Economic Consulting Firms

Financial Value of Climate Risks and Opportunities 🌍 Companies are under increasing pressure to reflect climate risks and opportunities in financial decision making. This is essential for embedding sustainability into strategy and unlocking measurable business value. ERM highlights that financial valuation of environmental and social factors enables companies to align investment decisions with long term performance. Value is created through energy efficiency, circular models, responsible sourcing, and workforce inclusion. These actions contribute to resilience, innovation, and cost efficiency. Sustainable products are experiencing significantly higher growth rates than conventional alternatives. Efficiency measures can reduce operating costs by up to 30 percent, while green finance instruments can lower the cost of capital. These gains can be captured directly in financial models and forecasts. At the same time, climate related risks are increasing in scale and frequency. Physical risks already account for over 270 billion dollars in annual damages. Transition risks may result in stranded assets worth hundreds of billions. The broader economic cost of unmitigated climate change could reduce global GDP by up to 18 percent by mid century. ERM presents two complementary approaches. Value creation focuses on capturing upside through efficiency, innovation, and market expansion. Risk mitigation addresses downside exposure by incorporating climate risks into business planning and decision processes. Both require integration of ESG into financial structures. This means applying standard financial tools such as internal rate of return and discounted cash flow to evaluate climate related actions. It also involves including environmental risks in sensitivity testing, pricing models, and capital planning frameworks. Translating these impacts into financial terms enables clearer comparison and stronger governance. Capital markets are moving toward companies that manage climate exposure effectively. Lower financing costs, stronger investor confidence, and increased access to sustainability linked capital are all benefits of a robust ESG integration strategy. Quantifying the financial value of climate related risks and opportunities enables companies to move from qualitative ambition to strategic execution. Those that lead in this area are better prepared to compete, attract capital, and deliver long term results. Source: ERM #sustainability #sustainable #esg #business

The Affordability Crisis Is an Inequality Crisis When prices spike in key sectors like energy, food, and housing, it's not just inflation—it's a massive redistribution shock that hits low-income households hardest. In our new working paper, my co-authors and I identify which sectors matter most for both inflation and inequality. Here are the key findings: The Problem with Standard Inflation Analysis Traditional approaches reduce inflation to a single aggregate index. This conceals two critical facts: inflation is often triggered by sector-specific price shocks, and consumption baskets differ systematically across income groups. The result? Unequal inflation burdens that worsen income inequality. Our Approach We extended the input-output price model to trace how price shocks propagate through production networks while accounting for how different income groups spend their money. By introducing decile-specific consumption baskets, we can simulate how each sectoral shock affects living costs across the income distribution and map these effects to changes in the Gini coefficient. What We Found The capacity to increase inequality is highly concentrated in a small set of "systemically significant sectors for inequality" (SSS-I): - Energy (oil, gas, petroleum & coal products) - Food and agriculture - Chemicals - Housing - Wholesale trade - Healthcare Consumption heterogeneity is critical: a shock to food generates inflation 126% higher for the poorest households than the richest. For petroleum and coal products, it's 54% higher for the poorest decile. The 2021-2022 Case The joint shock to the eight SSS-I sectors during this period raised the Gini coefficient by 0.0023—approximately one full year of the average annual increase in inequality observed during 1980-2021. Petroleum and coal shocks alone accounted for roughly one-third of a typical year's inequality increase, while food and agriculture shocks each represented about two-thirds. Policy Implications These findings challenge conventional monetary policy responses. Interest rate hikes do little to lower the price of oil or food, yet they raise debt costs and weaken labor markets—amplifying inequality rather than alleviating it. Using blunt monetary tightening against supply shocks is both inefficient and regressive. Macroeconomic stability and income distribution stability are deeply intertwined. A Better Path Forward We need a policy toolkit that includes strategic reserves, supply chain resilience, and sector-specific price instruments. These approaches can contain inflation in systemically significant sectors without worsening inequality.

Delighted to announce the launch of my completely rebuilt Financial Risk Management lecture series on YouTube. This 2025 series replaces my earlier playlists from 2021, offering a fully updated, end-to-end pathway through modern market risk management. Unlike the previous version, which required a sequence of prerequisite mathematics videos, this new series is accessible to learners from any background. All essential mathematics, statistics and modelling are introduced precisely when needed within each topic, so you can begin exploring the substance of financial risk management immediately and build technical skills as you progress. The series covers eight key topics, each in six videos, totalling about two hours per topic: Introduction to Financial Risk Management Credit Risk Management Portfolio Returns and their Distributions Volatility and Value-at-Risk Fixed Income Portfolios International Equity and Commodity Portfolios Risk Management for Options Portfolios Capital Reserves for Market Risk Every lecture from Topic 2 onwards is supported by interactive, practical Excel workbooks to help consolidate the theory. Whether you are preparing for interviews, advancing your professional practice, or studying at undergraduate or postgraduate level, this series delivers rigorous, industry-aligned content on how banks and financial institutions manage, measure and mitigate risk across a range of instruments and portfolios. Topics include VaR, Expected Shortfall, credit risk, risk aggregation, regulatory capital and the Basel Accords, backtesting, stress testing, and much more. Explore the full playlist of 48 videos here: https://lnkd.in/eUYzXPCF Feedback and questions welcome — please share with any colleagues or students who may benefit. #FinancialRiskManagement #MarketRisk #CreditRisk #RiskModelling #QuantFinance #FinanceEducation #RiskManagement #Banking #BaselAccords #ExcelForFinance #PortfolioManagement #ValueAtRisk #ExpectedShortfall #FinancialInstitutions #ProfessionalDevelopment #FinancialEngineering #FinanceStudents #FRM #FinancialRegulation #YouTubeLectures

Balance sheets can tell strange stories. At first glance, a financial analyst may think this company is going to get really healthy in April. But looking more closely, the reality is very different. If I were teaching a young financial analyst what to look for, here's what I'd advise (Note: this is loosely based on a real-life example, but I've modified many of the elements for educational purposes). (1) Assets Drop Because Items Are Disappearing In the top section of the balance sheet, we forecast prepaid loan fees and goodwill going to zero. This is strange behavior, as this will likely never take place in the normal course of business. This means it's not a normal month. • Prepaid loan fees are tied to debt, which means that if the debt goes away, so too will the fees. • Goodwill going to zero is even more strange. It means the company is likely going to write it off, or the balance sheet will be reset. These changes should tell an analyst that something is different. It's probably a one-off transaction. (2) Debt Goes Away In the middle of the balance sheet, I show that debt goes to zero all at the same time. Accrued interest, which increases every month, also goes to zero in month 4. These are the biggest clues of what's going to take place. A company rarely pays off that much debt all at once. The company is likely going to recapitalize, in the form of financial restructuring through a debt-for-equity swap. The debt is likely going to be removed through a transaction, not paying down the debt with cash. That's why you see no change to cash but a material change to equity. (3) Equity Turns Positive It should jump out to an analyst that Shareholders' Equity is negative in the first 3 months of the year, suggestion that the company may be insolvent. But in the 4th month, equity turns positive. This doesn't mean that the company all of a sudden becomes healthy -- it means that once the debt is retired, the balance sheet looks better on paper. --------------- A lesson for early-career analysts: A better-looking balance sheet does not always mean the business improved overnight. Sometimes the business does improve. Sometimes the accounting changed because of a major event. Every balance sheet tells a story. ✨ Considering following along through The Statement Newsletter, where we talk about next-level finance, accounting, and business management topics: https://lnkd.in/gSwWYzf4

It’s all about Capital Solutions: Many private credit managers manage an “Opportunistic Credit” investment program. Traditionally, these opportunistic credit investors known as ‘distressed’ investors targeted the fulcrum security within the capital structure of a highly leveraged/distressed company, whereby the holders of this debt class took control of the equity once the company exited Chapter 11. Today, most Opportunistic Credit investors have updated their playbook to avoid distressed companies that must go through Chapter 11. BK is expensive, costing ~10% of the total enterprise value of a company, which wipes out the pre-petition equity and eats into the recovery value of creditors. In BK, lawyers and bankers win, but the fees they earn comes directly out of recovery for the debt. Investment Managers recognize that companies typically benefit if they can continue to operate outside of Chapter 11. So, today it’s all about Capital Solutions. ‘Higher for Longer’ has proved punishing for many over-levered companies as interest expense eats up available cash flow, leaving little/no distribution for shareholders. Liability management exercises such as debt refinancing, discounted debt buybacks, and tender offers, help a company improve its debt profile without the need to convert debt into equity or fundamentally change the company's ownership structure. Private Equity sponsors have been quick to adopt to this market practice and prefer a pro-active engagement with creditors to strengthen the capital structure and cash flow of a company thru capital solutions. This allows the PE sponsor to retain their full equity position rather than being wiped out or diluted, which occurs in traditional restructurings where new equity is issued to creditors. Capital Solutions are always a negotiation, and often the PE sponsor is willing to invest additional equity to support the company since it is only fair that both the equity sponsor and creditors do their part to strengthen the capital structure, to enable the company to thrive. Transactional volume from BK to Capital Solutions shown below in this chart highlights this broader trend in corporate finance that is highly beneficial for investors, creditors, and stakeholders alike. Credit investors who navigate the complex landscape of corporate restructuring in an effort to create a win-win for the equity, company and creditors are the true value creators.

Inflation isn’t just an economic challenge—it’s a test of agility for businesses. As costs rise and purchasing power shifts, companies that rely on gut instinct risk falling behind. The real winners? Those who use data-driven insights to navigate uncertainty. 1️⃣ Understanding Consumer Behavior: What’s Changing? Inflation reshapes spending habits. Some consumers trade down to budget-friendly options, while others delay non-essential purchases. Businesses must analyze: 🔹 Spending patterns: Are customers shifting to smaller pack sizes or private labels? 🔹 Channel preferences: Is there a surge in online shopping due to better deals? 🔹 Regional variations: Inflation doesn’t hit all demographics equally—hyperlocal data matters. 📊 Example: A retail chain used real-time sales data to spot a shift toward economy brands, allowing it to adjust promotions and retain price-sensitive customers. 2️⃣ Pricing Trends: Data-Backed Decision-Making Raising prices isn’t the only response to inflation. Smart pricing strategies, backed by AI and analytics, can help businesses optimize margins without losing customers. 🔹 Dynamic pricing models: Adjust prices based on demand, competitor moves, and seasonality. 🔹 Price elasticity analysis: Determine how much a price hike impacts sales before making a move. 🔹 Personalized discounts: Use customer data to offer targeted promotions that drive loyalty. 📈 Example: An e-commerce platform analyzed customer behavior and found that small, frequent discounts led to better retention than infrequent deep discounts. 3️⃣ Demand Forecasting & Inventory Optimization Stocking the right products at the right time is critical in an inflationary market. Predictive analytics can help businesses: 🔹 Anticipate demand surges—especially in essential goods. 🔹 Optimize supply chains to reduce excess inventory and prevent stockouts. 🔹 Reduce waste in perishable categories like F&B, where price-sensitive demand fluctuates. 📦 Example: A leading FMCG brand leveraged AI-driven demand forecasting to prevent overstocking of premium products while ensuring budget-friendly variants were always available. 💡 The Takeaway Inflation isn’t just about rising costs—it’s about shifting consumer priorities. Companies that embrace data-driven decision-making can optimize pricing, fine-tune inventory, and strengthen customer loyalty. 𝑯𝒐𝒘 𝒊𝒔 𝒚𝒐𝒖𝒓 𝒃𝒖𝒔𝒊𝒏𝒆𝒔𝒔 𝒂𝒅𝒂𝒑𝒕𝒊𝒏𝒈 𝒕𝒐 𝒊𝒏𝒇𝒍𝒂𝒕𝒊𝒐𝒏𝒂𝒓𝒚 𝒑𝒓𝒆𝒔𝒔𝒖𝒓𝒆𝒔? 𝑨𝒓𝒆 𝒚𝒐𝒖 𝒖𝒔𝒊𝒏𝒈 𝒅𝒂𝒕𝒂 𝒕𝒐 𝒓𝒆𝒇𝒊𝒏𝒆 𝒚𝒐𝒖𝒓 𝒔𝒕𝒓𝒂𝒕𝒆𝒈𝒚? 𝑳𝒆𝒕’𝒔 𝒅𝒊𝒔𝒄𝒖𝒔𝒔 𝒊𝒏 𝒕𝒉𝒆 𝒄𝒐𝒎𝒎𝒆𝒏𝒕𝒔! #datadrivendecisionmaking #dataanalytics #inflation #inventoryoptimization #demandforecasting #pricingtrends

Do you know why economics, data science, and AI are converging rapidly? In the past 4 weeks, I have seen more open positions in various industries, that require an economics background. Employers are seeking economists skilled at machine learning, statistical software, and computational thinking. The purpose is to move beyond traditional theory toward applied problem-solving with technology. The "data-driven" push is quietly turning towards a "decision-making" priority as AI rapidly eases the technological burden. Does this mean that everyone needs to become an economist and go get a graduate degree in it? No, but it does mean that everyone would benefit from revisiting the core concepts of economics and applying them more consistently in their decision-making processes. For instance, if you look closely at any business mistakes, you will find that they are most likely rooted in a false assumption about trade-offs. Every pricing move, hiring call, expansion plan, and vendor choice is really a decision about scarce resources, time, and demand under constraints. Here is the basic economics framework that consists of just three questions or tests before making a decision to scale or adding new features to existing products: 1. What to produce?  - This is the demand test.  - A business needs to know whether the market truly wants the offer, or whether it is forcing supply into weak demand. 2. How to produce it?  - This is the operating model test.  - Cost is not just budget.  - It includes time, execution load, and the hidden strain on teams and systems. 3. For whom to produce?  - This is the allocation test.  - Buyers do not act in a vacuum.  - Their choices reflect pressure, incentives, and purchasing context. Data Science and AI are extremely useful in processing larger datasets, improving forecasting, and sharpening risk assessment.  But they do not replace economic logic. They make that logic easier to apply at speed, provided the source assumptions are sound. Actionable Insights for businesses: • Price the trade-off. Good decisions weigh scarce resources against real demand, not internal optimism. • Identify hidden costs. Production choices should include time, system complexity, and organizational load. • Segment by buyer priorities. Customer analysis improves when businesses study constraints shaping buyer behavior. • Use AI in tandem with theory. Models are strongest when paired with causal reasoning and economic context. Having more data is meaningless if you don't have the right framework to make better decisions with it. - Dr. Kruti Lehenbauer of Analytics TX, LLC #Economics, #DataScience, #AI #RefreshWithRyza P.S.: Have you seen a higher demand for economics skills in your industry?

Leaders ask me about frameworks they can use to identify and assess external risks and opportunities for their organizations. I have begun to use PESTLE analysis. I believe it is complimentary to risk management. First, some background, the framework was introduced by Harvard Business School professor Francis J. Aguilar in his 1967 book, Scanning the Business Environment, as a tool for businesses to systematically analyze external macro-environmental factors that could impact their strategic planning. The framework has evolved to PESTLE. ▶️Political-Government policies, political stability, trade restrictions, tariffs, and tax policies that may impact a business. ▶️Economic-Encompasses the economy and how conditions, like inflation rates, interest rates, exchange rates, GDP growth, and consumer disposable income, affect the business and its market. ▶️Social-Defined as cultural aspects, demographics, and consumer behaviors. ▶️Technology-This covers the velocity of technological innovation, automation, R&D that could affect an industry or market. ▶️Legal-This includes laws and regulations impacting the industry. ▶️Environmental-These is defined by such topics as such topics like climate change, sustainability practices, ethical sourcing, etc. PESTLE analysis is complimentary to risk management because it provides a structured framework for identifying and assessing external risks that are beyond an organization's influence and/or control. PESTLE helps leaders look at the macro-environment. The insights from a PESTLE analysis can be used as an input to scenario planning. This helps leaders consider how different external changes might play out and develop appropriate resiliency plans. Executives are expected to be strategic navigators in disruptive uncertainty. As a fan of risk management, this framework can help you mitigate internal financial, operational and technology risks by understanding the external emerging risks that can reshape your business overnight in our 24/7 business risk cycle. #RiskManagement #CFO #Leaders Inside Edge Risk Advisors LLC

Zoomcar has just announced a significant step towards financial stability by restructuring its debt. This move is aimed at reducing their outstanding debt and ensuring long-term sustainability. But, what’s the significance of doing this? Debt restructuring can be a game-changer for companies facing financial challenges. Here’s why: 📌 Improved Cash Flow: By renegotiating the terms of their debt, companies can reduce immediate cash outflows, allowing them to allocate resources more effectively towards growth and innovation. 📌 Enhanced Financial Stability: Restructuring helps in stabilizing the financial health of a company, making it more attractive to investors and stakeholders. This stability is crucial for maintaining trust and confidence in the business. 📌 Strategic Investments: With reduced debt obligations, companies can invest in strategic initiatives that drive long-term value. This could include expanding product lines, entering new markets, or enhancing technological capabilities. 📌 Operational Flexibility: Debt restructuring often comes with more favorable repayment terms, providing companies with the flexibility to manage their operations without the constant pressure of looming debt repayments. 📌 Stakeholder Confidence: Successfully navigating debt restructuring can boost the confidence of stakeholders, including employees, customers, and partners. It demonstrates a commitment to financial responsibility and long-term success. For entrepreneurs and business leaders, understanding the intricacies of debt restructuring is essential. It’s not just about managing debt; it’s about positioning your company for sustainable growth and resilience. What are your thoughts on debt restructuring? #DebtRestructuring #FinancialStability #BusinessStrategy #CorporateFinance

Growth in today’s business environment is no longer driven by instinct or historical success alone. The integration of 𝐝𝐚𝐭𝐚 𝐚𝐧𝐚𝐥𝐲𝐭𝐢𝐜𝐬 into business development has redefined how companies strategize, operate, and scale. Let me share some case studies: 🎯 Asian Paints combined weather data with regional buying patterns to predict peak sales and optimize inventory. 🎯 Tata Consultancy Services (TCS) using advanced analytics for predictive maintenance. 🎯 Zomato and Swiggy leveraging real-time data for customer engagement and delivery optimization. We have to agree on this, data is the new oil powering business engines. In an era where organizations generate enormous volumes of data across touchpoints—from customer interactions and logistics to financial flows and market signals—the ability to harness and analyze this information has become a core differentiator between stagnation and sustainable success. Data analytics transforms raw, often unstructured data into actionable insights. Whether it is a mid-sized manufacturing firm optimizing production schedules or an IT services company evaluating expansion into new geographies, data analytics is foundational to clarity and confidence in every major decision. Across sectors, the impact is tangible. A 2023 NASSCOM report indicated that over 74% of Indian enterprises that adopted advanced analytics solutions reported measurable improvements in operational efficiency, while 63% experienced revenue growth through better customer targeting and service personalization. The analytics maturity of a business increasingly correlates with its ability to innovate, adapt, and lead. 𝐑𝐞𝐚𝐥-𝐭𝐢𝐦𝐞 𝐝𝐚𝐬𝐡𝐛𝐨𝐚𝐫𝐝𝐬 𝐚𝐧𝐝 𝐩𝐫𝐞𝐝𝐢𝐜𝐭𝐢𝐯𝐞 𝐦𝐨𝐝𝐞𝐥𝐬 now allow businesses to pre-empt disruptions, allocate resources with precision, and manage vendor performance based on historical data rather than assumptions. Indian manufacturing clusters, particularly in auto components and textiles, are using analytics to reduce rework rates, lower inventory carrying costs, and improve delivery timelines. Sales and marketing teams no longer rely solely on quarterly performance reviews. Data-driven customer segmentation, sentiment analysis, and behavioral tracking provide granular insights into consumer preferences and product lifecycle trends. An EY India study highlighted that predictive analytics tools are helping organizations reduce voluntary attrition by as much as 20% by identifying high-risk profiles and implementing timely interventions. One of the most powerful applications of data analytics is in product and service innovation. By analyzing structured feedback, usage patterns, and online reviews, businesses are able to accelerate time-to-market and design offerings that are more aligned with actual user expectations. In the financial sector, for instance, lending institutions now use analytics models to determine creditworthiness and reduce delinquency.