How Purpose-Driven Banking Can Drive Customer Trust

Over many decades banks and financial institutions have invariably focused on shareholder interest - they have considered 'Volume is King' as a success mantra but they now need to think beyond that. Banks are increasingly under the pump to respond to growing demands from customers and communities to think beyond profitability and come up with initiatives for the well-being of the society. This is where it makes sense for banks to hop on to the 'Doing Well By Doing Good'bandwagon. Banks are cognizant of the fact that merely helping customers take smart financial decisions cannot be their only prime focus in the long run. The global banking space is evolving at a fast clip, and want to bank with organizations that not just operate with the highest integrity but also infuse substantial socially responsive investments.

Realization has dawned among banks that their business strategy must revolve around setting and attaining societal goals by driving convergence between their business performance and the larger interests of the society. Such an approach can help banks emerge as socially responsible organizations. 'Doing Well by Doing Good' isn't about banks doing the right things for the customer and the society - such purpose-led banking initiatives can enable banks to unlock substantial value and competitive advantage besides helping them secure their continued existense in an uncertain future. 

The importance of 'Doing Well by Doing Good' is not lost on banks but it cannot be denied that banks have made tardy progress in walking down the 'Doing Well by Doing Good' road. This is largely owing to their overwhelming focus on delivering shareholder interest. It is crucial to note that banks while adopting a purpose-driven banking approach need to rewire its entire business and there is a degree of reluctance among banks to take this route since it involves a large strategic transformation, espeically during pandemic times. According to a Deloitte survey, 87% of executives believe companies perform best over time if their purpose goes beyond profitability. Another research study revealed that 72% of consumers are more likely to be loyal to companies that lead with purpose.

Banks are indeed taking purpose-driven banking seriously. Swedish automaker Volvo announced that it will phase out all petrol diesel, and hybrid options and only sell electric cars by 2030 in its quest to reduce greenhouse gas emissions. Oversea-Chinese Banking Corporation (OCBC) framed a policy to stop funding coal-fired power plants owing to climate concerns and improve the society by donating money to philantrophies every year. Capital One, Ally Bank, and Alliant Credit Union waived overdraft fees - a move that is sense a huge sigh of relief for customers already bogged down pandemic-related challenges. Mascoma Bank also resorted to purpose-driven banking and provided its employees paid time-off for voluntering. 

Banks must not merely straitjacket themselves toward delivering financial services and must demonstrate committment to make a positive impact on the customers. Banks can do well by doing good by leveraging customer data and act as trusted advisors of their clients on budgeting and spending, helping them skirt detrimental spending habits and protecting them from bad actors. Of course, all of these can be achieved by banks by harnessing the power of Artificial Intelligence, Machine Learning, and cloud services. These emerging technologies aid banks to understand customer behavior and help them take smarter and safer financial decisions at all times, while providing cushion against any financial crime.

The bottom line is banks must put their thinking cap beyond profitability and carve out initiatives for the betterment of the society. And by doing so banks can strengthen customer loyalty and accelerate their ROI.   

Robotic Process Automation: Driving Operational Efficiency and Improved Customer Experience for Banks

There is a heightened focus today across the global banking sector on leveraging new-age technologies to stay ahead in a highly competitive marketplace. This is largely because the banking sector has been under a great deal of stress to optimize costs, boost productivity, address the shortage of skilled resources as well as deal with the ever-increasing employee costs. Further, the sector is grappling with other issues such as payment of regulatory fines and slow working procedures that have resulted in a significant amount of customer dissatisfaction. All these have posed roadblocks for the banking sector to offer reliable and more secure banking services to its customers.

The rapid shift from traditional banking to digital over the last few years or so has been accelerated by the growing need for banks to look for cost-effective and fast alternatives with their larger objective of accelerating operational efficiency through an improved customer experience. Robotics Process Automation (RPA) is being seen as the game-changer for the sector as it provides banks with the much-needed alternative to enhance their competitive edge.

The Covid-19 pandemic may have thrown normal life out of gear but it has led to a proliferation of digital banking services, which is poised to be the future of the banking sector, wherein RPA is the enabler banks need to offer low-cost and high-quality services without compromising one bit on security. According to a study conducted by McKinsey, up to 25% of banking processes are expected to be automated over the next few years – what’s more, RPA software for the banking sector will post a business revenue of $900 million by 2022. These projections indicate the impact Robotics Process Automation will have on the sector and help banks not just augment their operational efficiency but also build goodwill among their loyal customers.

So why has Robotics Process Automation generated so much buzz for the banking sector? Well, it can be attributed to the myriad benefits this automation technology offers. RPA has the potential to swiftly execute customer-facing as well as back-office tasks, ranging from sending emails, opening & closing applications, and transmitting information from one system to another. It obliterates manual, repetitive work that reduces the productivity of banks, minimizes the occurrence of risks, and engages customers with real-time scenarios, helping deliver an augmented customer experience. The best part about embracing RPA is that it requires minimal investment as banks do not need to modify their underlying legacy IT infrastructure.

Challenges in Adoption of RPA

Of course, there are challenges that come in the way of RPA adoption such as resistance to change, process standardization & organization misalignment, compatibility with legacy infrastructure, and lack of legal regulations governing automation. But the benefits of RPA far outweigh these challenges.

How Robotic Process Automation Can Drive Value for Banks?

Let us take a deep dive into how RPA can help scale up the efficiency of the banking sector.

Driving Customer Service to the Next Level

A large chunk of customer grievances across various customer service centres is repetitive in nature. The sight of long wait times and delays on the part of banks to provide information can be frustrating for customers. RPA can help address customer queries with a quick turnaround time. It helps banks save time and effort and also provides customers with the best possible solution.

Improvement in Compilation Procedure

Banks typically have the onus to strictly adhere to the rules and regulations, monitor the activities of their staff, report issues, and initiate steps when needed to prevent money laundering. Adhering to every single rule can be a tedious exercise, but RPA drives a smooth process by collecting a large amount of data and compiling it automatically, aiding banks in saving time and freeing up employees who carry out such mundane tasks.

Efficient Report Automation

A key aspect of banking operations is to present an accurate and error-free report for all stakeholders. RPA enables efficient report automation by collecting information from multiple platforms, confirming their authentication, and then producing the information in a specific format as per the banks’ needs.

KYC (Know Your Customer)

The KYC compliance is a long-drawn-out process for banks and slow and delayed processes can leave scope for a high level of customer dissatisfaction. According to a study conducted by Thomson Reuters, banks shell out around $384 million annually on KYC compliance. This explains why banks are turning towards RPA that can aggregate customer data, evaluate and validate it, and helps banks wrap up the KYC process in a shorter duration with fewer errors.

Effective Fraud Detection

The arrival of RPA has led to a significant increase in fraud detection, which makes it exceedingly challenging for banks to keep a check on every fraudulent transaction. RPA bots are capable of identifying new frauds by effectively leveraging the ‘if-then’ algorithm. RPA software completes the overall review within a few minutes and can identify even a minute of fraud in the system. It can also assess customer risks and warns them via notification to prevent further fraud attacks on their banking services.

RPA Road Ahead

There is no denying the fact that Robotics Process Automation has driven a significant improvement in the services of the banking sector and enabling banks to deliver an experience that is high on customer satisfaction. Of course, RPA can be a costly investment initially but it offers great long-term value, enabling banks to effectively execute smart banking operations and achieve good ROI within a few months.

Organizations Must Accord High Priority to Effectively Handling Supplier Risks

The supplier universe has evolved over time with organizations sourcing goods and services from suppliers separated by geographies, different time zones, diverse cultures, different geopolitical situations, and regulations. 

The expansion of the supplier universe is a far cry from decades back when suppliers of various organizations were located in close proximity and working relations were based purely driven by trust. The rapid globalization over the years has made supply chains more interconnected, which has led to increasing complexities within the supply chain.

Complexities across global supply chains have significantly enhanced supplier risks. Organizations are now wary about supplier failures as they can have major ramifications. Supplier disruptions such as natural disasters, economic crises, geopolitical risks unforeseen incidents at plants, labor disputes, etc. can not only hurt the profitability of organizations causing losses running into millions of dollars but also trigger reputational damage. The scourge of Covid-19 brutally exposed the vulnerabilities of suppliers and underpinned a pressing need for organizations to build agile, resilient, and future-proof supply chains.

Clearly, supplier risks are a critical issue that needs to be addressed by organizations. Over the years organizations owing to a lack of robust processes have been struggling to identify and successfully manage supplier risks. Over time organizations have counted on analytical models that leverage only historical data to assess supplier risks and failed to provide a warning about potential threats. This explains why organizations have not been able to effectively mitigate supplier risks. The need of the hour for organizations is to adopt a risk intelligent approach, wherein they proactively mitigate avoidable risks, and gear up with effective response strategies to counter unavoidable risks. 

Organizations will do a lot of good to themselves if they obtain accurate information about suppliers’ key performance indicators such as on-time delivery, uninterrupted supply of raw materials, supplier defect rate, compliance rate, purchase order accuracy, etc and accordingly, segment their suppliers based on various criteria. Such a threadbare supplier assessment exercise can help organizations come up with efficient supplier risk management strategies to minimize disruptions, as well as steer clear of monetary and reputational damages.

An effective risk management strategy cannot be a way forward for organizations without leveraging analytics. Analytics help organizations anticipate a possible disruption. Even if any unforeseen event cannot be predicted, it can sound out the fastest possible alert for a company to initiate necessary action and cushion itself from a potential disruption. This is where Predictive analytics comes in handy for organizations – it analyses large volumes of data sourced from across the business by applying hundreds of variables. Predictive analytics enables organizations to take suitable decisions based on the potential scenarios offered by analytics and ensure that their supplier ecosystem stays healthy at all times.

Effectively managing supplier risks is easier said than done. However, a proactive strategy well-armed with analytics-backed improved response measures can help organizations stay alert and skirt unforeseen supplier risks or at least minimize them.

Indian SAAS Ecosystem: Oodles of Promise

Cloud-based solutions are gaining increasing prominence among businesses across the globe. And among these cloud solutions, one that is emerging as a must-have solution for organizations is software-as-a-service (SAAS). The SAAS market has been witnessing exponential growth not just globally but across India as well and holds so much promise for the future. The software-as-a-service industry globally was valued at around $100 billion in 2019 and is expected to touch around $400 billion according to a recent study conducted by a prominent industry body. The increase in cloud consumption, growing need for scalability, and digital technology adoption will be the key growth drivers of the SAAS market. And to throw up an Indian perspective, one cannot deny the fact that software-as-a-service is witnessing soaring popularity among Indian companies. According to Bain & Co.’s India Private Equity Report 2020, along with the Indian Private Equity and Venture Capital Association (IVCA), the Indian SaaS market is forecasted to touch more than $20 billion by 2022 from $6 billion in 2019.

Clearly, the Indian SAAS growth story is earning global attention – it is estimated that the country’s SAAS landscape comprises more than 1,000 companies – more importantly, SAAS funding in India has grown at 15% CAGR over the last 3 years. Interestingly, the Indian SAAS companies are developing and offering solutions that are not just catering to the domestic market needs, but also to the global business needs. This can be gauged by the fact that Indian SAAS firms are deriving 75% of their revenues from global sales – it only reinforces the point that these solutions are not made just for the Indian market but also for addressing the global business requirements. 

The country has as many as six SAAS unicorns (companies that have a valuation of more than 1 billion). Freshworks was the first Indian SAAS company to attain the unicorn status in mid-2018, followed by Zoho – one of the SAAS pioneers in India. The year 2019 saw enterprise contract management solution provider Icertis and data management company Dhruva enter the unicorn club. HighRadius became the first enterprise to achieve unicorn status in 2020 and the fifth Indian SAAS unicorn, and in mid-2020 Postman emerged as the six Indian SAAS unicorn.

There is little doubt that the country will produce more Unicorns in the SaaS space. In the Indian context, it is a given that business-to-consumer (B2C) enterprises will continue to top the valuation charts, largely owing to the way software product enterprises function. The good thing about the Indian SAAS ecosystem is that Indian enterprises are carving out a presence across all levels. For example, Druva is serving large enterprises while Freshworks is catering to mid-sized enterprises, and then you have Zoho addressing the needs of less than mid-sized or smaller enterprises. And one thing that comes out to the fore is that the country’s SAAS ecosystem derives its strength from increased maturity, capital availability of capital, and abundant technical talent.

It is important to note that Indian SAAS enterprises started off their journey targeting the US market but over the years our SAAS companies are also catering to small and medium businesses in India and this has been possible owing to an increasing willingness among Indian enterprises to hop on the technology bandwagon as well as pay for it.  It is all about having a scale in the domestic market.

There is a general line of thought that the Covid-19 will dent the current valuations of SAAS companies, which effectively means that every player will end up losing revenue and the market will witness consolidation over the long-term. There is another perspective thrown around that heavy investments made in cloud companies has led to inflated valuations. Clearly, there is a need to address this as overcapacity and overfunding in cloud companies could impact the business if it went unchecked. It is also observed that in the current Covid-19 environment enterprises with robust balance sheets and those that are free from too many cost overheads will stay well positioned in the long run.

The Indian SAAS story has oodles of promises and many more frontiers are poised to be conquered notwithstanding the Covid-19 blues.

How Low-Code/No-Code Can Drive Next Level of Engineering Efficiency

 

The software industry is witnessing a never-seen-before demand to deliver mission-critical products at a breakneck speed as well as ensure such products are high on quality, cost-effective and can seamlessly integrate across multiple systems. Software organizations are challenged to meet the ever-evolving customer needs and see Low-Code/No-Code application development as a massive opportunity to simplify and streamline the software development process without the need for extensive manual coding. 

However, Low-Code/No-Code development has its share of implementation challenges - it lacks customization and  has integration issues, especially with legacy systems. Further, security and reliability are other concerns with Low-Code as there is a degree of risk involved in working with Low-Code as you don’t have complete control or knowledge of the entire coding process. Despite these challenges, the potential upside makes it a go-to-option for organizations. Let us take a deep dive into how the Low-Code/No-Code movement is revolutionizing the software industry.

Differences between Low-Code versus No-Code

Low-Code is all about developing software, applications, or databases with the help of  a graphical user interface (GUI) and can be fully customized with a minuscule amount of programming. Low-Code needs a visual integrated development environment (IDE) as the user simply has to leverage visual components to assemble their custom application. It offers the option to view or edit the source code and is cost-effective.

No-Code development can be deployed by anyone without any programming knowledge. Unlike Low-Code, No-Code does not offer the option of viewing or editing the source code. The No-Code space brings into play ‘citizen developers’ who build functional but generally limited apps without having to write a line of code. By leveraging a GUI, users can utilize No-Code development platforms by dragging and dropping features straight into their application framework.

Fast-Paced Software Development

Organizations leveraging Low-Code/No-Code platforms can enable software development within a few days or weeks, unlike traditional application development that can take weeks or even months. This allows for rapid speed-to-market as well as ensure software updates are carried out regularly as anyone can make changes irrespective of their level of coding knowledge. The absence of code writing also frees up software developers to focus on other more critical development tasks or even to focus on improvements to products or new products altogether – driving potential revenue.

Cross-Platform Compatibility

Custom applications largely developed through traditional methods are built for one platform or another, e.g. Android or iOS. Such platforms have limitations owing to the costs involved in developing two different platforms. Certain Low-Code/No-Code development is cross-platform and can be deployed across multiple devices, but these are limited.

Cost-Reduction

Low-Code/No-Code serves as an enabler for building more applications/platforms in less time, which helps organizations reduce development costs. They also eliminate the need for hiring more software developers, thus helping keep a tight rein on staffing costs and improve productivity.

Lower Maintenance Burden

Software maintenance is a big responsibility for organizations. Low-Code reduces the software maintenance burden by reducing the plumbing work from day-to-day development. Since Low-Code ensures components are standardized, pretested and ready-made, organizations have to deal with fewer bugs and integration issues than in the past. It also ensures software developers spend less time on maintenance.

No Need for Training In-House Talent

Organizations can leverage Low-Code/No-Code to reduce time and effort in training their workforce. Such platforms do not need organizations to have developers trained in different programming languages. Often basic HTML knowledge is more than enough, which paves the way for organizations to deploy in-house IT professionals to execute their software development solutions.

Conclusion

Low-Code/No-Code is set for the long haul and not many would dispute that. According to a Forrester report, the Low-Code market is poised to touch an annual growth rate of 40%, with spending forecasted to hit a whopping $21.2 billion by 2022. By harnessing the power of Low-Code/No-Code, organizations can accelerate large-scale software development cost-effectively.

Importance of Augmented Reality for Supply Chain Resiliency

Organizations are increasingly adopting a customer-centric approach aimed at providing faster, reliable, secure, and accurate services across their supply chains. This is where Augmented Reality (AR) has emerged as a go-to-technology for organizations to optimize their supply chains.

Augmented Reality can drive enhanced efficiency across supply chains by performing traditional tasks faster and more effectively by leveraging camera and sensor-enabled AR smart glasses and devices. This technology has the potential to address various supply chain pain points as well as streamline work processes at the individual and organization levels. Further, the physical restrictions imposed on account of Covid-19 are only going to accelerate the adoption of AR.

According to a study conducted by MarketsandMarkets, the Augmented Reality market is estimated to grow from $10.7 billion in 2019 and is projected to reach $72.7 billion by 2024 at a CAGR of 46.6% over 2019-2024. These projections further drive home the importance of AR across industries.

Let us understand how Augmented Reality can serve as an enabler for organizations to build resilient and cost-effective supply chains.

Warehouse Optimization

The biggest USP of Augmented Reality is in driving efficient warehouse management. According to a report released by DHL, warehouse activities (such as packing, storage, and put-aways) represent around 20% of all logistics costs. AR smart glasses and devices ensure a faster order picking process by enabling workers to adopt a heads-up approach while performing their tasks. Such an approach ensures that workers’ hands are free and they can stay focused on their tasks. The AR Vision picking software provides every piece of information needed by workers to carry out their jobs such as what items to pick next, how many items to pick, where to pack them in their fields of vision.

AR enables remote users to have a glimpse of what the wearer is seeing, which effectively means that OEMs, consultants, repair experts, offsite managers, etc can extend their remote helping hand to any worker. This can help keep a tight rein on unnecessary travel and downtime-related expenses.

The AR-enabled heads-up approach ensures enhanced safety – it can also play a crucial role in minimizing errors across warehouses. AR devices overlay virtual models and instructions on any user’s field of vision, which makes it possible to directly issue instructions to the task at hand and receive specific, visual feedback on how to complete the work. It is largely owing to the clarity of these instructions that workers are less prone to committing blunders.

Transport Optimization

Augmented Reality can pave the way for increased efficiency across logistics operations. AR-enabled scanners and sensors help logistics companies scan and document errors, damages, and product issues for regulations and compliance. The power of AR can be harnessed in optimizing container loading as well as it reduces the need for physical cargo lists and load instructions. It facilitates loading instructions on a heads-up display with step-by-step instructions on how to efficiently load a container.

Maintenance & Repair

Augmented Reality can be exceedingly handy in detecting machine breakdowns at warehouses. AR smart glass devices with their enhanced image recognition capabilities can identify any machine breakdowns in sorting and repackaging of goods. This technology also ensures timely maintenance of systems and is instrumental in preventing any major malfunctioning or delay in supply chains. Let’s cite an example of a forklift breakdown in a warehouse, wherein a worker can contact the concerned person over the phone, who can see the breakdown via the camera-enabled smart glasses and fix it in real-time.

Training & Learning

A key aspect of Augmented Reality technology is that it can quickly train new employees and even brush up skills of even seasoned employees to learn a new task, thus driving heightened worker productivity. AR smart glasses help workers in prompt and accurate identification of items through their various dynamic inspection functions. In case any worker is encountering any problem while performing a task, the worker can pull up information on the smart glasses to identify a solution instead of exiting the work area to find a helpful guideline, checklist, or diagram.

Aftersales Services

Augmented Reality drives higher efficiency in aftersales services. It provides a 3D imaging of the product and can map the defect – what’s more, customers can leverage the internet or database to fix the defect. This eliminates the need for organizations to have a sizeable number of skilled laborers to fix such issues as well as reduce repair costs and time for the customer as well as the company that provides repair services.

Future of Augmented Reality

The globalization of supply chain management and the inherent complexities associated with them have created a pressing need for technologies such as Augmented Reality. Organizations are starting to realize the importance of leveraging AR in supply chain management and although this technology is still in its nascent stages, there is no denying the fact that AR has a massive potential to enhance the sustainability of supply chain management.

Demand Sensing - A Game-Changer for Forecast Accuracy

In a hypercompetitive marketplace, organizations are straining every nerve to keep up with evolving customer expectations, the rapid pace of innovation, and cut-throat competition. All these prevailing market challenges drive home the importance of accurate demand forecasting for organizations to drive business growth. 

Accurate demand forecasting methods hold the key for global supply chains to be agile, resilient, and future-proof. Traditional demand forecasting methods largely bank on historical sales data and a few seasonality variables and have obvious limitations in predicting demand. These long-standing demand forecasting methods leave out volumes of structured and unstructured data that may have an impact on demand as well as fall short of factoring in constantly changing consumer preferences and external market events. Traditional demand forecasting methods are not always 100% accurate, time-consuming, resource-intensive, and can be a costly exercise. Traditional demand forecasting methods are not considered adequate enough to predict demand, especially near-term demand. Such traditional demand forecasting methods result in frequent stock-outs, overstock, blocked working capital, and more importantly, an unhappy customer experience.     

The inherent shortfalls associated with traditional forecasting methods have brought on the need for a demand forecasting solution that can better grasp ever-evolving market changes and help predict demand with a substantial degree of accuracy. And this need for a high accuracy-focused demand forecasting solution can be addressed by the next-generation automated Demand Sensing solutions that are poised to transform the demand forecasting space in years to come.

Automated Demand Sensing solutions are considered the next big thing for predicting demand. Unlike traditional forecasting methods, Demand Sensing leverages a wide range of different inputs that affect data and demand plans in the short term and breaks that demand plan into daily buckets so that forecast managers can take immediate decisions.

Demand sensing is considered a more effective approach than traditional forecasting methods because the former counts on more up-to-the-minute information for forecast accuracy. It generates demand signals by monitoring customer sentiments and their conversations that enable organizations to meet consumer demand while driving the lowest cost possible across their supply chains. This much-hyped demand forecasting solution harnesses the power of emerging technologies such as Artificial Intelligence and Machine Learning and analyzes real-time consumer demand information from point of sale systems, warehouses, and shipment locations as well as factors in weather, disruptions, etc to predict demand. Demand Sensing applies complex mathematical algorithms to automatically recognize demand patterns and spot complicated relationships in large data sets. 

Demand Sensing helps organizations to substantially enhance demand forecast accuracy resulting in higher levels of customer service, provides a more responsive framework for supply chains to fulfill demand near-term with precise execution, reduces overall inventory costs, enables organizations to gain a much leaner and efficient supply chain, and augment profitability. 

The true value of Demand Sensing can be realized in a well-integrated and synchronized supply chain. This demand forecast method will serve no purpose if supply chains are unable to quickly adapt and respond to anticipated fluctuations.