Revolutionizing Financial Services Using the Power of Data Science and Automation

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Over the past year, the pandemic has forced businesses to quickly adapt to a new operating paradigm. But even before Covid, finance departments faced growing challenges driven by ever greater business and operational complexity. As the vaccine rollout continues and allows countries to lift restrictions on the pandemic, the world is slowly but steadily moving closer to something akin to normal. Many executives take this time to examine their businesses and think about how they too can “build back better”. Now is the time for financial services to digitally transform.

Finance is responsible for one of the most important assets of a business: its money. He is responsible for ensuring the financial health of a business by performing a range of essential tasks including payroll administration, budget and cash flow management, keeping meticulous records of corporate assets and liabilities. business, paying the right amount of taxes and complying with regulations. The digital transformation of the financial department offers the opportunity to close, consolidate and report faster and with increased accuracy. It frees up resources associated with repetitive manual tasks, while reducing operational costs and increasing efficiency.

However, there are three common barriers to digital transformation within financial services: 1) increasing data complexity, 2) lack of accessible and user-friendly technologies, and 3) lack of skilled data workers. Data science and automation are now essential to enable new forms of data interaction and use, with education and skills enhancement a key ingredient to accelerate transformation.

On average, data workers tap into more than six separate data sources, 40 million rows of data, and seven different outputs to perform even a simple analysis. Multiply that by the many analyzes that every finance team must perform, and the data challenges grow exponentially.

In addition to increasing data complexity, many businesses are stuck using outdated legacy systems that are too complex for average employees to use, or simple spreadsheets that are prone to errors and lack proper controls. . According to IDC, $ 60 billion is wasted every year in the United States because of data workers such as finance professionals spending hours and hours on spreadsheets. The point is, with the vast amounts and increasing complexity of digital data, there is only one way for an organization to stay ahead: data science and automation.

This is a great opportunity for strategic CFOs and finance thought leaders to rethink the status quo and start transforming digitally. According to IDC,
the use of modern data science and analytics enables financial services to complete financial forecasting 74% earlier, make decisions 25% faster, and improve financial reporting accuracy by 16%.

By investing in more robust processes and leveraging modern, easy-to-use technology designed specifically for data science and automation, financial services can better meet today’s challenges. With the evolution of technology, a wave of smarter, more accessible data systems can be deployed by any organization to harness the power of data and automate manual processes to emerge actionable insights. Automated analytics workflows can enable organizations to speed up manual processes such as collecting and sorting the data needed for reconciliation, and to work more efficiently by freeing up staff to work on more creative tasks or at work. added value, such as identifying future sources of income.

Additionally, data science powers advanced analytics, which can help analysts spot unexpected connections within datasets, solving problems such as fraud detection, audit investigations and more. advanced analytics where visualizing data in a connected way can reveal new insights.

Unfortunately, as more companies recognize the power of data science, they face another challenge: the lack of data scientists. Due to the high demand, there is now a global shortage of data scientists in the job market. According to Quanthub, that shortage has grown to 250,000 by 2020. With such a significant shortage of established data scientists, bridging the digital divide and strengthening the skills of the existing team is the next logical step in leveraging the network. current business environment. Upgrading the skills and empowering workers of today can compensate for the bottleneck in the talent pipeline, but companies that don’t take advantage of the available data-driven insights will be left behind.

Improving skills goes hand in hand with any transformation journey. Any business undergoing transformation must also invest in its workforce and career prospects, not only to encourage a comparable investment on its part in your business, but also to make it feel more valued and knowledgeable about it. digital. Empowering those close to a process – those people who know exactly where the problems lie – are in the best position to turn raw data into information. Finance employees also have key foundational skills, such as strong analytical skills.

The end goal is to ensure that more people in the organization have access to usable data – an environment in which employees can improve their own digital culture.

By fully embracing digital transformation, data science and automation, the finance department can dramatically reduce the cost of processes, while successfully redeploying talent to value-added activities. While the past year has been a challenge, the future is full of opportunities.

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