Even as the U.S. continues the difficult process of re-opening, most of us are still experiencing a semi-cloistered life and will be for some time, with many companies continuing with remote work and consumers hesitating to return to old routines. Surviving the core of the pandemic, we have relied on our internet-connected world for just about everything. And that’s one thing that isn’t likely to change, even when we will have more freedom to roam — there’s no going back.
Businesses increasingly depend on technologies like artificial intelligence and data analytics as workers and consumers continue to manage corporate and personal finances remotely. The financial services industry has been forced to revamp its methods more than most. This will require relying even more on data to inform decisions regarding the reinvention of services, infrastructure, and management.
Reinvention of Mobile Services Through Data Analytics
The most urgent challenge for the financial industry is the shift of more services to mobile. Consumers depend more than ever now on smartphones and tablets, and banks and credit unions must adapt to the needs of people who continue to want to use services digitally. Consumers also increasingly depend more on their mobile devices as digital wallets. But they want and need security when banking digitally.
This transition to a more mobile banking structure is made seamless and secure by using data in a compliant and efficient fashion. With data minimalization, retail banks only use the data necessary for each consumer and base this information on user behaviors, allowing the institution to offer the right services for each consumer. Through data analytics, institutions can process real-time indicators of each consumer’s financial health.
In the process of digital transformation and specifically when moving to digital services, software designers and IT engineers often want to include all the bells and whistles around new technologies when they should be focused on the solutions needed most — how to store data, how to classify data, and how to best use data so the customer is getting a personalized service that works smoothly.
Marketing teams should ensure they have a seat at the digital transformation table to ensure that the data they need to deliver a one-to-one experience can be factored into the design. If a financial institution can’t design a system that is agile, as well as personalized, consumers won’t use it and will look elsewhere.
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Taking A Closer Look at the Data Infrastructure
While the migration to mobile financial services is the most urgent need, the financial industry was already building a data infrastructure before the pandemic changed the world. AI technologies and the move to cloud computing have given financial institutions a head start in creating a digital ecosystem that meets customer needs. As a result consumers already have remote access to their financial data and institutions can scale the vast amount of data they collect.
However, this digital transformation still has room for improvement when it comes to predictive analytics and extrapolation of insights from the data. Retail banks can take a page from the health sector’s use of data. The healthcare industry is relying on big data to track the path of the virus and communal spread, as well as understanding the symptoms and the virus’s DNA in order to develop a vaccine and test for antibodies.
In a similar way, financial institutions could leverage aggregated data to improve response time for applications. These are examples in which having the right data-driven approach could help shorten response times, increase efficiency and consumer convenience. Data-driven insights can help banks and credit unions mitigate risk, and provide support for customers in those locations where a resurgence in COVID-19 could delay businesses reopening and employees returning to work.
How Data Analytics Will Help During Reopening and Beyond
Every industry is going to have to make adjustments to revive and survive in post-COVID-19 society. Retail banking has the technology foundations in place with its digital transformation migration, but now more than ever it need to invest in a more robust data strategy in order to better understand and meet the personalized needs of a customer and business base that is now managing finances remotely on a more permanent basis. Data analytics will drive the mobile and other digital options to allow for loans, the ability to get credit approvals, and simple bank transactions.
Technologies like artificial intelligence and machine learning will streamline the process, and emerging storage options will allow for more agility in how data is processed and shared.
Here are three data-driven strategies to implement:
• Robust data collection: How are consumers interacting with your apps? What is your typical hold time at your call centers? What type of metadata are you getting through partnerships with retailers? Go beyond collecting the data you need today, as often the value of a given data set emerges over time.
• Enrichment: While retail banks certainly have rich data sets about their customer’s purchase histories and financial backgrounds, frequently that data is insufficient. To better understand and serve consumers, enrich your data sets with third party information to help with strategic initiatives.
• Transparency: As data becomes more plentiful and regulations require it, it is important to make it easy for people to understand and obtain a copy of the data that has been collected that is related to them. Transparency is important to establish and maintain good will and will help ensure you are aligned with future regulations.