The New Reality: What Banks Need to Meet the Covid-19 Challenges?

Digital banking

October 24, 2020//-From the first reactions and wave of responses we have seen from the banking industry, IDC has identified certain requirements that are critical to responding to the challenges of doing business in 2020 and beyond.

Banks that already have or are working toward the development of these capabilities will mark themselves as having technology capabilities that allow for enhanced resilience and the ability to face the extraordinary challenges of 2020.

These will also place them on a strong footing to build off these investments and drive themselves forward for the future.

Channel Upgrades

For many, the experiences of 2020 have involved losing almost all access to physical banking services. Although many banks have already made significant investments into channel upgrades, there are still processes that may require branch visits for origination or final verification.

Branches have seen a pressing need for upgrades to further drive efficiencies at physical locations, allowing for more efficient and effective servicing of customers.

Technologies such as facial recognition as customers enter the branch allow the identification and automatic preparation of VIP and urgent customer records.

Footfall sensors allow staff to optimize resources where they are needed best and customer flow to be streamlined across counters.

Simpler customer needs can be redirected to automatic kiosks whereas more complex needs can be addressed by human tellers.

Digital payments are another key part of service offering at the disposal of banks. With usage of mobile payments rising by as much as 60% in Q1 in some markets in Asia/Pacific according to IDC research, support for such payments is a must.

Driving new payments revenue means increasing connectivity in other channels such as ecommerce, sharing economy and digital media subscription services.

Adopting a fully featured payments engine that can allow for such connectivity as well as allow payments data to be collated will ensure that banks do not miss out on the customer engagement and revenue possibilities, especially with over 30% growth in digital payments expected globally in 2021 according to IDC research.

As one of the final pieces of the digital puzzle, onboarding customers remotely remain challenging in some environments because of regulation.

However, in many jurisdictions, regulation has loosened in the light of the development of secure and tested eKYC systems.

Fully digital onboarding has become even more vital as digital channels take front stage as the primary route for all banking activities.

The KYC portion of the process which is often heavily scrutinized by regulators can be enhanced for security by running multiple checks against various databases.

Artificial intelligence (AI) can play a significant role in facial detection accuracy by allowing for more precise verification and for identification of unusual behaviors beyond the normal parameters of legitimate customer acquisitions and for earlier fraud detection and alerts.

 

Communication Rethink

This year 2020 has seen banks become vital sources of information and support during a crisis.

People have relied on their banks to continue to keep them funded and financed but this period has revealed cracks in the communication strategies of some banks, as they have fed their customers with disparate and sometimes conflicting information regarding important issues such as implementation of loan moratoriums.

It must be noted here that fintech companies are often cited as being better in this aspect, being more up to date with their information as well as allowing for more relevant and customized messaging to be pushed to users.

For banks, their communication has often been siloed and they will need to understand the confusion and unsatisfying customer experience this brings.

The call center and other remote banking technologies serve as a key channel for dealing with more complex issues and must also not be neglected.

Call centers as the hub of the remote banking experience for the customer are still often a source of frustration for many customers.

Technology for the call center however can allow for many steps to be taken to remedy this situation.

AI controlled voice assistants which can measure voice sentiment allow calls to the center to be assessed and prioritized based on tone and cadence of the caller speech.

This allows emergencies to be recognized and acknowledged for expedited processing.

Automated voice assistants now have also reached the level where they are now able to truly mimic human conversations for certain requests, allowing for many of the simplest and most common queries to be handled by a robot and settled in a highly satisfactory manner.

The call center is also tied in directly to backend platforms which include information unified from other channels — meaning that calls into the center will also be able to resolve issues and problems which have been originated on other channels.

During the pandemic challenger banks across regions such as Europe and Asia have demonstrated a system of daily communication with customers that was clearly differentiated.

Daily email blasts with titles like “How to save money during lockdown”, “Top jobs growing during Coronavirus” and “Top Spending Hacks to make your money last” all demonstrate a different engagement style for pure-play challengers versus incumbents.

Incumbents tend to communicate with customers primarily around transactional activity and marketing, like next best offers.

Challengers see email, notifications, and app engagement as relationship opportunities. Incumbents have often held off on such more relationship driven engagement as it conflicts with the role of the branch and call-center, but more significantly they have underdeveloped digital due to internal channel bias.

Infrastructure Overhaul

The functions of the bank today perform highly specialized roles which necessitate the banks workings to change to match this differentiation.

Key to these conversations has been that of cloud usage and of being cloud ‘native’.

Firstly as a means of flexible storage allowing institutions to access resources beyond their physical assets and now as a full platform of services and tools which enable bank to have quick access to analytic tools, development tools and other functionality such as AI on tap, without having to make their own separate investments in such software.

Flexible capacity for development work, testing and simulations mean that new products can be rolled out and brought to market at an accelerated rate, bypassing the need to wait for internal resources to be freed up first.

The DBS Bank in Singapore has been highlighted globally for its aggressive aims to increase cloud usage internally and move away from local storage and capacity.

The DBS Bank previously set targets for 50% of its applications to be able to run on public cloud by 2018 and reduce their servers by 80% by 2019 as it drove applications and workflows to the cloud.

New banks set up as ‘virtual banks’ such as Monzo bank and Fidor bank have taken much pride in leveraging cloud systems to create new institutions.

Cloud in banking remains varied and a mixture of public, hybrid and private cloud for different situations.

According to relevant regulation will provide banks with a balance of the best benefits and security that is needed for financial data and transactions.

The benefits of moving toward increased cloud platforms are sometimes highly notable, the DBS Bank reporting a 71% decrease in system incidences, despite a 166% increase in operating systems – improvements attributed to the stability and simplification of systems which cloud platforms offered them.

Cloud is not optional or for secondary non-critical systems at this juncture. The pandemic situation of 2020 has proven to be a testing time for internal controls and cyber security for many financial institutions.

Threat profiles have changed due to both internal and external factors and weaknesses have been exposed in the behavioral history method of detecting fraud which has spurred banks to think how they could improve in security and controls to better account for undocumented behavior in general while maintaining service levels and security standards.

Banks have looked to see how AI and machine learning (ML) can be further applied to account for such unpredictable swings.

AI techniques can be used to quickly remodel situations based on recent events at a quicker pace than using more traditional analysis and simulation trials.

AI and machine learning (ML) allow banks to be able to quickly identify the key trends present in data and extrapolate the key patterns which make up the data set.

This allows banks in turn to quickly reconfigure and scale up their analytical models to account for the latest behavioral data. While obviously very useful during the pandemic situation, beyond 2020, banks which have mastered these skills will be able to leverage them in future situations to attain heightened levels of alert detection and response actions.

Data and Analytics Redefinition

The importance of data as one of the key factors in defining a ‘digital bank’ has been something which most if not all banks have firmly embedded into their digital transformation programs.

However, with the advent of the pandemic, historical behavior models have been rendered far less useful in predicting for future behavior.

There has in effect been a reset on the global economy and consumer behavior has been fundamentally altered.

Credit history, scorecards and risk analysis from the previous year will no longer be able to produce accurate assessments when so much has changed which may include factors such as income, employment status, disposal income and debt levels.

To this end, banks will have to quickly learn to get more comfortable working with more recent sets of data from perhaps the past 6 months and using these to formulate their analytical models.

Starting with a smaller data set and building up effective analyses through rigorous cross analyses of this more manageable pool.

Dashboards which allow for real-time overviews of key data statuses and which are available organization wide will allow for this effective collaboration to reconstruct the value of data within the banking organization.

Further to this, deferred loan repayment schedules as well as the obviously higher possibility of defaults and non-performing loans mean that bank reserves and capital levels have come under new pressure to remain with working and regulatory limits.

In general, running stress tests in banks is both time consuming and resource intensive. Digitalizing these processes in order to cope with a number of different scenarios which are often required by regulators such as those within the US and Europe allows for banks to free up resources for what can be a particularly high workload when done through traditional more manual methods.

One other area that could significantly help both customers and banks during the long recovery period from the economic effects of COVID-19 is a different approach to default.

Today most banks simply wait for loan defaults, and then pass it to the collections team, threatening customers with a credit score hit or the like.

A better use of data analytics capability would be to identify customers with potential of default risk and engaging them in a proactive deferral or payment modification scheme to both reduce collection costs and build long-term customer loyalty.

During the pandemic we saw most US banks unwilling even to consider deferrals — this will likely hurt them medium-term in respect to brand.

With this change, banks should switch to less emphasis on historical data and length of time as a factor and more on drilling down in resolution, breadth and on learning to use not just internal data but external data.

Stress testing simulations are often cited as one of the most computationally demanding tasks that banks need to process and AI and ML can help in identifying, selecting the correct inputs and then calculating the effect on reserves in the event of a crisis scenario.

Vendors with experience in AI and ML can often assist banks which may have the correct direction they would like to take their models, but do not have the experience or know-how of how to translate that into a working model.

Furthermore, the power required for stress testing has become a key area where cloud storage has often proven to be invaluable.

Banks can use cloud resources when they need the extra computational power for testing and are then able to offload this elastic increase in bandwidth upon completion.

This cloud approach brings huge cost and scalability benefits compared with having resources dedicated on-site.

Workflow Reimagining

Many banks have had to quickly grapple with most of their staff working from home and have had to redesign security around workflows to enable secure communications and productivity.

Creating new HR and work platforms to support this new virtual office. Beyond this common example however, banks will need to instigate major cultural change that can foster collaboration and break down legacy barriers and thinking.

The culture of innovation must be a core part of the businesses mission and instilled from the top-down. The DBS Bank here has been highly notable for its long transformation and a key highlight of its transformation plan was its intention to benchmark their progress not against other banks but against key tech companies globally, including giants such as Amazon, Facebook and Netflix.

Identifying their desire to go beyond what their industry is offering and offer leading experiences across technology.

A process which can benefit highly from this collaborative thinking is loans processing. In many loan applications, manual documents still need to be scanned or verified for credit checks.

However, fully digital loans processes for loans such as personal loans are now possible and involve the usage of technologies such as robotic process automation (RPA) to automate manual workflows without having the need to overhaul current systems used for loans applications.

For those who do wish to use a new system end to end however, there are many platforms now which enable the loan process to be handled fully digitally with little to no human intervention.

eKYC using biometrics, video recordings and AI can handle the KYC element, whereas automated processes that have direct links to customer databases and external credit bureaus allow many more parts of the loan to be handled digitally.

Finding new ways to perform workflows has been a key trait of banks which have managed to stay engaged with their customers throughout 2020.

As another example where legacy services can be reimagined for the digital age, in wealth management, long cited as an area which banks can leverage technology to decrease costs, while at the same time making them much more accessible to the general public, AI tools are able to scan external markets and offer timely and relevant advice similar in nature to that offered by human advisors.

Often called ‘Wealth-Tech’, such efforts have been highly successful such as Acorns, Robinhood Markets and Stash Wealth.

Key to their success has been offering modern and intuitive apps which allow for smaller and more rapid purchases of investment products such as funds and stocks, coupled with AI engines which offer potential investment advice to users.

Innovation Acceleration There are also innovation driving technologies which serve as platforms to create totally new possibilities across banking and the wider financial services industry. For example, we are only beginning to see the role that 5G plays across commerce.

With max transfer speeds of up to 4.6 Gbps or 6.5 Gbps depending on band, the potential for new services to be built on top of such networks is immense.

Much in the same way as the sharing economy and mobile video market were created and enabled by 4G, 5G will bring about its own wave of innovation, possibly in the form of augmented reality (AR), virtual reality (VR), and other technologies.

For banks, 5G will power much of the next wave of Internet of Things (IoT) and we will start to see further implementations and advancements of existing technologies such as branch connectivity, AI in facial detection, and real time calculation of customer options.

One of the unique features of 5G networks is “priority guarantees.” Guaranteeing that network bandwidth is available for critical applications means that 5G can be used where currently only wired connections are possible due to mission critical workloads.

This can be used in further implementations to allow for sophisticated remote banking and eKYC platforms, highly functional mobile workspaces and smart branches.

Along with 5G, blockchain and distributed ledger technology (DLT) are two of the key technologies which truly have the power to change almost everything. The immutable ledger which allows for almost bulletproof security has usages in almost every industry from retail to mining to of course banking.

The Bank of China in Hong Kong is already using blockchain technology to process their real estate valuations for mortgages.

A succinct solution to a process which usually requires massive amounts of documentation and verifications from a large number of different parties, it is the perfect use case for blockchain and an effective tool for reducing the manpower and effort hours needed for such transactions.

Italy is also one of the first countries to have a working interbank reconciliation system in place and live with its “Spunta Banca” project.

Curled from Banking Industry Rises up to the New Normal 2020 report

 

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