Accend Eliminates Manual Financial Spreading to Help Credit Teams Move Faster and Smarter

Every credit decision starts with numbers. But if you’re still manually spreading those numbers, you’re wasting time, money, and risking costly errors, says Pranjal Daga. 

Financial analysts at banks, fintechs, insurers, and lenders have spent countless hours manually spreading and analyzing financial statements, a slow, error-prone process that drags down approval speeds and inflates operational costs. Despite advances in automation across industries, underwriting remains largely manual, creating a billion-dollar inefficiency that financial institutions worldwide have struggled to resolve.

Accend, a company built on addressing inefficiencies in financial data analysis, is tackling this problem head-on. The company has officially launched its AI-powered Financial Statement Spreading & Analysis solution, marking its expansion into underwriting. The goal is simple: deliver 100% accuracy by combining AI-driven analysis with human-in-the-loop validation, allowing credit teams to move faster without sacrificing precision.

Underwriting teams across financial institutions operate in an environment where accuracy is non-negotiable. Yet, the traditional approach to financial statement analysis is riddled with inefficiencies. Analysts manually extract and enter data, cross-check numbers, and compile credit memos, resulting in slow approvals and costly errors.

This is not only an inconvenience, it directly impacts the bottom line. Every delayed decision means lost revenue, increased risk, and frustrated customers. The process is particularly taxing for fintechs and fast-moving lenders, where rapid decision-making is a competitive advantage.

Joseph Zhou, Pranjal Daga, and Yutong Pei, Accend’s co-founders, recognized the need for a better system. Instead of relying solely on AI or human effort, they built a hybrid model that ensures both speed and precision, addressing the key barriers that have made AI adoption slow.

Accend’s approach is straightforward: leverage AI where it excels—automating data extraction and analysis—while ensuring human oversight for verification. This combination guarantees 100% accuracy, making it a viable replacement for manual processes that have persisted for years.

• AI Handles the Heavy Lifting – Accend’s AI rapidly spreads financials, extracting data with high precision and generating credit memos faster than any manual approach.
• Human-in-the-Loop Review – Expert analysts validate AI-generated outputs to ensure absolute accuracy, solving the trust gap that has slowed AI adoption in finance.
• 10x Faster Underwriting – By eliminating redundant manual work, underwriting teams can significantly reduce costs, errors, and approval times.

“Our customers consistently tell us that they’ve been searching for a solution like this for years,” says Pranjal Daga. “By combining AI with human validation, we’ve finally built a tool that credit teams can trust. It’s not just about speed, it’s about getting financial data right every single time.”

For credit teams dealing with large volumes of financial statements, the results are already speaking for themselves.

Russell Gu, Head of Credit Risk at Slope, shared his experience using Accend’s platform:

“Accend offers the best solution for data-driven credit teams looking to maximize insights from financial documents. Their API solution and onshore time zone support accelerate financial review more than 4x.”

Gu highlights the challenges that many credit teams face today: “Underwriting processes are outdated, with analysts spending hours manually extracting and spreading financial data. This not only slows down approvals but also introduces a high risk of errors. With Accend, we’ve been able to cut down our financial review time significantly, allowing us to make faster and more accurate credit decisions.”

Companies like Slope, Pleo, Rho, and Evergrow have reported an 80% reduction in application processing times, significantly enhancing their credit underwriting and onboarding efficiency.

Unlike other AI applications where minor errors are acceptable, financial statement spreading demands near-perfect accuracy. This has historically kept AI adoption in underwriting at bay—credit teams cannot afford miscalculations. Accend solves this problem by ensuring every financial spread is reviewed and validated by expert analysts.

This hybrid approach does more than just speed up processes; it instills confidence in AI-driven underwriting. Financial institutions that have hesitated to integrate AI into credit risk analysis now have a solution that guarantees accuracy while delivering measurable cost and time savings.

Accend is built for credit leaders who need both efficiency and precision in their operations. Whether it’s banks, fintechs, or alternative lenders, the solution enables underwriting teams to move faster without compromising on accuracy. The ability to generate credit memos 10x faster allows teams to focus on higher-value activities rather than repetitive data entry and validation.

“We knew there had to be a better way—one where accuracy meets speed,” says Accend co-founder Joseph Zhou. “Credit teams today spend an incredible amount of time manually processing financial statements, leading to delays, errors, and inefficiencies. Our solution allows them to move faster without sacrificing precision.”

The launch of Accend’s AI-powered Financial Statement Spreading & Analysis solution is more than just another AI-driven product hitting the market. It signals a shift in how credit underwriting will be conducted in the future. Accend’s model challenges this hesitation by proving that AI, when combined with human oversight, can outperform traditional methods in both speed and precision.

To showcase the impact of its new solution, Accend is offering the first financial spread and analysis for free. Credit teams interested in seeing how AI can transform their underwriting processes can reach out to Accend’s team or book a direct consultation.

“With Accend, your teams can focus on…what truly matters—making smarter lending decisions” says Pranjal.