Value Drivers

In this episode, Thomas Bodereau, Co Founder and CFO of Arrago, discusses his journey from banking and structured finance to building a French fintech focused on lifetime mortgages. Thomas spent much of his career in structured finance, including four years in Hong Kong. Arrago initially helped banks sell performing assets to institutional investors. When COVID changed market conditions, Thomas and his partners shifted their focus to an asset class they had already identified: lifetime mortgages. Understanding Lifetime Mortgages Arrago focuses on prêt viager hypothécaire, or PVH. An older homeowner uses a house or apartment as collateral and receives a lump sum based on the property value. Regular repayment is not mandatory, and interest compounds over time. Thomas explains why this fills a gap in France. Traditional bank lending is largely based on income and the ability to make monthly payments. Older homeowners can therefore have difficulty obtaining conventional credit even when they own valuable property. Arrago's lifetime mortgage customers are around 77 years old on average. How the Arrago Model Works Arrago develops the terms and risk models used for lifetime mortgages, including assumptions around property values and borrower longevity. It also operates a platform connecting brokers and retail banks to support underwriting. Because a bank is required to underwrite the loan, Arrago works with banking partners. Arrago then buys back the loans and groups them into a special purpose vehicle financed through capital markets or private equity money. Thomas explains that pension funds can be interested in these assets because they have longevity related liabilities and relatively few natural longevity assets available to match them. Building Origination Capabilities Arrago originally relied heavily on third party brokers for origination. Thomas describes that as an early strategic mistake because lifetime mortgages were not a core product for many brokers. Arrago eventually built its own origination capability and invested in SEA, SEO, and PR. For a team coming from structured finance, this required different skills. Thomas says understanding many things does not mean you will be good at executing everything. In some areas, hiring experienced people can save money over time. Trust and Market Development Thomas points to the UK as a more mature lifetime mortgage market and emphasizes the role of established financial institutions. For a complex retail financial product, trust matters. He argues that participation by major banks or insurance companies in France could help make lifetime mortgages more familiar and accelerate market development. Founder Lessons Thomas says entrepreneurs need to make decisions quickly and admit when they are wrong. If a plan is no longer relevant, founders should change direction rather than follow it simply because it was the original plan. He also emphasizes financial discipline, particularly when selecting outside providers. Relationships have mattered as well. Thomas credits former colleagues and business contacts with providing advice, introductions, financing support, and help during Arrago's early development. Key Takeaways • Lifetime mortgages can provide credit to older homeowners who may struggle to obtain traditional loans • Arrago connects risk modeling, bank partners, underwriting support, origination, and capital markets financing • Longevity affects both the risk model and the investment characteristics of the loans • Arrago built its own origination capability after initially relying heavily on third party brokers • Trust from established financial institutions could help expand the French market • Founders need to recognize mistakes quickly, adapt, and maintain financial discipline Chapter Summary (02:06) Thomas shares his journey from structured finance to entrepreneurship (06:29) Thomas explains the problem lifetime mortgages can address in France (12:27) Thomas describes Arrago's risk modeling, underwriting, and financing model (16:29) Thomas discusses the decision to build Arrago's own origination capability (18:11) Thomas explains why founders cannot execute everything themselves (20:49) The conversation turns to longevity and uncertain loan duration (24:08) Thomas discusses lessons from more developed European lifetime mortgage markets (28:49) Thomas shares lessons on decision making and financial discipline (31:46) Thomas reflects on relationships, trust, and the network that helped Arrago Resources Arrago: https://www.arrago.fr/ Stay Updated Please visit Brio360 for other episodes and resources on driving value creation https://brio360.com Follow Our Host Peter Ho https://linkedin.com/in/peterhocm Know a great guest for Value Drivers? Pitch founders, CEOs, CFOs, operators, or investors with standout capital allocation and scaling stories: [email protected] Please note that information provided in the podcast is for informational and educational purposes only and is not a recommendation to take any particular action, nor an offer or solicitation to buy or sell any securities or services presented. It is not investment advice. Brio360 does not provide legal or tax advice.  

In this episode, Sai Dhanak, cofounder and CEO of Deduction, discusses his journey as an entrepreneur and his vision for building an AI native personal accounting firm. Sai started his first company out of college, a video calling application for families that was later acquired by Mattel. He then joined Latch, where he served as chief product officer and helped the company grow from roughly 20 people to 500 and eventually go public. After leaving Latch, Sai wanted to solve a problem he personally understood. He saw the traditional tax and accounting experience as slow, expensive, and outdated, while advances in AI created an opportunity to rethink how professional services could be delivered. Rethinking the Personal Accountant Deduction is focused on the personal accountant market rather than DIY tax preparation. Sai argues that products such as TurboTax already work well for people who want to prepare their own taxes. Deduction is aimed at people who want someone else to handle the work, often because their financial situation has become more complicated or because they simply do not want to do it themselves. He also points to a supply problem. Demand for personal accountants is high, while the number of available CPAs is limited. The result can be slow responses, relatively high fees, limited proactive advice, and outdated customer experiences. Deduction combines tax professionals with an AI agent called Taylor, CPAI, to provide a more responsive and modern experience. How Deduction Works Sai says Deduction currently charges $500 for the year, including unlimited advice and preparation of the annual tax return. Clients are generally answered within 24 hours and often the same day. Taylor, CPAI can also reach out proactively about deadlines and tax planning. Deduction intentionally uses familiar communication channels. Customers can interact through email and SMS, track the progress of their return online, and upload documents digitally. Where Humans and AI Fit A major part of the conversation focuses on the boundary between AI automation and professional review. For material tax advice and tax returns, a member of Deduction's licensed tax team reviews the response. Tax professionals can also step into conversations when clarification or correction is needed. Some workflows have additional safeguards. Filing a tax return, for example, requires a human action and cannot be completed independently by AI. Sai describes the model as combining human trust and expertise with AI convenience and intelligence. DeductionOS and the Tax Team Behind the customer experience is DeductionOS, the company's internal platform. Sai describes it as an AI and human workspace where tax professionals can see AI agents communicating with clients and preparing tax returns. The system surfaces specific issues that require human attention. Deduction currently hires its CPAs, enrolled agents, and tax administrators internally and operates nationally. Over time, DeductionOS may also help the company expand its capacity beyond its internal team. Building Trust Peter and Sai discuss trust as one of the biggest challenges in applying AI to a high stakes service such as tax preparation. Every customer receives an onboarding call, and customers can call or text the company when they need help. Sai believes that as more services become AI native, human interaction may actually become more important. Deduction also offers a guarantee covering penalties and interest up to $10,000 when an error by Deduction is the sole reason for the issue. Who Deduction Is For Sai positions Deduction between DIY tax software and the traditional personal accountant experience. The core customer is what he describes as the mass affluent market: people with some financial complexity, often married or operating a small side business, but who may not require highly specialized tax planning. Scaling a Seasonal Business Deduction is currently supply constrained rather than demand constrained. Sai says the company is primarily investing in technology and its tax team to increase capacity. While January through April remains an important peak, many taxpayers file extensions, creating another peak around September and October. Customers also need help throughout the year with estimated taxes, business formation, planning, and other tax issues. Over time, Sai expects Deduction to expand further into tax advisory and planning. Customer Acquisition and the Longer Term Opportunity Deduction currently receives customers through referrals, SEO and GEO, and partnerships. Sai says demand for accountants is strong enough that getting the word out has not been the primary constraint. Looking further ahead, he sees an opportunity to make a personal accountant available to a much broader group of Americans and build a national, next generation tax brand. Key Takeaways • AI is creating an opportunity to rethink traditional professional services such as personal accounting • Deduction is focused on customers who want a personal accountant rather than DIY tax preparation • Taylor, CPAI handles parts of the customer experience while licensed tax professionals review material advice and tax returns • Certain high stakes actions, including filing a tax return, require explicit human involvement • DeductionOS allows tax professionals and AI agents to work together and surfaces issues requiring human attention • Human interaction remains an important part of building trust in an AI native service • Deduction currently targets mass affluent customers with moderate tax complexity • The company is supply constrained and is investing primarily in technology and its tax team • Tax planning and advisory could extend the customer relationship beyond filing season • Sai's longer term ambition is to build a national personal accounting brand Chapter Summary (01:44) Sai Dhanak shares his entrepreneurial journey and why he started Deduction (04:29) Sai explains the personal accountant market and the CPA supply problem (08:21) Sai discusses Deduction's pricing, responsiveness, proactive service, and customer experience (10:19) Peter and Sai discuss human review, AI guardrails, and higher stakes tax decisions (12:40) Sai explains how DeductionOS allows tax professionals and AI agents to work together (15:22) The discussion turns to trust, human touchpoints, and Deduction's guarantee (17:07) Sai positions Deduction relative to TurboTax and traditional tax firms (18:32) Sai describes Deduction's mass affluent target customer (19:07) Sai explains why Deduction is supply constrained and where the company is investing (19:44) Peter and Sai discuss tax seasonality and opportunities for year round advisory services (22:27) Sai discusses referrals, search, partnerships, and customer acquisition (23:43) Sai shares his longer term vision for Deduction and DeductionOS (25:56) Sai shares some of the podcasts and books he enjoys (26:58) Sai reflects on the lucky breaks and relationships that shaped his career Resources Deduction https://deduction.com     Stay Updated: Please visit Brio360 on other episodes and resources on driving value creation https://brio360.com   Follow our host:         Peter Ho https://linkedin.com/in/peterhocm   Know a great guest for Value Drivers? Pitch founders, CEOs, CFOs, operators, or investors with standout capital allocation and scaling stories: [email protected]     Please note that information provided in the podcast is for informational and educational purposes only and is not a recommendation to take any particular action, nor an offer or solicitation to buy or sell any securities or services presented. It is not investment advice. Brio360 does not provide legal or tax advice.

In this episode, Akshay Sarma, CFO of axio, discusses his path from Deutsche Bank to helping build a consumer finance company in India. Akshay began his career across trading, structuring, fixed income, and asset backed financing. After several years inside a large financial institution, he became interested in whether he could take an idea from a whiteboard and turn it into a real business. That question led him into the startup ecosystem and eventually to Capital Float, now axio, where he has spent more than a decade navigating economic cycles, a major business pivot, and the challenges of running a lending business. From Deutsche Bank to a Startup Akshay describes the adjustment from working inside a large institution with established systems to joining a smaller company where processes and tools had to be built from the ground up. Without the support of a major brand, the team had to sell its ideas, establish credibility, design processes, and improve them as problems emerged. He explains that this environment forced him to become stronger at the basics and learn what it means to operate as the smaller player in the room. From Small Business Lending to Consumer Finance axio began as a lender to micro, small, and medium sized businesses in India. Its products included supply chain finance, unsecured business loans, and financing for merchants selling through ecommerce platforms. The company entered consumer lending in 2018 and operated both businesses until the disruption caused by COVID. In 2021, it decided to run down the small business loan book and focus on consumer finance. Akshay explains that the pivot required changes to the organization, processes, operating metrics, and business plan. CFO Lens on Short Tenure Lending Many of axio's consumer loans run for one, three, or six months, with an average duration of roughly two to three months. Because the loans pay down quickly, the company needs continued disbursements and repeat customer usage to maintain its assets under management. Akshay describes this as a treadmill model. The short duration also changes how credit performance should be evaluated. Losses may relate to loans originated throughout the year, while assets under management reflect only the smaller balance currently outstanding. Traditional portfolio ratios can therefore look misleading. Finance needs to identify the right measures and explain why short tenure lending should be evaluated differently from longer duration lending. Balancing Growth, Risk, and the P&L Repeat customers can create what Akshay calls lower risk AUM because the company has more information about their repayment behavior. This allows the business to balance established customers with newer customers, including people taking their first loan. The goal is to identify poor risks early while helping strong customers return, receive higher limits, and use the product again. Akshay emphasizes that finance must work closely with credit and product teams. Product decisions need to account for growth, risk, customer behavior, and unit economics. They also need to consider how accounting and tax rules affect the P&L. A product may look attractive from an operating perspective while producing a different reported financial outcome. Capital Allocation and Product Experiments Peter and Akshay discuss capital allocation across technology, people, and lending products. axio made an early decision to build its lending and loan origination systems internally. The company also invested in people before reaching its current scale. Akshay describes these as conscious choices that created near term P&L costs but gave the company greater flexibility. For new lending products, he favors staged experiments. The company can begin with a defined capital budget, wait through the repayment cycle, gather feedback, and then decide whether to increase the investment. The process may include feedback from credit, collections, customer support, and customers themselves. Guardrails and Stop Loss Decisions Akshay argues that teams should agree on success metrics, amber lights, red lines, and required actions before launching a product. This allows the company to act when performance changes rather than debating its response after money has already been disbursed. The appropriate decision also depends on the funding environment and the amount of capital available. A capital constrained company may need to stop losses more quickly, while a company with more equity may have additional time to adjust the product. Akshay notes that axio has both closed products early and continued iterating on products that initially struggled. Team members may disagree, but once a decision is made, they commit while continuing to monitor the agreed metrics. Keeping a Complex Business Simple Akshay offers two main lessons for CFOs entering complex, high growth businesses. The first is to stay close to the basics. Even a complicated business is made up of simpler components. Finance leaders should identify the core metrics that define success and continue watching them as the company grows. The second is to build a strong FP&A and scenario planning process. Akshay maintains multiple versions of the business plan to understand what happens when performance is above plan, below plan, or significantly worse than expected. These scenarios help finance understand where intervention may be needed and when an issue should be raised with operating leaders, founders, investors, or the board. Key Takeaways • Moving from a large institution to a startup requires learning to build processes and credibility from the ground up • A business model pivot may require changes to the organization, operating metrics, processes, and business plan • Short tenure lending needs different portfolio measures than longer duration lending • Repeat customers can provide a lower risk foundation for measured growth • Finance needs to connect growth, credit risk, unit economics, accounting, and the P&L • Early investments in technology and people can create flexibility as a company scales • New lending products should be tested through defined capital budgets and gradual increases • Success metrics, warning indicators, and stop loss actions should be agreed before launch • Core metrics and scenario planning can help CFOs manage a complex business Chapter Summary (01:34) Akshay Sarma shares his path from Hyderabad and Mumbai to Deutsche Bank, Cambridge, and the startup ecosystem (05:12) Akshay discusses the adjustment from a large financial institution to building processes inside a startup (08:05) Akshay explains how Capital Float moved from small business lending toward axio's consumer finance model (10:35) The discussion turns to the CFO implications of short tenure consumer lending (14:07) Akshay explains how repeat customers help balance portfolio growth and credit risk (16:04) Peter and Akshay discuss collaboration among finance, credit, and product, as well as the difference between unit economics and the P&L (19:35) Akshay outlines capital allocation decisions involving technology, people, and organizational scale (22:13) Akshay explains how axio uses defined budgets and gradual increases to test new lending products (23:54) The discussion turns to success metrics, warning indicators, red lines, and predetermined actions (27:04) Akshay discusses stop loss decisions, funding conditions, and when to close or continue adjusting a product (29:21) Akshay shares his advice for CFOs managing complex, high growth operating models (31:56) Akshay explains why FP&A and scenario planning are important tools for the CFO office (34:30) Akshay discusses the Mahabharata and Good to Great (35:42) Akshay reflects on destiny, mentorship, hard work, and the people who shaped his career Resources axio https://www.axio.co.in/ Stay Updated Please visit Brio360 for other episodes and resources on driving value creation https://brio360.com Follow Our Host Peter Ho https://linkedin.com/in/peterhocm Know a great guest for Value Drivers? Pitch founders, CEOs, CFOs, operators, or investors with standout capital allocation and scaling stories: [email protected] Please note that information provided in the podcast is for informational and educational purposes only and is not a recommendation to take any particular action, nor an offer or solicitation to buy or sell any securities or services presented. It is not investment advice. Brio360 does not provide legal or tax advice.  

In this episode, Marc Frenkel, CFO of Coterie Insurance, discusses his path from investment banking and insurance finance to helping scale a tech enabled MGA focused on simplifying commercial P&C insurance for small businesses. Marc began his career in investment banking at Rothschild, where an early insurance restructuring assignment introduced him to the complexity of the industry. He later worked at AmTrust Financial and FinLync before joining Coterie, where he saw an opportunity to work on a meaningful problem in small business insurance. Coterie focuses on micro commercial insurance, serving very small businesses, solo entrepreneurs, side hustles, and local service providers that are often underinsured or unaware of their commercial insurance needs. Marc explains why this part of the market has historically been difficult to serve and why technology, data, and agents all matter in making the model work. What Coterie Is Solving A big theme in the conversation is the friction in small business insurance. For many micro commercial customers, the insurance need is real, but the premium is small. That makes the traditional underwriting process difficult because agents may need to gather a lot of information for a policy that generates limited commission. Marc discusses how Coterie uses technology, data, and publicly available information to make the process faster and more efficient. Marc describes the goal as helping agents quote and bind coverage more efficiently while reducing the amount of manual work required to understand the business. The discussion also highlights a counterintuitive point: Coterie is not only competing with other insurance providers. It is also addressing underinsured businesses and low awareness of commercial insurance needs. CFO Lens: Scaling an Insurtech MGA Peter and Marc discuss the metrics that matter when scaling an insurtech MGA. Marc explains that while EBITDA matters, the deeper operating model depends heavily on loss ratio. Because Coterie does not retain balance sheet risk, it relies on capacity providers that need confidence in the quality of the premium being written. That makes underwriting discipline central to the business. Growth is important, but Marc emphasizes that not all growth is equal. Growing with poor quality premium may create short term revenue, but it can damage capacity relationships and undermine the business later. For Coterie, quality growth means expanding premium while maintaining the loss ratio and protecting the trust of capacity providers. Capital Strategy and Quality Growth The conversation turns to how capital allocation changes as a company moves from startup mode to scale mode. Marc describes how investment decisions looked different when Coterie was earlier stage and not yet profitable. At that time, payback period mattered heavily because the company had to preserve cash and manage toward break even. Now that Coterie is profitable and better capitalized, the company can think more strategically about long term value creation. Marc discusses investments in technology, platform capabilities, and product expansion, including how existing distribution, data, and infrastructure may create an advantage in adjacent opportunities. A key idea is capital efficient growth: finding opportunities where the company can expand without creating unnecessary complexity. Building the CFO Office Marc also shares what he focused on after joining Coterie. He joined during a difficult period for insurtech and the broader venture market, when capital was no longer easy to raise. That shaped his early priorities as CFO. The goal was to build a plan to reach cash flow break even, reduce reliance on capital markets, and give the company more control over its own destiny. The discussion covers forecasting, contribution margin, fixed and variable expenses, board communication, and KPI discipline. Marc also explains why finance needs the right level of data granularity. Looking at the business only in total can hide important dynamics. Coterie sells through partners, so understanding performance at the partner level helps the team identify where growth is slowing, where competition may be increasing, and where the product or distribution strategy needs to adjust. Key Takeaways • Micro commercial insurance is a large market, but historically difficult to serve efficiently • Coterie uses technology, data, and agents to reduce friction in quote to bind • For an MGA, loss ratio is a critical constraint because it supports capacity provider trust • Quality growth matters more than simply growing premium • Capital allocation changes as a company moves from cash preservation to profitable scale mode • CFOs need to understand where granular data improves decisions and where it creates unnecessary noise • Reaching cash flow break even can change a company's strategic flexibility and control over its future Chapter Summary (01:47) Marc Frenkel shares his career path from Rothschild and AmTrust Financial to FinLync and Coterie Insurance. (03:10) Marc explains the small business insurance problem Coterie is solving and why micro commercial P&C insurance is hard to serve efficiently. (05:37) The discussion turns to how Coterie uses technology, data, and agents to improve quote to bind. (10:09) Marc outlines the CFO metrics that matter in an insurtech MGA, including premium growth, loss ratio, capacity, and underwriting discipline. (13:59) Peter and Marc discuss quality growth and why bad premium can create problems later. (16:15) Marc explains how Coterie thinks about capital allocation, product expansion, and long term investment priorities. (21:32) The conversation turns to investors, capacity providers, risk appetite, and board communication. (23:10) Marc discusses building the CFO office, including reporting cadence, forecasting, systems, and finance maturity. (28:12) Marc shares how finance uses data to understand business performance at the right level of detail. (32:20) Marc reflects on risk, judgment, and the need for finance leaders to move between risk on and risk off modes. (34:49) Marc shares the lucky break that led him to Coterie and how a principled stand changed his career path. Resources Coterie Insurance: https://coterieinsurance.com Marc Frenkel on LinkedIn: https://www.linkedin.com/in/marc-frenkel-66287931 Stay Updated: Please visit Brio360 for other episodes and resources on driving value creation https://brio360.com Follow our host: Peter Ho https://linkedin.com/in/peterhocm Know a great guest for Value Drivers? Pitch founders, CEOs, CFOs, operators, or investors with standout capital allocation and scaling stories: [email protected] Please note that information provided in the podcast is for informational and educational purposes only and is not a recommendation to take any particular action, nor an offer or solicitation to buy or sell any securities or services presented. It is not investment advice. Brio360 does not provide legal or tax advice.  

In this episode, Yogi Goel, co-founder and CEO of Maxima AI, discusses his path from EY, Wall Street, and Rubrik to building a company focused on applying agentic AI to accounting and record-to-report workflows. Yogi started his career at EY, where he developed a foundation in audit, accounting standards, controls, and how large companies operate. He later worked in finance and capital markets before joining Rubrik, where he saw firsthand how finance and accounting operations need to evolve as companies scale. That experience shaped the problem Maxima AI is focused on today: accounting teams still spend too much time on manual work, spreadsheets, reconciliations, checklists, and system-to-system coordination. What Maxima AI Is Solving A big theme in the conversation is that accounting workflows matter more than many people realize. Record-to-report is not just a back-office process. It affects close speed, audit readiness, reporting confidence, and management visibility. Yogi explains how Maxima AI fits into the accounting workflow as an agentic system of work. The goal is not to replace the ERP or remove human judgment. Instead, Maxima AI helps prepare accounting work so finance teams can review, approve, and move faster with better control. Where AI Fits in Finance Peter and Yogi discuss how AI should be used in finance and accounting, especially in workflows where teams still rely on manual review and repetitive coordination. One important distinction is the boundary of automation. Yogi's view is that AI can take on more of the preparation work, but human judgment still matters. CFOs, controllers, and auditors need confidence that the work is accurate, explainable, and auditable before it reaches the general ledger. CFO Lens: Trust, Controls, and Auditability For CFOs, AI adoption is not just about speed. It is about trust. Yogi notes that finance leaders should not feel pressure to rip and replace existing systems. A more practical path is to start with lower-risk workflows, build confidence, and then expand over time. That makes controls, audit trails, and clear human review essential to adoption. The Future of the CFO Office The conversation also looks ahead to how the CFO office may evolve over the next several years. If AI adoption increases, the role of accountants and analysts may shift away from lower-value manual work and toward review, judgment, risk management, and business insight. For CFOs, the opportunity is not just a faster close. It is building a finance function with more capacity to help the business make better decisions. Key Takeaways • Accounting teams are still dealing with too much manual workflow complexity • Record-to-report affects close speed, controls, audit readiness, and financial visibility • Agentic AI can help prepare accounting work, but humans still need to review and approve key judgments • CFO adoption depends on trust, controls, auditability, and clear boundaries around automation • AI can work alongside existing systems rather than replacing them immediately • The finance function may become more strategic as repetitive tasks become more automated Chapter Summary (02:13) Yogi Goel shares his background across EY, Wall Street, Rubrik, and Maxima AI (06:14) The discussion turns to the accounting problem Maxima AI is solving (10:41) Yogi explains how Maxima AI fits into record-to-report workflows (15:08) Peter and Yogi discuss CFO adoption, controls, auditability, and trust (20:01) The conversation explores where automation should stop, slow down, or require human judgment (24:02) Yogi shares his view on how the CFO office may evolve over the next several years (28:55) The discussion turns to ERPs, systems of record, and why so much work still happens in Excel (33:22) Yogi reflects on lucky breaks that shaped his career and the relationships that helped shape Maxima AI Resources Maxima AI: https://www.maxima.ai/ Stay Updated: Please visit Brio360 for other episodes and resources on driving value creation https://brio360.com Follow our host: Peter Ho https://linkedin.com/in/peterhocm Know a great guest for Value Drivers? Pitch founders, CEOs, CFOs, operators, or investors with standout capital allocation and scaling stories: [email protected]   Please note that information provided in the podcast is for informational and educational purposes only and is not a recommendation to take any particular action, nor an offer or solicitation to buy or sell any securities or services presented. It is not investment advice. Brio360 does not provide legal or tax advice.