share
Accelerate Data Innovation with Real-Time Financial Services, an essential white paper companion highlighting the challenges of legacy infrastructures and opportunities made available by real-time data, is now available. Download for free below.
Banks and financial institutions face exceptional challenges in today’s fast-paced digi-sphere. The meteoric rise of digital communications and evolving customer behaviors have propelled digital products from the periphery to the center. Success hinges on the quality of the customer experience.
To compete, financial institutions must provide an array of real-time services to meet an expectation that’s been developed by the digital era and accelerated by the pandemic: customers demand a seamless omnichannel banking experience.
The curtain may not have fully closed on in-person interactions, for they still remain a crucial aspect of banking, but today’s market demands revolve around speed and accessibility, requiring financial institutions to pivot towards digital banking.
This requires stark transformations in many areas of the customer experience, including how users interact with the bank, how digital products are purchased, how portfolios are accessed, and how customer support is provided.
But for banks, this poses one serious challenge: the rigidity of their legacy IT systems means they have problems with scalability, flexibility, reliability, and complexity. Fintech start-ups created in the cloud have a modern architecture that gives them the agility to adapt to market trends, the flexibility to innovate, and the opportunity to maximize the user experience.
In contrast, banks are bearing the weight of a cumbersome architecture that leaves them heavy-footed as opportunities pass them by. This is problematic because today’s tech-sphere has shaped customer expectations in almost every industry, making them accustomed to fast, easy, and accessible digital products.
Meeting these demands is synonymous with the adoption of digital products, a reality that highlights an advantage that fintechs have over banks – banks have only dipped their toes into digital waters, fintechs were born in them.
As a result, creative fintechs are turning heads in today’s marketplace because of their ability to provide a fast, seamless, personalized, and easily accessible financial service. Banks and financial institutions must embrace cloud and microservices architectures that use real-time data to maximize the user experience and ultimately meet customer expectations.
Below we’ll reveal how real-time data can accelerate the modernization of banks and surpass consumer and business expectations.
Customers across all demographics want fast, easy, and simple access to their finances through digital doorways. Being the first digital generation, millennials are more intertwined with digital technology, demanding a firmer grip on their finances with a few taps on their smartphone.
Older generations have the same expectations but for different reasons. Digital banking is a safer way for the most vulnerable to access their finances in the pandemic. Equally, people with mobility issues can circumvent the challenges of in-person visits just by going online or via an application.
Yet the greatest of these expectations is for digital banking to be absolutely seamless. This means that real-time data isn’t expected, it’s demanded, and users won’t tolerate an omnichannel experience that’s decimated by lags or inconsistent interactions due to the lack of a standardized data layer.
The reality is that even though customers favor banking through digital channels, they often prefer face-face-to-face interactions when committing to more complex financial products. Mortgages, loans, and investments – these are all examples of when the human side needs to be a part of the banking experience.
Research shows that banks are more likely to maximize sales when combining the human element with digital channels to produce a more complete banking solution. One European bank experienced consistent sales growth of up to 20% over two to three years. Around 60% of active customers leverage digital channels (online and mobile) and 80% of all touchpoints occur on digital.
However, only 25% of sales are made online or via mobile (20% online, 5% mobile). Now, although digital channels have revamped the banking experience, and customers have welcomed and adapted to this, many of the conversions still happen in-branch or on the telephone.
Customers expect to use different channels depending on their objectives. They do research, gather information on investments or loans on the website, discuss with a banker or advisor the different options, and finalize the transaction over the phone, email, or in-person. Often, they then hop onto the mobile app to check status or balances and then chat with support if they encounter any issues.
But banks may have ended up with disparate databases for each channel that was developed. Without a way to integrate the siloed data or use a unified data layer to present the 360 views of customer data in real-time, customers will face an incoherent experience when moving between the different channels.
Moreover, providing a seamless user experience isn’t just table stakes for banks anymore – deficiencies in any channel are enough to create friction and encourage customers to go to competitors.
Research suggests the bar has been set and it’s sky-high:
Transitioning from legacy IT systems to modern cloud architectures won’t happen overnight and will be a long process for many traditional banks. But the adoption of a unified real-time data layer that acts as a superhighway from the backend systems to customer-facing applications will give banks the speed and flexibility to innovate with digitized products and services. It also provides an omnichannel experience, and ultimately meets customer expectations all while this transition takes place.
But creating real-time customer experiences requires a real-time multi-model in-memory database. Using one that can provide the necessary data with low latency and high read/write throughput will revamp the customer experience from top to bottom; lags will be eliminated, all interaction channels will be cohesive, promoting a seamless experience. Users will be able to instantly access their account information on their mobile devices wherever they are.
In addition, users can instantly search through their transaction history or understand where they are spending too much on their credit cards with an in-memory database that supports secondary indexing of their datasets and can query and aggregate the data in a fully distributed manner in real-time.
For traditional banks, the returns can be astronomical. The adoption of a real-time data platform paves the way for an omnichannel platform that will transform the customer experience in a way that builds their trust, engagement, and loyalty. This results in better customer retention, acquisition, and enhanced brand reputation, which in turn lead to growth and fending off those fintech disruptors.
Today’s tech environment is moving at such a pace that yesterday’s data is old enough to be stale and inaccurate. Acting on these insights is enough for an opportunity to slip by or for a hidden inhibitor to hamper the user experience. All it takes is a lag to create friction, two to create frustration, and three to kill the experience altogether.
This places banks in a very uncomfortable position. IT legacy systems are inherently rigid and lack the scale and flexibility to quickly unearth, filter, and streamline unstructured data in a way that’s optimal for analysis. Cloud-based architectures, on the other hand, provide fintechs with instant access to accurate data.
The accessibility of these cloud-based architectures gives fintech the upper hand over banks when it comes to data analytics. When fintechs are analyzing, banks are still gathering. When fintechs have spotted a new opportunity, banks are still searching for it. When fintechs are innovating, banks are still guessing.
To level the playing field, banks must integrate a database that can power real-time analytics. This is an indispensable asset that allows analysts to respond instantly to customer preferences, negative feedback, and fix errors before they linger long enough to contaminate the user experience. With real-time analytics, banks can discover which products users are interested in or how users interact with their products at that precise moment in time so they can recommend new products or services.
This takes a lot of the guesswork out of the personalization process and allows banks to create digitized products that are more closely aligned with customer needs and preferences. But this is only the tip of the iceberg; trends can be detected instantly, important performance indicators can be monitored, and points of engagement and disengagement can be identified as well as areas of strength, mediocrity, and weakness.
Fintechs are basking in a hotpot of data innovation, partly because of their ability to micro-measure experiments when innovating new ideas. Leveraging real-time analytics sets up the perfect conditions for experimentation because analysts can instantly gauge what’s working and what’s not.
New ideas can quickly be refined, tweaked, and tested in shallow waters before being thrown into the deep end. Banks will then have the ability to tailor the banking experience based on user behavior and create a product that resonates with their target market.
Financial markets are volatile and always susceptible to unexpected fluctuations. A political event, a pandemic, or even a tweet from Elon Musk is enough to give them a shake.
As these markets ebb and flow with international events, portfolio managers are closely analyzing which investment opportunities will generate the best returns for their clients. New investment assets like cryptocurrency (Bitcoin for example) are set to be mainstream. Sudden fluctuations in the markets open just as many doors as they close. For a trader to capitalize on these investment opportunities, they need to make decisions that are based on reliable and accurate market data.
But in today’s fast-paced environment, the speed at which data is accrued has a large bearing on the quality of data – decisions made on minutes-old market or pricing data can lead to severe losses. To stay ahead of the curve, portfolio managers must leverage real-time insights and risk calculations to move with the market’s rapid movements instead of playing catch-up.
Using real-time analytics, portfolio managers can see the potential gain or loss made from an investment decision at that precise moment of time. These potential gains or losses will recalibrate within each notch in an investment asset (stocks, options, commodities, futures, etc.) price. This minimizes risk by allowing traders to know when to cut their losses, reacquire stock or even capitalize on a window of opportunity before it closes.
We also can’t ignore the unprecedented influx of new users due to fintech apps like Robinhood and others entering the market in recent years. The industry has become more cutthroat, more competitive, and more unpredictable. And given that market values fluctuate on a dime, traders must leverage real-time data to make quick, calculated decisions on price moves to maximize returns for their clients.
Banks and financial institutions need to modernize to meet modern-day expectations. Customers demand the seamless user experience that’s provided by innovations from the fintech disruptors. Legacy IT systems and Relational Database Management Systems (RDBMS) are still the backbone and system of records for many banks and will take time to update. A solution is needed which enables them to innovate and respond to customer expectations without disrupting these legacy back-office systems.
A real-time modern data layer provides a fast and powerful solution that many banks can pivot to while making the transition to cloud-based architectures. Redis Enterprise can accelerate this process by supplementing banks with a real-time database that guarantees real-time customer/client experiences.
Stop testing, start deploying your AI apps. See how with MIT Technology Review’s latest research.
