Data Driven Decisions in the Banking IndustryMay 22nd, 2019 by Alex Brockman
First of a three-part series revolving around #Data and it’s impact on the Financial Industry.
As the amount of organic data produced annually rises each year, it is imperative for the banking industry to materialize their data strategy. AT Kearney surveyed bank account holders and showed they trust their primary financial institution twice as much as Google and three times as much as Facebook to safeguard their most sensitive information. All the while, banks control 1/10th the amount of data Facebook has on the average client, and 1/9,000th the amount Google stores.
2018 saw the most breaches of confidential records breached with nearly 6.5 billion accounts from companies like Yahoo, Equifax and Facebook making headlines. The phrase “data security” was mentioned more than at any time in history during the Facebook “Cambridge Analytica” senate hearing. These events have led to record low trust levels in the big tech companies.
So, if data is so vulnerable, and so valuable at the same time, what are some of those market advantages to be realized? Institutions can leverage all the data from their swath of products and platforms to:
- Better understand spending patterns of their customers
- Customer Segmentation – Personae Creation
- Fraud: Management, Prevention, Risk: Assessment, Compliance & Reporting
- Customer Feedback Analysis & Action
Better Understand Spending Patterns of Consumers
Influencer Jim Marous says banks need to do three things for their customers to create a market advantage in today’s economy:
1. Know Me
2. Anticipate My Needs
3. Reward Me
These factors are all iterative and change as clients’ lives and lifestyles change. Some of the data points are paychecks amounts, saving/spending tendencies during holidays, and investment during varying market conditions. All these factors should be calculated and analyzed for relationship deepening opportunities, which doesn’t mean more products. Wells Fargo is evaluating all the monthly recurring payments account holders make and putting them up in their mobile app so that their customers can see if they are spending/wasting money.
Customer Segmentation – Personae Design
The financial industry has often aspired towards client segmentation, but the formula was typically to take the most profitable 20% of the client population, then model their offerings around what they want and need. This has been expanded from geographic to demographic, psychographic, and now, customer personae. The international design firm NewGround recently developed the first set of financial industry specific personae to better understand their customer’s behavior and motivation to provide a deeper engagement in the eventual place of business. Client and market data are being used every step of the way to create alignment between what the market needs, what the institution offers and how those offerings are delivered.
Fraud & Risk
Transaction data can be leveraged to understand where clients spend their money, when they access funds, what types of habits they fall into, etc. When deviations occur, the institution can proactively reach out to the client to determine if fraudulent activity is occurring or if it is a unique event. Tapping into the credit history and looking holistically at long term trends can more accurately allow a bank to position lending opportunities to applicants and prospects. Employing big data algorithms also allow banks to minimize overhead by detecting/fixing compliance, audit and reporting issues.
Customer Feedback Analysis & Action
We live in the connected world of social media and online platforms. Mostly every institution has an online banking website, and most have adopted mobile applications as well; both of which feature feedback/chat functions for clients to get help or leave a comment. Using big data tools can amalgamate this information with social media and online mentions of their brand to appropriately engage with those audiences. This type of interaction is being adopted by many in the banking industry, sometimes poorly, but a great example is of a small $250M community bank in Edmond, OK. Jill Castilla has gone ‘all-in’ and is sought after as the model for future banking relationships.
Banking has historically been an in-person, transactional service. As the world shifts those transactions to technology channels, big data will play a significant role in the financial industry’s ability to anticipate and deliver market demands. The amount of organic data produced annually continues to climb, so this is not an issue the industry can ‘bookmark’ any longer.
- How to use Big Data in the Banking Industry
- Financial Industry – Data Visualization