What’s Next in Digital Transformation: Data-Driven Decision-Making

Amid changing economic conditions, leaders at banks, credit unions and other financial services companies should capitalize on the digital transformation that their institutions have been undergoing in recent years and ensure that they can generate the kind of timely and actionable data they need to make well-informed decisions.

Recent turmoil in the banking sector has elevated the risks facing financial services companies industrywide and accelerated their need to boost their data and analytics capabilities.

Banks, credit unions and other financial services companies already faced numerous economic and market challenges, including higher interest rates, inflation, margin compression, regulatory pressures, workforce shortages, shifting customer expectations, and increasing competition from nontraditional service providers. While inflation is expected to slow, the Federal Reserve recently affirmed long-running concerns about the potential for an economic downturn. The Federal Open Market Committee predicts the failures of Silicon Valley Bank and Signature Bank in March likely will contribute to a recession later this year. (More recently, First Republic Bank, which, like Silicon Valley and Signature, suffered a massive deposit run, also failed.)

Executives at banks and other financial services companies must ensure their institutions stay on top of evolving challenges. Using data and analytics to monitor trends, project the potential impact of various changes, and determine how best to respond is vital.

Many institutions have begun a digital transformation over the last few years, working to automate processes and enhance digital services for customers. Leaders should build on that momentum and implement predictive solutions to address economic turbulence in 2023 and beyond.

Three steps financial institutions can take to help drive success are:

  • Prioritize data as a critical component of strategic decision-making
  • Leverage analytics and reporting to inform strategic initiatives
  • Utilize artificial intelligence (AI) to grow efficiencies

Read More: What the Data-Driven Bank of the Future Looks Like

Prioritize Data as a Component of Strategic Decision-Making

Financial institutions have no shortage of data. To be successful, however, leaders must ensure they have the right data, and that they are using it to make timely decisions. They need to identify what data their business needs and build data literacy across the organization so that individuals at all levels can benefit from data-driven insights.

Other industries have demonstrated the power of data in driving success. Take the sports world, for instance. In the late 1990s and early 2000s, Oakland Athletics’ General Manager Billy Beane integrated data and statistical analysis into the team’s recruiting strategy to identify undervalued players. The team’s subsequent success — including 11 playoff appearances during his time as GM — was detailed in Michael Lewis’ book, “Moneyball.” Prior to Beane, baseball felt lightyears away from the data realm. Now, use of data and analytics is the norm in baseball and the practice has permeated many other sports.

Data Drives Success:

Bankers should take a lesson from Billy Beane. Using the right data to make timely decisions improves an institution's agility and performance. This advantage is all the more important at a time when clarity is hard to come by.

Adopting a more modern data strategy would allow the leaders of financial institutions to make more accurate, insightful decisions that result in more efficient budget planning and operations, among other benefits.

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Leverage Analytics and Reporting to Inform Strategic Initiatives

A primary challenge to overcome is knowing how best to use data and how to make the data come to life. By leveraging analytics and reporting for comprehensive insights, financial institutions can move beyond just crunching numbers and give leaders access to actionable data that can inform their decisions.

This is crucial for financial institutions to build agility, especially in today’s uncertain economic climate. Leaders need to assess the full breadth of data the institution has access to, identify what data is key to monitoring institutional performance, and how best to organize that data, track trends, analyze those trends, and report results. In some cases, analysts may need to drill into data down to the transaction level to gain a deeper understanding of underlying factors behind specific trends.

“By leveraging analytics and reporting for comprehensive insights, financial institutions can move beyond just crunching numbers.”

— Eric Wheeler, Syntellis Performance Solutions

As a case in point, many banks saw deposits increase as businesses, families, and individuals limited spending during the COVID-19 pandemic. But deposits have been draining away since then, especially following consumer concerns about the recent bank failures. Many banks are running promotional deposit campaigns in response, offering customers signing bonuses or other perks to open new accounts or make regular deposits. Robust analytics and routine reporting allow banking leaders to actively monitor the performance of such campaigns to see where and when they need to adjust to reduce financial risks and increase chances for success.

Dig Deeper:

Use Artificial Intelligence to Improve Efficiency

Artificial intelligence, or AI — which is generally part of digital transformation efforts already — has the potential to help financial services companies automate data analysis and streamline manual tasks, improving productivity across the organization. This allows valuable human resources to focus on other priorities.

For example, banking institutions could automate daily data loads and analysis in their reporting systems. This provides finance and executive leadership teams with actionable reports on the latest balance sheet inflows and outflows to support any funding decisions they might need to make for that day.

In addition to automating daily reporting, the planning process should include the ability to model different scenarios, such as interest rate changes or other planning growth assumptions. Finance teams can automate the process to transfer base-level assumptions between different scenario models and execute analyses. This ensures more efficient and effective processes so leaders are not caught off-guard when managing through shifting markets and interest rate environments.

Digital transformation will continue to propel the financial services industry forward. To keep up, leaders need to prioritize data as a critical component of strategic and financial planning. By leveraging analytics and reporting for more informed decisions and using AI to improve efficiency, institutions can stay ahead of the curve and drive sustainable and successful outcomes despite changing economic conditions.

About the author:

Eric Wheeler is the director of product management at Syntellis Performance Solutions.

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