The finance and accounting departments at many top-tier financial firms are undergoing a major evolution right now.
With the rise of financial technologies and data analytics, there are new opportunities for finance and accounting teams to automate routine tasks, integrate systems, and leverage data to provide more strategic value to the business.
While this transition can be challenging, the payoffs for companies can be tremendous in terms of improved accuracy, efficiency, and new business insights.
In this article, I provide a complete guide on how decision makers can evolve their finance and accounting business functions in ways that will set them up for future growth and success.
By embracing automation, integrating systems, aggregating data, leveraging analytics, and incorporating data science, financial firms can reshape their finance and accounting departments into efficient, agile, and strategic assets.
Read on to learn key steps finance leaders can take today to drive this evolution and position their teams for the future.
Automating Manual Processes
Many finance and accounting processes are still done manually using Microsoft Excel or related spreadsheet software.
Tasks like financial reporting, account reconciliations, expense processing, and invoicing are time-consuming and prone to errors when done manually.
There is a hidden efficiency and accuracy cost associated with using human capital to do these repetitive tasks month after month.
By automating these processes, finance teams can reduce labor costs and improve accuracy right now.
For example, automating trade reconciliation can significantly benefit an investment firm’s middle office by streamlining the process of matching trade details between the firm’s internal records and external sources.
By implementing automated reconciliation today, the firm can promptly identify and resolve discrepancies, minimizing the risk of errors and delays.
This, in turn, enhances operational efficiency, reduces manual workload, and ensures timely and accurate trade settlements, ultimately fostering a more seamless and efficient middle-office operation.
Integrating Systems and Data
Most companies use a myriad of different systems to manage finances, from accounting software to OMSs, ERPs, CRMs, HRIS, and more. Unfortunately, data is often fragmented across these systems.
By integrating systems and centralizing data, finance teams can gain a more holistic view of the organization.
This aggregated data can uncover trends and insights that would be nearly impossible to see when data is siloed.
Finance should play a key role in system integration efforts to ensure quality data flows.
For instance, investment firms utilize a wide range of systems including portfolio management systems, order management systems, risk analytics, accounting platforms, and more.
Unfortunately, critical data is often fragmented across these disparate systems, presenting major challenges for reporting and analysis.
By integrating core platforms and centralizing data into a CRM or data warehouse, investment firms can gain a single source of truth right now.
This aggregated data provides portfolio managers, analysts, and executives with complete visibility into performance drivers and risk factors across the business.
In addition, system integration allows seamless data flows between platforms, reducing manual efforts to reconcile data.
With comprehensive data integration, investment firms can uncover key insights, monitor positions in real-time, and make better informed strategic decisions.
Leveraging Power BI / Tableau / Other BI Tools
Data analytics allows finance, investment and accounting teams to go beyond traditional reporting and begin performing advanced analysis to drive business decisions right now.
Power BI and other business intelligence tools allow investment firms to perform sophisticated data analytics and uncover actionable insights from their financial data.
By connecting to diverse data sources from across the enterprise, Power BI provides portfolio managers and executives with interactive dashboards and visualizations to analyze performance trends, model different scenarios, and identify new opportunities.
Advanced features like forecasting, sentiment analysis, and natural language queries enable users to go beyond traditional reporting. Investment firms can leverage Power BI to conduct attribution analysis, optimize asset allocation models, detect market anomalies, improve risk management, and quantify drivers of returns.
With user-friendly interactive reports, investment teams can drill down into details, uncover correlations, and collaborate to gain valuable perspectives for decision-making.
The robust analytics and visualizations from Power BI, Tableau and other BI tools empower financial firms to become more data-driven.
Incorporating Data Science
While analytics focuses on past trends, data science leverages statistical models to gain deeper insights into real-world business problems right now.
Finance and accounting could partner with data scientists to tap into leading-edge techniques like multivariate regression, scenario modeling, Monte Carlo simulations, natural language processing, and more.
For example, these advanced methods can help optimize pricing, improve demand forecasting, analyze customer churn, and enhance financial modeling.
Drawing insights from both internal and external data allows finance to reduce uncertainty in planning and better quantify opportunities today.
Becoming a Strategic Advisor
As finance and accounting teams shift from number-crunchers to data-driven strategists, their role within the enterprise becomes elevated.
Finance and accounting are uniquely positioned to advise on major corporate decisions due to their enterprise-wide view, analytical capabilities, and ability to quantify business impacts.
By partnering with business leaders and operating divisions, finance evolves into a trusted partner that helps guide strategic moves to maximize growth and profitability right now.
This strategic role relies less on manual processes, and more on data synthesis, visualization, storytelling, and influencing skills.
Enabling the New Operating Model
It’s important to note that technology alone cannot unlock lasting value – it requires a new operating model.
Key roles like Data Engineers, RPA Developers, and Integration Architects must be introduced.
Agile methodologies like Scrum and Kanban facilitate collaborative, iterative work. A CoE drives standards, best practices, and training.
With self-service reporting and chatbots answering queries, less time is spent on repetitive tasks.
Staff is freed to focus on value-added analysis, modeling, and strategic initiatives.
This ultimately pushes finance and accounting from back-office function to strategic advisor.
Overcoming Evolution Obstacles
This finance and accounting evolution journey has challenges.
Legacy systems can require difficult, risky upgrades to enable automation and integration.
Data quality issues like inconsistencies, inaccuracies, and duplication must be resolved.
Organizational resistance to new ways of working must be overcome with executive sponsorship, change management, and reskilling programs.
There are also cybersecurity and regulatory considerations arising from opening systems and data.
However, leading financial institutions recognize the vital importance of modernizing their finance and accounting function.
They forge ahead with careful planning, staged roadmaps, and end-user engagement.
The Future of Finance
Although this evolution poses challenges, leading finance teams are already automating processes, aggregating data, and applying sophisticated analytics.
Those that embrace these changes will thrive as stewards of business intelligence, while laggards will be mired in manual tasks and siloed data.
To stay competitive, CFOs must actively adapt their departments by investing in digital tools, analytical talent, and new ways of operating.
While the future of finance looks quite different, those companies that evolve their finance function into a strategic asset will gain a distinct competitive edge.