Himansi S.

• Led end-to-end financial planning and integrated forecast modeling for a ~$2B strategic acquisition, developing revenue and cost synergy projections to support executive investment decisions and long-term profitability. • Built comprehensive 3-statement and scenario-based financial models to evaluate deal economics, capital allocation, and ROI outcomes. • Owned quarterly forecast cycles and monthly variance analysis across multiple product lines, improving forecast accuracy by 18% and strengthening operating margin control. • Partnered with Product, Strategy, and Operations leaders to evaluate new ETF launches, developing scenario models projecting 12–15% recurring revenue growth. • Designed executive-level Power BI dashboards tracking AUM growth, fee yield, expense ratios, and operating leverage, reducing manual reporting time by 40%. • Conducted detailed pricing, profitability, and cost allocation analysis, contributing to ~20% reduction in operational redundancies post-acquisition integration. • Delivered monthly executive performance reviews, translating complex financial data into actionable insights for senior leadership. • Identified margin expansion and cost optimization opportunities through advanced variance and trend analysis across revenue streams. • Automated recurring financial reporting workflows using Python and SQL, reducing close-cycle preparation time by 30% and increasing reporting scalability. • Strengthened financial data integrity and reporting efficiency through process automation, improved validation controls, and cross-functional collaboration.

• Led annual budgeting and rolling forecast processes across Trading and Treasury functions, managing multi-million-dollar expense budgets and improving forecast precision by 21%. • Owned monthly P&L reporting and comprehensive variance analysis, identifying key cost drivers and implementing corrective actions that improved expense efficiency by 15%. • Partnered with Risk, Treasury, and Operations leadership to support capital planning and liquidity forecasting initiatives aligned with enterprise performance objectives. • Developed rolling forecast models to enhance short- and long-term financial visibility across revenue and expense streams. • Built automated financial dashboards consolidating revenue, expense, and liquidity metrics, reducing manual reporting effort by 42%. • Designed scenario and sensitivity models to assess revenue impact under changing market conditions, supporting executive-level strategic planning decisions. • Strengthened liquidity and capital allocation analysis by integrating financial and operational datasets for improved forecasting accuracy. • Enhanced financial data validation processes using SQL and automation tools, increasing reporting accuracy and reducing reconciliation discrepancies by 34%. • Streamlined month-end reporting workflows, accelerating reporting timelines and improving data transparency across stakeholders. • Delivered actionable financial insights to senior leadership, enabling data-driven decision-making and improved cost governance.

• Managed budgeting and forecasting for a treasury products portfolio exceeding $1.4B in notional exposure, improving forecast accuracy from 82% to 93% over two fiscal cycles. • Owned monthly and quarterly financial performance reporting, delivering actionable variance analysis and forward-looking projections to senior leadership. • Conducted detailed profitability and cost-benefit analysis across structured products, improving capital efficiency by 14%. • Built and enhanced financial forecasting models to support revenue planning and expense management across treasury product lines. • Automated recurring financial reporting processes using SQL, VBA, and BI tools, reducing reporting turnaround time by 35%. • Improved financial data transparency by standardizing reporting frameworks and strengthening reconciliation processes. • Partnered with Technology and Operations teams to streamline financial data flows, increasing reporting reliability and accelerating decision-making. • Developed multi-scenario financial models under macroeconomic stress conditions to support long-term strategic planning initiatives. • Identified margin enhancement and cost optimization opportunities through trend analysis and performance benchmarking. • Strengthened internal financial controls and reporting accuracy through improved data validation and cross-functional collaboration.