Before working in data, I was a personal banker for several banks and a credit union. Yes, I was the person you would see if you wanted to open an account, apply for a credit product, or ask questions about your accounts. And yes, people still go to their banking branch! I met often with customers to understand their needs and make appropriate recommendations based on our discussion. As a result, I developed deep relationships with customers and built trust.
As someone who has seen behind the “veil” of modern banking and now works in data services, I see many opportunities for banks to make better use of their data. The two most important areas of opportunity are customer insight and fraud detection. As we move quickly into the digital age, financial institutions must deeply understand their customers and their behavior.
According to McKinsey, 71% percent of consumers expect personalized interactions and 76% are frustrated when this does not happen.In banking, it’s increasingly easy for personalized interactions to go by the way-side. If a customer speaks to a banker, that individual may not take the time to forge a connection or personalize the conversion. However, more and more often, the entirety of the banking experience is digital. Your customer may go months or years without speaking to a banker. As a result, your staff needs to be equipped to make infrequent interactions count, and banks must go above and beyond to ensure that their digital interactions with customers are powered by individualized data strategies.Fraud, too, is a growing phenomenon for banks and their customers. In 2022 alone, 65% of credit card holders were victims of fraud —an increase from 58% in 2021. As fraud becomes more prevalent, financial institutions must take the necessary steps to implement modern technology that can help combat fraud. In this post, I’ll explore how modern banking institutions can improve customer experiences and combat fraud by leveraging the power of their data in the Snowflake cloud.
Getting to Know Your Customer
In my banking days, I loved building relationships with customers and gaining their trust by recommending solutions for their financial needs. However, in this digital age, banking customers may not have a specific banker they see with their financial questions. They’re more likely to do everything from their app.
According to Finextra, as institutions grow and customers begin relying more on digital and mobile banking, it will be harder for bankers to know who has visited their bank and who relies solely on their mobile platform. Whether their customers are banking digitally or visiting a branch, there are huge opportunities for banks to collect valuable data–if their data systems are in place.
When customers visit a bank branch, they’re often asked the standard list of transactional questions. These routine inquiries can be time-consuming and tedious. How many times have we all had to fill out the same form? It’s off-putting, and consumers are tired of it. Banks with sophisticated data architecture can eliminate redundant questionnaires and allow their bankers to focus on the customer experience.
When banks are able to train and alter expectations such that their employees serve as the human face of their organization, they gain a significant advantage over the competition. The rarity of in-person or phone interactions means that they matter more. Your customer is likely to carry that experience with them for years to come. Equipping bankers to respond quickly and effectively to customer questions, with data at their fingertips, will be the secret ingredient that allows financial institutions to retain satisfied customers and expand accounts.
Understanding Customer Needs
In my time in banking, I saw customers develop strong relationships with local bankers. Often, this relationship meant that the customer’s banking needs could be easily met. But what happens when their banker retires, or moves to a different office, or calls in sick? When only a single individual understands the customer, you put your institution in a position to deliver inconsistent, or at worst, bad service.
Relying on a Customer360 platform would allow any banker within the office to understand the customer’s finances and make personalized recommendations quickly. By looking at the 360 profile, bankers can sit down with a customer who rarely visits an office, understand their financial situation, and skip those redundant questions. Diving directly into those most important, meaningful questions can help the banker find the best solution for the customer at hand. This will bring back the “personal” experience when talking to a personal banker.
Extend this beyond the realm of the physical bank, and you’ve created a digital experience that makes people feel seen and understood. As a result, bankers are able to deepen customer relationships and build trust.
What the customer really wants is to have a personalized plan for the problem they are facing. If, throughout the process, there is a product that may help them in another way —great! A Customer360 approach would be revolutionary for a financial institution because it can provide timely and personalized recommendations based on the client’s history.
Data cloud platforms like Snowflake make Customer360 infinitely scalable for financial institutions. Innovations like data clean rooms and zero copy clones offer secure cloud options for the banking industry to build complex systems that process, analyze, and make good use of their customer data.
Helping Customers (and Banks) with Fraud
Another issue that I found frustrating was the amount of fraud that customers had on their accounts. As a banker, dealing with this was very disappointing. Not only was the customer unhappy with their card or account being compromised, but rectifying the issue usually took time. Finalizing the paperwork would take me about thirty minutes to an hour, in most cases.
On top of this, sometimes new accounts needed to be opened, or a new card had to be printed. Such cases happened pretty frequently.Throughout the process, the customer often lost trust in the bank. Until that point, they’d assumed their funds were secure. But with 65% of cardholders experiencing fraud each year, eradicating fraud remains one of the biggest challenges in the financial industry.
Fortunately, it is possible for institutions to utilize their data to build a model that can detect fraud–often long before it happens. Why should they do this? About 54% of people have said they have encountered fraud when shopping online. Successful monthly fraud attacks have increased from 43% to 48% for mid to large retailers and 27% for smaller businesses.
Online transactions have increased since the COVID-19 pandemic, incrementing the number of fraudulent transactions. As fraudsters are becoming more savvy in their tactics and using new ways to commit fraud, it is up to the bank to make sure they are protecting their customers.
The old way of catching fraud (sometimes this is as basic as having a person in the fraud or operations department sift through transactions) is not enough. Without a data-driven fraud detection model, the process of detection fraud is too time consuming and prone to human error. So, how can data improve fraud detection methods?
Correctly implemented, fraud detection that leverages artificial intelligence can be incredibly effective. One Denmark-based bank migrated to a machine learning system for detecting fraud that yielded a 50% increase in detected fraud and a 60% decrease in false positive cases of fraud. A PYMTS study offered similarly positive results. Financial institutions leveraging ML and AI saw a 64% increase in customer satisfaction.
Creating data-driven models that run on AI and ML offers significant benefits for banks, improving overall security and safety while making customers feel comfortable about how their bank handles their data. Scammers are using more advanced techniques to commit fraud, and financial institutions need to use advanced technology to protect their customers and the bank itself.
The Modern Data Stack and Hakkoda
The banking industry is behind other fields when it comes to leveraging sophisticated data systems. One survey found that 95% of global banking executives believe legacy systems and outdated core banking systems are preventing them from capitalizing on the use of their current data.
A modern cloud system, such as Snowflake, coupled with a modern data services provider with deep expertise in the financial sector can allow banks to take full advantage of their data. Migrating to the Snowflake cloud eliminates data silos, and with a central storage location, Hakkoda’s data experts can facilitate deep analysis that allows financial institutions to unlock the power of their data. With modern capabilities like Customer360 and ML-backed fraud detection, banks are able to deliver a more personalized approach to their customers while protecting individuals and their institution. Contact a Hakkoda expert today to begin your data innovation journey.