The Finance Tech Stack: Opportunities for Innovation (Part II)

  • ERP/Accounting: The ERP/general ledger is the backbone of the CFO’s tech stack, connecting financial information across business processes and accounting sub ledgers.
  • Payroll: Software used to manage employee information, payroll and benefits. This may be integrated with the HRIS, or separate. The system may be owned by HR, but Finance will interact heavily with it as personnel expenses are a large part of a company’s overall spend.
  • FP&A: Software used to track business KPIs, and make decisions around budgeting and forecasting.
  • Spend management: Software used to manage vendor spend and employee expenses.
  • AP/AR reconciliation: Software to manage complex AP/AR workflows and reconcile large volumes of invoices.
  • Bookkeeping/Financial Close: Software that helps companies close the books every month. Includes workflow/task management tools, reconciliation and reporting.
  • Equity management: Software that helps companies manage their cap table and investor relations.
  1. Better financial planning & analysis: The majority of planning and analysis takes place in Excel and Google Sheets today. Even companies using advanced tools like Anaplan or Adaptive Insights will default to Excel for certain parts of the process. While Excel is beloved by finance teams for its flexibility, it has significant shortcomings around collaboration, real-time updates, and versioning. We see an opportunity for companies to build automated workflows on top of Excel or create end-to-end solutions that obviate (or drastically reduce) the need for Excel altogether. We also believe data analytics using advanced tools like SQL and Python will become an increasingly core skillset for FP&A teams. The worlds of FP&A, BI, and data science are colliding — especially in consumer businesses. We are bullish on software that anticipates this shift and helps non-data oriented FP&A folks make the transition more easily.
  2. Expediting the close process: Today, a company often does not have a clear picture of its P&L for the quarter until halfway through the following one. This makes it very difficult to be agile and react to the changing realities of a dynamic business. The reality is that preparing monthly financial statements is still a time-consuming and manual process. For most companies, the default way to get to a quicker close is putting more resources on the problem, but this introduces its own set of issues. Manual steps like downloading transactions and reconciling paper invoices make the process error-prone. Tools like Blackline help expedite this for large companies, but they tend to be expensive, clunky, and require heavy implementations. We believe there is an opportunity to develop lightweight workflow tools that streamline the most painful aspects of close: invoice and spend reconciliation.
  3. Enabling real time spend management: Related to the previous point, a major point of frustration for finance teams is around spend management. Tools like Divvy have been successful because they do a great job of helping finance teams set centralized spend limits and track expenses against budget in real time. However, other parts of the process like data entry and classifying transactions require significant manual effort, creating lags in visibility into critical COGS items. We believe there is an opportunity to leverage ML/AI to create tools that can ingest data from various sources, identify anomalies, and automatically pull in the appropriate entries into Netsuite or other systems.
  4. Sales and cash flow forecasting: Sales forecasts influence critical downstream decisions. However, accurately forecasting sales (and therefore cash flow) is tough, especially for businesses without subscription revenue. One CFO of a transactional consumer software business shared with us that 70% of the company’s revenue for the year is done in a span of three weeks. In order to accurately forecast, such companies have to develop manual workarounds which involve downloading data 2–3x a day from billing systems and running static Excel analyses on them. It’s critical for early stage companies, too, to know when they are about to run out of cash. We believe there is an opportunity to build tools for the finance team that can take predictive modeling to the next level.
  5. Additional fintech products: More and more, we see an opportunity for companies in the space to not only offer SaaS tools but also to insert themselves into the flow of funds. The most obvious example here is in spend management — companies like Divvy and Brex make the majority of their revenue through interchange. In addition, once a company has visibility into the cash inflows and outflows of its clients, it is in a good position to offer financial products like working capital, lending and insurance. For instance, a tool that does cash flow forecasting may be able to proactively recommend working capital solutions or even offer those solutions themselves based on access to a company’s past financials. Brightflow.ai is one example of a company that aspires to make this shift, and we see many more going in this direction.

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Medha Agarwal

Medha Agarwal

Currently @RedpointVC. Former founder, ops, and consultant. Proud @HarvardHBS @Harvard @Radlwtcrew @Bainalerts alum. Recovering New Yorker, currently loving SF