Peer-To-Peer Lending Models

#fintech has revolutionized #lending not only via the what (access), but also via the how (process) and platforms have played a big role. Let’s take a look. Lending done the traditional way is balance sheet-based and implies a direct relationship. However, limitations such as complex underwriting, bureaucratic processes, inflexibility and a lack of customization have long made the case for alternatives. The rise of platforms has changed everything. China’s SuperApps have led the way and although the authorities have over the past years cracked down on the model, it’s worth having a look. Ant Financial’s lending arm – called Credittech – contributed at its peak in 2020 almost 40% of Ant’s revenues. The model ran on minimal credit-risk taking with 98% of lending either securitized or underwritten by (100) partner banks. Credittech consisted of 3 business lines: 1. Huabei (translated Spend) — Small-ticket consumer credit aimed at daily expenses — Launched in 2014 as a virtual credit card — Main target group: young Chinese with consumption potential but limited credit history — Instant credit underwriting based on platform data — In essence, a Chinese BNPL version with two variations: 1) an interest-free option for up to 40 days repayment after purchase 2) monthly instalments between 3 and 12 months 2. Jiebei (translated Borrow) — Launched one year after Huabei (2015), targeting larger tickets — Short-term, consumer unsecured lending — Requirement for previous credit history with either Huabei or the Ant platform — Instant credit underwriting and disbursement to the customers’ Alipay account (or to connected cards) — Repayment via 3-12 month installments 3. Mybank (MY is short for mayi, which translates as Ant): — An Ant Financial digital only bank targeting small businesses — Focus on servicing large volumes of small-ticket loans via #technology: big data, automation, standardization, and Artificial Intelligence (AI) — Data-driven underwriting (assessment of more than 3,000 variables) — Due to the lack of credit history #data or collateral the bulk of the credit decision is made based on repayment data from e-commerce platforms, online customer profiles, smartphone payments and other available records (local government, insurance) — 3-1-0 lending model: borrowers can complete their online loan application in 3 minutes, obtain approval in 1 second, with 0 human interactions. — Profitable business model via high-approval rates, low defaults rates (∼1%) and lower operational costs — In 2020 MYbank accounted for 50% of the SME market in China, with 78% being first-time borrowers and 40% female-run SMEs. Technology, the abundance of data, access to both sellers and buyers and market size and leverage, make platform models uniquely positioned to cut the lending Gordian Knot. Opinions: my own, Graphic sources: World Bank, Economist Intelligence Unit, BFA Global LP

𝗟𝗼𝗮𝗻 𝗖𝗼𝘃𝗲𝗻𝗮𝗻𝘁 𝗖𝗼𝗺𝗽𝗹𝗶𝗮𝗻𝗰𝗲: 𝗧𝗵𝗲 𝗚𝗿𝗲𝘆 𝗭𝗼𝗻𝗲 𝗧𝗵𝗮𝘁 𝗞𝗲𝗲𝗽𝘀 𝗟𝗲𝗻𝗱𝗲𝗿𝘀 𝗮𝗻𝗱 𝗕𝗼𝗿𝗿𝗼𝘄𝗲𝗿𝘀 𝗔𝘄𝗮𝗸𝗲 𝗮𝘁 𝗡𝗶𝗴𝗵𝘁 A borrower misses their EBITDA covenant by just 2%. A supply chain glitch, nothing more. But the lender notices a breach. The consultant gets the call. What follows? A waiver? A renegotiation? A technical default? This is the world of loan covenant compliance—where small numbers carry big consequences, and every decision balances on trust, timing, and interpretation. The Tug of War Behind the Numbers If you're a banker, you’re walking the fine line between relationship manager and risk officer. Do you protect the portfolio? Or preserve the client? If you're the borrower, covenants can feel like tripwires. You hit a strategic hiccup or reinvest for growth, and suddenly, you’re facing potential default—despite running a fundamentally sound business. If you're the loan consultant, you’re the bridge between calm and crisis. One word—“material”—can mean the difference between waiver and war. Why the Grey Area Feels So Personal Terms like “best efforts” or “material adverse change” are ambiguous by design. They protect both parties... until they don’t. Covenant breaches are rarely just about numbers. They're about reputation, judgment calls, and fear of triggering the domino effect. Lenders fear seeming inflexible. Borrowers fear being misunderstood. Consultants fear being blamed when things go south. Beyond compliance, it's a trust test where empathy, ego, and economics intersect. How to Survive the Fog a. Prevention is stronger than cure Define everything clearly at the loan structuring stage. Don’t wait for a breach to interpret terms. b. Talk early. Talk often. Silence is the enemy. Borrowers: flag risks early. Lenders: ask questions, not just forensics. Consultants: create safe space for honest dialogue. c. Bring in a neutral voice. Legal advisors, auditors, or independent consultants can help everyone take a breath and find ground. d. Design with realism. In volatile industries, consider buffer thresholds, covenant-lite terms, or periodic covenant resets. The Conversation We Rarely Have Loan compliance is never just a legal clause. It’s a lens into how we share power, shoulder risk, and maintain relationships during tension. If you’ve ever had to explain to a founder why a 3% miss triggered a lender response... If you’ve sat with a banker weighing risk versus reputation... Or if you’ve been the middleman trying to keep both sides aligned... You know that covenants are not just about control—they’re about trust. And trust, once shaken, is rarely the same. Your Turn Navigating covenant compliance grey areas can be tough. Have you seen a minor breach escalate or de-escalate successfully? Let’s open this up. Real experiences help all of us navigate better. #LoanCovenants #CorporateLending #RiskManagement #DebtAdvisory #FinancialConsulting #PradeepKumarGuptaa

Access to Credit: The Missing Piece Half of Filipino adults now have financial accounts, but only one in ten can borrow from a bank. Because the system was never designed for them. 📊 Data shows the divide: ● Credit-to-GDP: The Philippines sits at 53%, far behind Thailand (94%) and Malaysia (125%) — World Bank, 2024. ● Formal borrowing: Only 11% of Filipino adults borrow from formal institutions — World Bank Findex, 2024. ● MSME financing: MSMEs make up 99% of businesses, yet get just 4.5% of total bank loans — BSP, 2024. ☁ The problem isn’t demand; it’s risk and cost. Traditional banks lend where credit is easy to measure: large corporates, salaried workers, collateral-backed clients. Entrepreneurs, self-employed professionals, and small merchants — even those with healthy cash flow — remain invisible to legacy scorecards. This is a problem when so much of our commerce is dependent on the growth of small and medium enterprises. But the model is starting to shift. ☀ Digital banking and embedded finance players are proving that data can be collateral. Platforms utilizing embedded banking, such as Shopee, Lazada, and GCash, are already using real-time cash-flow data to underwrite MSME and BNPL loans. On these platforms, defaulting means more than missed payments. It can mean losing access to the very marketplace where your income flows. It’s a new kind of trust equation: credit tied to behavior, not paperwork. 🔍 The implications ➀ Legacy risk models are exclusion engines. By design, they favor those who already have credit and filter out everyone else. ➁ Embedded and digital lenders are rewriting the rules. By using alternative data, they can extend loans responsibly where traditional systems can’t. ➂ Regulation must evolve with innovation. Open banking, credit data portability, and risk-sharing programs will determine how fast this shift scales. ⚙️ The call to action ➊ Modernize risk models. Move from collateral-based lending to data-driven confidence. ➋ Empower MSMEs. Mandate fair access and incentives for banks to lend to productive small enterprises. ➌ Build the bridge between access and growth. Credit is not a by-product of inclusion, it powers it. 💡 Financial inclusion without credit is like building roads that lead nowhere. A bank account opens the way, but credit creates opportunity and growth. #FinancialInclusion #Lending #MSME #Philippines #FutureOfBanking 🔗 Sources: World Bank 2024; World Bank Findex 2024; BSP MSME Credit Report 2024; IFC MSME Banking in the Digital Era 2024; TechCollectiveSEA 2025; Visa SEA Embedded Finance Report 2024

Govern to Grow: Scaling AI the Right Way    Speed or safety? In the financial sector’s AI journey, that’s a false choice. I’ve seen this trade-off surface time and again with clients over the past few years. The truth is simple: you need both.   Here is one business Use Case & a Success Story. Imagine a loan lending team eager to harness AI agents to speed up loan approvals. Their goal? Eliminate delays caused by the manual review of bank statements. But there’s another side to the story. The risk and compliance teams are understandably cautious. With tightening Model Risk Management (MRM) guidelines and growing regulatory scrutiny around AI, commercial banks are facing a critical challenge: How can we accelerate innovation without compromising control?   Here’s how we have partnered with Dataiku to help our clients answer this very question!   The lending team used modular AI agents built with Dataiku’s Agent tools to design a fast, consistent verification process: 1. Ingestion Agents securely downloaded statements 2. Preprocessing Agents extracted key variables 3. Normalization Agents standardized data for analysis 4. Verification Agent made eligibility decisions and triggered downstream actions   The results? - Loan decisions in under 24 hours - <30 min for statement verification - 95%+ data accuracy - 5x more applications processed daily   The real breakthrough came when the compliance team leveraged our solution powered by Dataiku’s Govern Node to achieve full-spectrum governance validation. The framework aligned seamlessly with five key risk domains: strategic, operational, compliance, reputational, and financial, ensuring robust oversight without slowing innovation.   What stood out was the structure: 1. Executive Summary of model purpose, stakeholders, deployment status 2. Technical Screen showing usage restrictions, dependencies, and data lineage 3. Governance Dashboard tracking validation dates, issue logs, monitoring frequency, and action plans   What used to feel like a tug-of-war between innovation and oversight became a shared system that supported both. Not just finance, across sectors, we’re seeing this shift: governance is no longer a roadblock to innovation, it’s an enabler. Would love to hear your experiences. Florian Douetteau Elizabeth (Taye) Mohler (she/her) Will Nowak Brian Power Jonny Orton

Diversification Feels Great—Until the Market Drops Everyone believes in diversification. It’s the bedrock of modern portfolio theory. Mix uncorrelated assets. Reduce volatility. Improve outcomes. Clean math. Solid concept. But here’s the problem: diversification often vanishes when you need it most. In calm markets, alternatives behave nicely. Low correlation. Smooth returns. A little friction here and there, but mostly predictable. Then a shock hits—like 2008, 2020, or 2022—and everything moves together. Take a look at Figure 2.5. It shows downside correlation between private market strategies and public markets. The correlation levels spike during market stress, especially for strategies like private equity, venture, and even parts of real estate. These are the exact moments when diversification is supposed to protect you. Instead, what you get is convergence. That’s not a flaw in the model. It’s a flaw in how we interpret correlation. Because correlations are not fixed. They are conditional. When liquidity dries up, when markets panic, when buyers disappear—assets that normally move independently start falling in sync. Correlation goes up. Diversification goes down. And portfolios that looked balanced start to break. This is where many investors get blindsided. They think: “I’ve got private markets, so I’m diversified.” But what they really have is a portfolio that works well in smooth conditions and underperforms in drawdowns—the exact moment they can’t afford it. So what’s the solution? Start measuring diversification in stress, not just in averages. Look at: Downside correlation, not just 10-year rolling Distribution behavior during market shocks (see Figure 3.3) Sector overlap and common drivers of returns (see Figure 3.1) Ask not just “what do I own?”—but “what happens when everything drops 20%?” If you haven’t tested that, you don’t really know your portfolio. Diversification isn’t just about adding more funds. It’s about behavior under pressure. And in that moment, correlation math gets real. For more see our Nomura CIO Corner: https://lnkd.in/e4TCax_g #DownsideRisk #PortfolioStrategy #DiversificationTruth #PrivateMarkets #CIOInsights

Non-Performing Loans Don’t Lie—They Reflect Our Lending Culture I still remember a moment from years back at Mkombozi Commercial Bank. A supervisor looked at a file, shook his head, and said: “Paul, this loan didn’t fail because the client was weak. It failed because we didn’t follow through.” That stuck with me. Because over the years, I’ve seen the same pattern repeat—across banks, teams, and markets. In my 10+ years of banking and microfinance, I’ve learned one thing the hard way: 👉 NPLs are not just about clients failing to pay. They’re often about how we, as bankers, choose to lend, monitor, and engage… Let’s break it down clearly: ✅ 1. NPLs Are Mirrors, Not Just Metrics They reflect our lending habits, our assumptions, and sometimes… our shortcuts. If we approve loans without deep understanding or follow-up, the risk begins there. ✅ 2. Weak Monitoring = Silent Defaults A loan that’s disbursed and forgotten is a loan waiting to default. Regular check-ins, business reviews, and emotional connection matter more than we think. ✅ 3. Cultural Red Flags in Lending 👉🏻Approving loans just to hit monthly targets 👉🏻 Ignoring early warning signs like missed calls or delayed payments 👉🏻 Over-relying on collateral instead of understanding the client’s business 👉🏻No post-disbursement engagement—just “wait and see” 👉🏻 Lack of borrower education or financial literacy support ✅ 4. What a Healthy Lending Culture Looks Like 👉🏻Lending based on character, capacity, and relationship—not just paperwork 👉🏻Regular follow-ups with empathy, not pressure 👉🏻 Educating clients before and after disbursement 👉🏻Treating recovery as a chance to rebuild—not just collect 👉🏻 Celebrating clients who recover and grow not just those who pay on time ✅ 5. Relationship Banking Is the Cure Strong relationships reduce NPLs. When clients feel seen, heard, and supported—they speak up before things go wrong. ✅ 6. Time to Reflect, Not Just Recover Before we blame the borrower, let’s ask: 👉🏻Did we educate them well? 👉🏻Did we monitor consistently? 👉🏻Did we build a relationship or just a transactions ✍️ Final Advice to Relationship Managers, Officers, Recovery Teams and Credit Analysts: ✅ Don’t wait for default—engage early ✅ Track soft declines and follow up with care ✅ Blend data with emotion—know your client’s reality ✅ Educate before you escalate ✅ Treat recovery as a second chance, not a punishment ✅ Build trust, not just targets ✍️Let’s build a lending culture that prioritizes wisdom, empathy, and sustainability. Because numbers don’t lie—but they do speak. Loudly. Found this insightful?,Please like, comment and repost so others can learn Paul Chengula 📞 0714 260266 |0769 218125 📧 pauloignaschengula@gmail.com Tanzania

A conversation with a retail investor last week reminded me how counterintuitive investing really is. He asked: “If I can handle the risk, why would I ever choose a lower-return asset?” Fair question. I mean, if one strategy offers a 12% expected return and another offers 6%, why pick the 6% one? Bigger return = better option, right? Not necessarily. What matters is not just the headline return, but also how efficiently that return is generated. Take two strategies: • Strategy A: 12% return, 18% volatility • Strategy B: 6% return, 6% volatility At first glance, A wins. But B only takes one-third of the risk. That means you could hold 3x as much of B and still take the same total risk as A. Now the comparison becomes: • A = 12% return at 18% risk • 3x B = 18% return at 18% risk Same risk. Higher expected return. Now we’re finally comparing apples to apples. That’s the core idea behind risk-adjusted returns, and why professional investors focus so much on the Sharpe ratio: return per unit of risk. Of course, I’m simplifying. Volatility isn’t the full picture of risk, leverage isn’t free, and historical Sharpes don’t hold perfectly going forward. Still, it has big implications: • 100% equities may not be the most efficient portfolio - even if your goal is high returns • Portfolio construction and position sizing matter at least as much as asset selection alone • Diversification is not just about reducing risk - it can improve returns too • Return and risk are linked, but they are not the same decision: choosing the most efficient portfolio first, then sizing it to the risk you actually want, may be better than simply selecting the asset with the highest expected return • Leverage is not automatically more risky than concentration - a modestly levered diversified portfolio can be less risky than an unlevered concentrated one And maybe a more actionable takeaway for retail investors: Spend less time asking which asset has the highest expected return, and more time asking how each asset changes the risk and efficiency of the overall portfolio. #assetallocation #portfoliomanagement #portfolioconstruction #retailinvestors

The Case for Funds of Funds, Pt. 2: Diversification (and Access) 💡 This week, we're covering the benefits of the humble fund of funds. Yesterday, we spoke about benefits to simplification (and access). Today, let's move on to the topic of diversification - where we think that a FoF shines across three parameters: First, there is manager diversification. As the name implies, a FoF invests in a number of underlying managers (typically somewhere between 8 and 16, in my experience). The GP managing the FoF typically attempts to combine those underlying managers in a way that adds value to the overall portfolio. For example, rather than investing in ten generalist managers, they invest in a number of specialized managers that individually would be more risky but taken together offset their underlying risks. They might also want to add managers that have different ways of generating returns, i.e. from your pure-play buyout manager in a certain industry to managers focusing on turnarounds and special situations. Secondly, there is risk diversification. Take some of those specialized managers that we just mentioned. Yes, such a manager, if they do well, is likely do perform better than your diversified generalist megafund. But things can go the other way, too, so if you are committing to 3-4 funds per year, betting one of your tickets on such a manager might be overly risky. A FoF can alleviate that problem, providing investors with diversified access to such specialized GPs without incurring outsized single manager risk. Taken together, manager and risk diversification also translate into access-related benefits. In my last family office job, we met numerous of those high-performing, but also highly concentrated GPs. With 3-4 tickets per year, taking a bet on such a GP would’ve been too much of a concentration risk. However, we still saw benefits in this approach, and instead opted for a FoF to access those funds and their expected performance potential. Third and last, there’s time diversification. While not the case for every FoF, many FoFs spread their commitments to GPs over 12-36 months (i.e. 1-3 vintage years). Those underlying managers also have investment periods of 3-5 years. Assuming our FoF invests in 12 managers over 3 years, and our underlying managers invest in 10-12 companies, our single commitment becomes a portfolio of 120-144 companies built over 7-8 calendar years. This diversification extends further as you invest in another fund of funds in subsequent years. However, investors should be mindful of overdiversification. If your fees are very low (think a global stock market ETF), you’d gladly pay a few basis points more to lower your risk while still generating performance similar to your desired benchmark. However, in the world of alternative assets, where fees are still measured in percents rather than basis points, you should be mindful of how incremental (over)diversification might negatively affect your performance.

Reflecting on PHOENIXUS’ latest Building Our Financial Futures session, led by the insightful Schutz Lee, it’s clear that the lessons on portfolio diversification, asset allocation & rebalancing are essential tools for women, especially as we prepare for the realities of longer life expectancies, wealth transfers & changing market conditions. Schutz’s guidance helped us navigate these complex concepts, highlighting that portfolio diversification—spreading investments across various asset classes—is the foundation of a resilient financial strategy. By doing so, we mitigate risk & ensure that our portfolios are not overly reliant on any one market or sector. This approach becomes even more crucial for women, who often outlive men & find themselves managing wealth not only for themselves but for our families. In exploring asset allocation, which is all about determining the right mix of investments to align with our individual financial goals & risk tolerance, whether it’s equities, bonds, or alternative investments, understanding where & how to allocate assets ensures that our portfolios grow sustainably over time, allowing us to adjust as life stages change or new opportunities emerge. Finally, the importance of rebalancing is emphasised - the process of realigning the weightings of our portfolio. As market conditions shift & with events like the impending interest rate adjustments, regularly rebalancing ensures that we maintain the desired risk profile & continue to meet our financial objectives. This session also touched on broader financial trends affecting women in particular. With intergenerational wealth transfer becoming more prevalent, especially as older generations pass on their wealth, women must be prepared to manage this transition. The idea of horizontal wealth transfer, where assets move between spouses, reinforces the need for women to be financially literate & proactive in managing our family’s wealth as they often inherit financial responsibilities. Understanding how to diversify, allocate & rebalance portfolios isn’t just a strategy for today—it’s a long-term commitment to financial security and independence. By taking these steps, women are not only securing our own futures but also positioning ourselves as stewards of wealth for future generations. The time to act is now. Don’t wait for the market or life events to dictate your financial journey. Take control, implement these strategies, and move confidently toward the future you deserve. #FinancialEmpowerment #WomenInLeadership #PortfolioManagement #Diversification #WealthTransfer #Phoenixus #FinancialIndependence #InvestmentOpportunities #TakeAction

Your pension portfolio should give you zen like calm, poise and balance. However, the essence of successful investing lies not merely in picking winning stocks but in how these stocks interact within a portfolio. A well-constructed portfolio should include stocks that rise and fall at different times, creating a smoother, more stable return over time. This concept, known as diversification, is crucial for mitigating risk and achieving consistent long-term investment success. Understanding the Nature of Market Volatility Stock markets are inherently volatile, driven by a complex interplay of factors such as economic cycles, interest rates, geopolitical events, and investor sentiment. For instance, technology stocks might surge during periods of innovation and economic expansion but could suffer during market downturns or regulatory challenges. Conversely, stocks in more defensive sectors, such as consumer staples or utilities, tend to remain stable or even appreciate when the economy slows, as the demand for their products is less sensitive to economic forces. The Role of Correlation in Diversification Correlation is a statistical measure that describes how two assets move in relation to each other, with a correlation coefficient ranging from +1 to -1. A correlation of +1 indicates that the assets move in perfect sync, while a correlation of -1 means they move in opposite directions. A correlation of 0 suggests no relationship between the movements of the assets. In a well-diversified portfolio, the goal is to include assets with low or negative correlations. For example, when technology stocks like Microsoft rise due to an economic boom driven by innovation, energy stocks like ExxonMobil might fall if the same boom suppresses oil prices. Conversely, during periods of economic contraction, energy stocks might perform well due to rising oil prices, even as tech stocks decline. This dynamic allows for a more stable overall portfolio performance, as the opposing movements of non-correlated assets help to smooth out returns. The Evolution of Diversification Theory The concept of diversification through non-correlated assets is not new. It dates back to the work of Harry Markowitz, who introduced Modern Portfolio Theory (MPT) in 1952. In his seminal paper “Portfolio Selection,” Markowitz demonstrated how combining assets with low or negative correlations could reduce portfolio risk while maintaining expected returns. His work laid the foundation for the idea that a diversified portfolio offers the best risk-return trade-off, a principle that remains central to investment theory today (Markowitz, 1952).