There’s growing frustration among CIOs at banks and credit unions. They’re hamstrung with maintaining existing hardware and software, and are busy patching their legacy back-end technology systems together instead of innovating and delivering user-rich digital experiences. They have almost no control over the rate of progress – or their overall digital banking roadmap.
According to the Harris Poll, most consumers (58%) say they’d prefer to use community and regional banking providers. Unfortunately, many of these institutions are light years behind the giant multinational banks when it comes to offering digital banking services. The trend of consumers leaving for financial institutions with better digital capabilities is growing – and consumers are taking their deposits with them.
This is not good news for community banks and credit unions. Board members are more closely scrutinizing their digital banking capabilities as a KPI to recruit and retain customers. This is especially critical as the inability to quickly meet customer demand for digital banking services directly impacts the bottom line.
That’s why in today’s landscape, there are really only two models for the survival of banks and credit unions: digital-first banking or digital-only banking.
Below are four essential focus areas to help banking CIOs move faster, help their organizations deliver better, more secure digital banking services, as well as provide innovative user experiences to attract customers (and deposits). As it turns out, these focus areas also make digital banking more cost-effective overall through a more streamlined and efficient system.
As banking systems move from proprietary, siloed services to globally accessible applications, it’s a good practice to use “open banking” services via secure standardized APIs. Europe, particularly the U.K., has taken the lead on promoting open banking and consumer choice through regulation, and Asia Pacific banks are rapidly following this trend. Banks and credit unions in the United States however, have a long way to go to catch up.
Organizations should aim to adopt secure and scalable API management and open banking solutions while avoiding cobbled-together systems that create ever-increasing complexity when functions are later augmented and built upon. Oftentimes, such inflexible systems bring unexpected consequences.
When considering the rate of adoption in the industry, we are seeing more and more institutions invest in digital-only channels and, in some cases, multiple digital channels that target specific demographic groups (e.g., Millennials).
Technology evolves with increasing velocity, yet there are certain universal and enduring truths that never change – among them is the fact that there will always be a criminal element in human society. Similar to the bandits that attacked travelers along the road in ancient times, thieves live among us today, both in person and through digital channels. Digital banking has attracted a new category of hackers who work in large groups, are highly organized, and operate like regular businesses. In order to defend against this, digital banking security must be baked into the solution at each and every access point.
As banking becomes more digitized, exposure to fraud grows alongside it. To effectively counter intrusions, banks should utilize a layer of security measures that address the key vulnerabilities of any digital banking system. These measures should include comprehensive app and data protection, user and device digital profiling and identification, protocols such as ‘know your customer’ (KYC) validation, biometrics, and both real-time and forensic fraud detection.
For example, geotagging is being developed as a security measure. Should a seemingly suspicious international transaction take place, banks and credit unions can, through geotagging, immediately verify whether a customer is actually travelling abroad. They can also reduce false alarms that can trigger the automatic locking of customer accounts when customers are indeed travelling overseas (and may be inconvenienced by the disruption).
Additionally, there are security benefits through AI and machine learning, which are highlighted next.
AI is quickly becoming what the cloud was five years ago – and is on its way to being the de facto standard for financial institutions. While many financial institutions use chatbots, this is only one application of AI.
A Fannie Mae survey revealed that 40% of mortgage lenders are using predictive modeling and machine learning for tasks such as detecting potential defaults and notifying loan specialists to contact borrowers at opportune moments, things which result in more efficient application processes, often the cutting time by a week or more.
AI will have a transformational impact on financial institutions across the globe and will ultimately become a dividing line between the winning and losing banks. According to the research firm Autonomous Next, AI adoption across the banking sector could reduce costs for U.S. financial organizations by approximately $450 billion by the year 2030. Most experts agree that AI’s full power is yet to be harnessed. There are implications in nearly every banking department, including compliance (suspicious activity reports, anti-money laundering activity, audits), risk mitigation, fraud detection and customer care (both front office and back office).
An often-overlooked use of AI is identifying sales opportunities (especially during the onboarding process) and analyzing patterns and trends that help financial organizations create efficiencies. AI can help identify loans, CDs, and other products that mesh with the customer’s profile and present those sales opportunities at appropriate times.
Used in the right way, AI can be remarkably effective, yet I offer two cautions when entering the AI space: Set the right foundation with data integrity and metrics, and never expect AI to perform like a real human. Prior to attempting any modeling, it’s absolutely crucial that financial institutions concentrate on getting the raw data, metrics and compliance factors (such as data privacy)100% accurate. Additionally, it is important to remember that AI falls short in situations that require more nuanced customer interactions. Organizations should not use AI when a live teller or loan officer is the more appropriate channel.
Some banks and credit unions have addressed the distinction between the two modes by integrating options for customers to opt away from AI and interact with a real person. The main idea here is for customers to be in control of when that switch takes place. On the back end, an effective digital banking system will also offer banking representatives the same ability to seamlessly move access channels and retrieve a customer’s transaction or process, which is often midstream when the customer initiates direct contact. Knowing when – and how – to effectively toggle between digital and live channels delights customers while improving back office efficiency.
Many financial organizations are tied to multi-year contracts with their legacy systems. Multiple years can be an eternity in a world where consumer expectations evolve constantly, and financial institutions that want to compete effectively should consider centralized, integrated digital banking solutions that incorporate all facets into a single, unified system.
Today’s transition is not nearly as difficult as it was in the past. New digital channels and API layers enable organizations to simultaneously upgrade their legacy systems, which continue to function in place while bringing new digital functionality to market much faster, and with far less disruption.
Financial institutions that are forced to use “bolt-on” solutions with existing back end systems in order to add features will quickly find themselves lagging behind others that have centralized functionality under one umbrella. These centralized solutions are empirically more efficient, and typically include things like security, identity management, rich aggregated analytics, alert management, systems management, fraud prevention, AI/machine learning and open API management.
In closing, today’s banking CIOs are under pressure to lead digital banking innovation in their organizations. Many CEOs and Boards expect CIOs to transform their organizations’ digital banking footprint more quickly, and with antiquated systems and equipment. CIOs are being forced to keep pace – not only with competing financial organizations, but with the best mobile and online process systems offered by Amazon, Starbucks, or Facebook.
By focusing limited time and resources on API, security and AI, and with the ultimate goal of seamlessly integrating onto one platform – CIOs and their IT teams can retake control of their digital banking innovation’s roadmap and be far more agile now and in years to come.
Steve is a seasoned product manager for DBX digital banking at Kony, responsible for the entire portfolio of banking applications, including Retail Banking, Business Banking, Loans, onboarding, digital banking platform etc. He has over 30 years’ experience in technology and software development and has a unique mix of business process and technical skills that help create unique innovative Customer experiences and industry solutions. Before Kony, Steve has also held CTO and senior R&D roles in both major corporations like IBM and Shell and innovative startups.
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