝘄? One recommendation from our findings that’s both practical and powerful: 👉 Increase the share of women in venture capital. Why it matters:  • Women VCs show significantly less bias.  • Diverse teams make better decisions.  • Mixed teams perform better. If we want fairer funding decisions, we must rethink who’s making them. 𝗟𝗲𝘁’𝘀 𝗻𝗼𝘁 𝗮𝘀𝗸 𝗶𝗳 𝘄𝗼𝗺𝗲𝗻 𝗮𝗿𝗲 “𝗶𝗻𝘃𝗲𝘀𝘁𝗮𝗯𝗹𝗲.” 𝗟𝗲𝘁’𝘀 𝗮𝘀𝗸 𝘄𝗵𝘆 𝘀𝗼𝗺𝗲 𝗶𝗻𝘃𝗲𝘀𝘁𝗼𝗿𝘀 𝘀𝘁𝗶𝗹𝗹 𝗮𝗿𝗲𝗻’𝘁. The paper is open access in Venture Capital—An International Journal of Entrepreneurial Finance. Feel free to share it or use it in teaching, workshops, or policy work. 📄 https://lnkd.in/eN4jfJQx

Latest research tells us that female tech founders, in advanced tech and AI sectors, need twice as much experience as their male counterparts to secure VC funding. They also need a minimum of 12 years of leadership experience to gain VC funding, versus the male average of nine. This is what we mean when we talk about a double standard and a very real gender funding gap. While I know the issue of female founders receiving less VC funding is not new, the latest data, reported in Startups.co.uk, shows little improvement. VC funding for tech startups has slowed, but AI investment remains strong. However, the gender funding gap is glaring, with female founders receiving just 2% of funding in 2023. As AI-focused companies attract record VC investment, the gap risks widening before it improves. Money talks, and it’s time for investors to properly interrogate why female founders receive far less of their funding while facing double the experience expectations of men. To break this cycle, we have to tackle unconscious bias and the lack of women in VC decision-making. Women founders also face smaller networks, less access to mentorship, fewer repeat funding opportunities. The UK Government’s £250m fund for female founders is a step forward, but AI’s rapid growth must not deepen these disparities. I’ll link the report in the comments, but I’d really love to hear from female founders and VCs on what would really move the dial to help close the gender funding gap. It certainly feels like we’re a long way off. Photo credit: Startups.co.uk

Key Findings from the 2025 State of #Fraud Report 🔸 Rising Fraud Incidents Across All Sectors: 60% of financial institutions and #fintechs reported an increase in fraud events targeting #consumer and business accounts in 2024. Fraud was predominantly digital, with 80% of events occurring on #online or #mobilebanking channels 🔸 Key Fraud Types: Credit card fraud, identity theft, and account takeover (ATO) #fraud were the most common types of fraud reported. 20% of enterprise #banks ranked check fraud as their most frequent fraud type. 🔸 Financial and Reputational Costs: 31% of organizations experienced fraud losses exceeding $1M in 2024. 73% ranked #reputational damage as the most severe consequence of fraud, followed closely by direct financial losses (72%) and loss of clients (72%). 🔸 Role of Organized Crime: 71% of fraud attempts were attributed to financial #criminals or fraud rings, marking a shift from first-party to third-party fraud. 🔸 Fraud #Detection and Prevention: 56% of financial organizations most commonly detected fraud at the transaction stage, while 33% identified it during onboarding. Real-time interdiction was conducted by only 47% of respondents, highlighting a gap in immediate fraud prevention. 🔸 Fraud Detection Trends: Inconsistent user #behavior (28%) and mismatched personal data (20%) were leading indicators of fraud attempts. Mid-market banks reported the highest incidence of fraud, with 56% facing over 1,000 fraud cases. 🔸 AI and Technology Adoption: 99% of organizations reported using AI in fraud prevention, with 93% agreeing that machine learning and #generativeAI will revolutionize detection capabilities. #AI was predominantly used for anomaly detection (59%) and explaining large datasets for #risk analysis (67%). 🔸 Fraud Prevention Investments: 93% of respondents indicated ongoing #investments in fraud prevention, with identity risk solutions being the most impactful (34%). Top technologies for 2025 include identity risk solutions (64%), document #verification software (49%), and voice/facial recognition systems (38%). 🔸 Regulatory Impact: 62% of organizations plan to increase fraud prevention investments in response to #regulatory scrutiny and potential #reimbursement requirements for fraud losses. Predictions for 2025: 🔆 Fraud will continue to rise, driven by increased availability of consumer data on the #darkweb 🔆 Financial institutions are expected to adopt #centralized platforms for fraud and identity risk management to enhance efficiency and reduce losses 🔆 Advanced AI tools and real-time #payments systems will remain key focus areas for fraud mitigation strategies. These findings emphasize the need for a multi-layered approach to fraud prevention, prioritizing identity verification, AI-driven analytics, and real-time interdiction

British Business Bank recently doubled its commitment to the Invest in Women Taskforce from £50m to £100m - and that alone is big news. But what I’m even happier to see is their newly announced £400m Investor Pathways Capital programme, launching in 2026. Why does this matter? Because this initiative focuses on building the pipeline of who gets to invest. For too long, venture capital has relied on closed networks and familiar faces. This programme will: • Deploy capital into small, early-stage funds • Help new investors build a track record • Back emerging talent, not just the usual suspects • Crucially, target at least 50% of investment towards female fund managers And we know what happens when women control capital: outcomes change. Capital flows differently. Diverse funders back diverse founders. For me, this is about changing the system from the inside out - making sure the next generation of investors reflects the future of the UK, not just its past. It’s a step towards the kind of inclusive, sustainable investment ecosystem we urgently need.

For those who've not already downloaded it, here's the link to the latest Gallagher Re Global #InsurTech Report. "The 2024 Global InsurTech report series explores the impact of #ArtificialIntelligence (#AI) on our industry, dissecting AI's functions and processes within the (re)#insurance value chain. This final report in the series will examine 'Claims', a process which begins with the first notice of loss, through validation, adjustments, approval, and then all the way to settlement and the transfer of funds to the customer. It is here that insurers fulfil their obligation to their clients in the event of an actual loss and given how fundamental claims are to the industry, this is an area where a (re)insurer can really demonstrate their worth. Getting the claims and settlement processes right can maximize the investments that (re)insurers are making elsewhere and create best-in-class customer engagement experiences. The benefits of this are not only felt externally, either; the pricing and underwriting process can also benefit from a clear and comprehensive view of claim and loss data, for example, to aid with capital allocation and forecasting. As per previous reports, we also spotlight key InsurTech companies, engage with industry thought leaders, and provide detailed insights into the latest InsurTech investment trends. Key findings for Q4: - Global InsurTech funding dropped 5.6% YoY, from USD4.51 billion in 2023 to USD4.25 billion in 2024 - Early-stage funding and average deal sizes were bright spots for 2024 - Global InsurTech funding halved QoQ, from USD1.38 billion in Q3'24 to USD688.24 million in Q4 2024 - AI centered InsurTechs accounted for 42.3% of deals in Q4'24 - Half of Q4'24 InsurTech deals involved InsurTechs with a focus on claims Detailed, insightful, and excellent as ever Andrew Johnston, Freddie Scarratt CC: Brea Charlie https://lnkd.in/eTzQWzrM

🔍 Insurance fraud is evolving—so should our strategies to fight it. Behavioral analytics is emerging as a game-changer in fraud detection. By combining machine learning, NLP, and data science, it helps insurers spot fraudulent patterns, identify anomalies, and mitigate risk—while upholding customer trust and ethical standards. Here’s what the infographic highlights: ✔️ Behavioral analytics detects unusual behavioral patterns in claims ✔️ Uses diverse data: transactional, contextual, and historical ✔️ Flags indicators like suspicious geolocations and device anomalies ✔️ Drives business impact by reducing financial loss and accelerating investigations ✔️ Promotes ethical AI through privacy, fairness, and human validation ✔️ Integrates seamlessly into existing insurance workflows In a world where fraudsters adapt quickly, leveraging intelligent analytics is no longer optional—it’s essential. What’s your take on AI in insurance? Let’s discuss in the comments. Don't miss upcoming insights on Digital Transformation 🔔 Activate the bell to stay up to date! And if you want to delve deeper, take a look at the DeltalogiX blog > https://bit.ly/4hDs9HU #InsuranceInnovation #FraudDetection #BehavioralAnalytics