We’ve all gotten the email: “Rates are going up! Act now!” or “You’re stuck in debt! Merge your bad debt into OUR personal loan”. This blanket marketing approach —resorting to a generic snail mailer or a blast email— has been the go-to strategy to almost every lending institution in the country for decades.
But in today’s market, you’re looking for personalisation. There’s no room for cookie-cutter messaging or one-size-fits-many campaigns. Banks and lenders have all the data they need to drive campaigns to the individual. Understanding their needs and situation helps create more effective products and campaigns.
The shift towards personalisation in banking and financial services responds to a new era in data. It also marks a departure from legacy technology and banking core platforms. Such changes need a different approach —but how? Let’s explore the digital transformation in banking and how you can overcome the most common hurdles to embrace innovation.
A Digital Transformation in Banking Is Here Today
The traditional banking industry has embraced a sales-oriented approach. Its focus has been on offering services via face-to-face customer service. Back in 2016, a whopping 60% of the population preferred visiting a physical branch to open a new bank account.
Traditional banking’s physical-based distribution also explains why such institutions still rely on legacy technology and platforms. Banks have been used to people reaching out to them, not the other way around.
And that might be the main difference between traditional banks and the banking industry of the future. This new generation of banks and banking platforms establishes closer relationships with customers. How do they do this? By including advisory, wealth, investment services, and checking and savings accounts.
Fintechs, Neobanks, and Big Tech now enable a decision engine and insight model based on digital distribution. This has allowed them to offer a full set of banking services and embrace full-service requirements and regulations.
A Return to the Basics
Banks and credit unions must re-dedicate themselves to getting to know their customers. They’re doing this while expectations are at an all-time high and disruption is waiting in the wings.
Building more meaningful relationships requires banks to take a step back. Knowing who their customer base is, what interests them and what do they value is the first step towards creating a new sales journey. At the heart of driving relationships over transactions is data. Taking into account a person’s attitudes, milestones, technology preferences, and even their interaction history before offering a new service is important.
Leveraging data to shape client experiences brings forth an important caveat: customer information must stay secured and not be shared. Banks and credit unions must navigate the risks of identifiable data. Once way to elevate social consciousness on data privacy and protection. Banks should also focus on enforcing security, data safety measures, and establishing best-practices.
Telling the Entire Story
Traditional banks have information on all the stages of the customer journey. Yet this sometimes doesn’t cover the modern personal data profile. Information about the sales cycle, inquiry, servicing and other areas can play a relevant role.
Industry disruptors, on the other hand, look at sentiment, attitude, and interactions. These create better customer and member experiences. They also generate trust while providing innovation at a rapid pace.
The modern data ecosystem provides more order and insight for a digital transformation in banking. A modern data stack suggests four phases: chaos, order, insight and innovation. Along the way, financial services professionals can gather a clear vision of what their customers need and how they can help.
What the Digital Transformation in Banking Looks Like
In a chaotic data environment, Excel is king. Banks and financial institutions rely on three activities. These refer to Excel document sharing, in-house and core banking applications, and point solutions. Any experimentation with data sciences goes without a strategic approach. Thus, automated solutions still rely on manual middle and back office operations.
Transitioning to a more organized scheme requires centralizing data warehouses. A digital transformation also involves standardizing tooling and creating broad data literacy, access and effective storytelling. Creating effective insights, however, takes order to the next level. Think implementing API/EDI connectivity to second and third parties. You can automate middle office functionality with cross-system integration and process alignment, and implement standardized reporting that complies with regulations.
The final step in your data innovation journey may include embedded apps blending internal and point solutions. These combine external data sharing to fuel revenue streams and insights. This allows rich data insights to pivot towards which haystack has the needle and where it’s buried.
How Hakkoda Helps You Get Started
Begin your digital transformation today. We’ll leverage data engineering, data science, and even data-driven full-stack application development.
