Revolutionizing Financial Service with the Power of Data Science and Automation

Over the past year, the pandemic has forced businesses to quickly adapt to a new operating paradigm. But even before Covid, financial services faced growing challenges from ever-increasing business and operational complexity. As the rollout of the vaccine continues and allows countries to lift pandemic-related restrictions, the world is slowly but surely moving closer to something resembling normal. Many leaders use this time to review their business and think about how they too can “build back better.” Now is the perfect time for financial services to digitally transform.

Finance is responsible for one of the company’s most important assets: its money. He is responsible for ensuring the financial health of a company by performing a range of essential tasks, including payroll administration, managing budgets and cash flow, maintaining meticulous records of assets and liabilities of business, paying the right amount of taxes and ensuring regulatory compliance. The digital transformation of the finance department provides the ability to close, consolidate, and generate reports faster and with increased reporting accuracy. It frees up resources from repetitive manual tasks, while reducing operational costs and increasing efficiency.

However, there are three common barriers to digital transformation within finance departments: 1) growing 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 upskilling being key ingredients to accelerate transformation.

On average, data workers leverage more than six distinct data sources, 40 million rows of data, and seven different outputs to perform even simple analysis. Multiply that by the many analyzes every finance team must perform, and the data challenges increase 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In addition to increasing data complexity, many businesses are stuck using outdated legacy systems that are too complex for average employees to use, or simple error-prone spreadsheets that lack proper controls. According to IDC, $60 billion is wasted each year in the United States due to data workers such as finance professionals who spend hours upon hours buried in spreadsheets. The fact is, with the massive amounts and explosive 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 begin digital transformation. According to IDC, using data science and modern analytics helps finance departments make financial forecasts 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 uncover actionable insights. Automated analytics workflows can allow organizations to speed up manual processes such as collecting and sorting data needed for reconciliation and to work more efficiently by freeing up staff to work on more creative or value-added tasks. , such as identifying future revenue streams.

Additionally, data science powers advanced analytics, which can help analysts spot unexpected connections within datasets, solving problems such as fraud detection, audit investigations, and other types. advanced analytics where viewing 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 high demand, there is now a global shortage of data scientists in the job market. According to Quanthub, this shortage has grown to 250,000 in 2020. With such a significant shortage of established data scientists, bridging the digital divide and honing the existing team is the next logical step to take advantage of today’s business environment. Upskilling and empowering today’s workers can offset the bottleneck of the talent pool, but companies that don’t take advantage of available data-driven insights will be left behind.

Improving skills goes hand in hand with any transformation journey. Any business undergoing transformation should also invest in their workforce and career prospects – not only to encourage comparable investment on their part in your business, but to make them feel more valued and digitally literate. Empowering those closest to a process – those people who know exactly where the problems lie – are best placed to turn raw data into insights. Finance employees also possess key foundational skills, such as strong analytical skills.

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

By fully embracing digital transformation, data science, and automation, the finance department can significantly 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 opportunity.

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