What does "Monopoly" have to do with Big Data and Banking Today?

Piggy Bank lost in the Woods of Big Data

Everyone’s familiar with trading properties, picking up "Chance" cards, and exchanging colorful fake money during the game of Monopoly. For many of us, this simple board game was our first introduction into handling cash and doing our best to invest it wisely. Monopoly continued to entertain and educate us with the early millennium release of the Electronic Banking Edition, where card transactions replaced traditional dollar bills. Who doesn’t love a board game that includes fun tech-gadgets and still lets you play with money?

Technology has not only influenced the game of Monopoly, but also the banking industry, where changes in their infrastructure and management practices happen quickly due to an increasingly technological society. In fact, according to Booze Allen, over 50% of money center banks (those that borrow and lend with governments, large corporations, and banks) have listed technology and infrastructure as a top priority for 2014. This is a necessary priority across the industry, which is already being utilized by the world’s largest banks with a lot of capital. However, smaller community banks must also continue to meet regulatory requirements and distinguish themselves from competitors to increase profits in the same way that their larger competitors are, by embracing emerging technologies and data analytics. Banks that utilize data analytics to meet all of their business goals will undoubtedly have the competitive advantage within their markets.

Today’s community banks face issues much larger than not being able to "pass Go." Whether a bank is looking to reduce churn, increase lending, or monitor their regulatory compliance, they can distinguish themselves from competitors using Big Data analytics. Data management within community banks has often been viewed as a burden rather than an opportunity, because of presumed associated costs. However, data analytics doesn’t have to mean, "breaking the bank." The goal of any analytics initiative is to hopefully result in a ROI for the client. That starts with banks asking the right business questions and taking advantage of data analytics opportunities to find patterns, trends, and ultimately the most complete, accurate answers to those questions. This will be the competitive edge and the future of successful banking.

To increase profitability and their competitive edge, banks should use data analytics to tackle the issue of customer churn. This challenge has consistently proven to be one of the leading and most costly problems facing community banks. Banks must invest significantly more money on initiatives to acquire new customers, retain existing ones, and even more money to re-acquire customers that have already left. Banks could immediately increase their revenue by using data analytics to focus on reducing churn. By fully understanding their customers based on the bank’s own data, they could predict why and when a customer is going to leave the bank before it occurs.

So why haven’t more banks pursued this easy enough (Monopoly-proof) solution? Why haven’t they been able to reduce their churn rates and increase revenues with all of today’s technology? The challenge of implementing this type of strategy lies in the volume and variety of data that a bank has spread across many databases and systems. This makes it nearly impossible to analyze and retrieve customer interactions and actionable insights through conventional data management technologies.

Money center banks have already dedicated technology and teams of data scientists to remedy this issue and utilize data analytics. Although they have the resources to use these tools (thus giving them a seemingly competitive advantage), money center banks do not need to hold "monopoly" over the industry. Community banks can also use Big Data technologies to stay competitive! If community banks compile their data efficiently and cost-effectively, they will have an "x-factor" in their ability to acquire local non-bank data. Integrating this public data with their own customer data gives them a hugely competitive advantage, as they’re able to "pass GO" and become the data-driven personal banker in today’s digital age.