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FinTech Will Lead India’s Financial Formalisation

FinTech Will Lead India’s Financial Formalisation

The Indian FinTech market has scaled great heights in the past few years, both in terms of funding and adoption of emerging financial services solutions. India ranked 2nd globally in FinTech adoption with the percentage of users reaching 57.9%.

Deloitte has already pegged FinTech as one of the fastest-growing sectors due to increasing number of preferred digital channels for financial investments and wealth management[2]. In fact, the overall transaction value in the Indian FinTech sector is projected to reach $137.8 billion by 2023, as opposed to $66.1 billion in 2019[3]. The weather has also run favourably for the sector on several fronts.

First, customer experiences have undergone sweeping transformation by the non-financial tech firms, leading to the rise of increased digital expectations from financial firms/service providers. Second, the Indian regulators have now enabled a positive environment of knowledge sharing for FinTechs in addition to several initiatives aimed at enhancing the country’s digital infrastructure. Finally, the adoption of new technologies such as artificial intelligence (AI), machine learning (ML) and big data, fueled by the rising internet and mobile penetration has empowered financial organisations to tackle the pressing pain-points of the time.

Quite understandably, innovation in the FinTech sector has taken the world by storm. Moving forward, the open-API economy may even see surprising participation from the non-financial sectors such as telecom, retail, and power, who can leverage open-data as a means to boost their portfolio by foraying into financial services.

Before we get ahead of ourselves, let’s dive into the key technology advancements India needs to be ready for along with the need to propel indigenous R&D and IP creation.

How FinTech is leading the revolution

A large portion of India’s population are excluded from the formal financial system, due to a multitude of reasons. Lack of awareness about the benefits of financial services products, the inability of traditional financial players to serve this segment in a cost-effective manner and the lack of a national infrastructure to support future progress being the key.

However, since the launch of schemes such as Jan Dhan Yojana, and Direct Benefit Transfer, there has been a significant rise in the awareness of these products. The introduction of the Goods and Services Tax (GST) regime has also been a mindful step towards formalizing the unorganized sector of the Indian economy with several FinTechs leveraging its generated digital footprint (i.e. GSTN), standing at an impressive ~1.21 crore registered entities. Jan Dhan Yojana, the flagship initiative by the government has also seen a significant uptick in the number of people with bank accounts in India, currently standing at 320 million. Finally, access to platforms such as UPI through the ‘Digital India’ initiative has allowed banks, wealth, lending and insurance players to innovate freely around the pressing consumer problems.

These, in turn, have led to the rise in demand for financial services solutions, thereby creating viable market opportunities for FinTechs.

Driving excellence through collaboration

If we were to take part in the collaborate-vs-compete debate, the growing trust in the FinTech industry has brought challengers and incumbents together to explore more opportunities for new revenue streams, and rapid go-to-market solutions. In fact, FinTech challengers today have emerged as sophisticated competitors. The interactions between them, incumbent players and global experts are forming ecosystems that are replacing traditional bilateral partnerships designed to solve problems. It is interesting to see so many partnerships and the launch of new brands such as Kotak 811, iMobile and SBI’s YONO. ICICI powered Neobank initiative called ‘Open’ is also an example of a similar move.

To achieve the middle ground between innovation and regulation, RBI’s proposed first-of-a-kind regulatory sandbox for FinTech start-ups offers the right kind of boost needed to help this industry achieve its potential.

That said, the road to collaboration is not free from hurdles. While incumbents struggle with the pace of innovation and the obsolescence of their legacy systems, startups are feeling the brunt of bureaucratic, legal and cultural issues when working with these institutions. Nevertheless, the maturity of collaboration is all part of the ‘one-step-at-a-time’ revolution, sure to lead to a promising avenue for growth and financial inclusivity.

Each must welcome the wave of change with a humble heart, open mind and embark on the journey of unlearning the traditionally accepted models.

This article has been published in BUSINESSWORLD.

http://www.businessworld.in/article/FinTech-Will-Lead-India-s-Financial-Formalisation/27-10-2019-178089/

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Evolution of chatbots in financial services with Natural Language Understanding

Evolution of chatbots in financial services with Natural Language Understanding

Technological advancements over the last few decades have prompted the exponential growth of customer service across industries. The Amazons and Alibabas of the world have set new standards for customer expectations. With real-time updates, ease of information exchange, and round-the-clock customer service, industries are building solutions for seamless transactions. To meet these demands, artificial intelligence (AI), machine learning (ML) and chatbots are becoming a priority for businesses, including the banking and financial sector. Chatbots are helping organizations reduce costs, provide quick services, offer transactional support, and serve as a medium for upselling products.

The digital-era calls for instant communication and 24/7 connectivity. Chatbots enable a better communication channel for users to engage with business services. By using application programming interfaces (APIs), chatbots integrate with data management platforms to analyze data for end users. In the financial sector, consumers of data insights range from end customers to banking CXOs.

Essentially, chatbots are artificial intelligence (AI) powered virtual assistants that are trained with a conversational dataset to respond to questions. Initially, chatbots were trained on a fixed set of questions (rules-based chatbot) with which customers could interact like a frequently asked questions (FAQs) system. But as technology evolves, chatbots have evolved from sounding like a robot to emulating human speech. Natural language Processing (NLP) plays a major role in developing conversational analytics platform to provide real-time insights for decision making. NLP provides an efficient means of monitoring end user sentiments.

In everyday banking, chatbots find their use across varied functions and operations; eliminating the need for customer service agents. Gartner predicts that by 2020,  85 percent of customer service interactions will be handled by chatbots. The technology is being used to provide customers with a 24/7 support system, help with customer onboarding, KYC forms, resolving queries, and selling new products or services. According to a study by Juniper Research, as automated customer service evolves, by 2023 bank operational cost savings via chatbots will reach $7.3 billion. Future banks would be saving 862 million hours, equivalent to approximately half a million working years, as per Juniper.

Ally Bank was one of the first few banks to implement a chatbot for their customers. Introduced in 2015, Ally Assist – a virtual assistant within the Ally Mobile Banking app, helped customers request account summaries or transaction history, make payments, peer-to-peer transfers, deposits, and monitor savings. Using machine learning, Ally Assist analyzes spending patterns to predict customer needs and provide relevant help topics and messages. The assistant uses NLP to address common customer service queries.

Bank of America introduced Erica – a virtual financial digital assistant to allow customers to access information on account balance, credit reports, send notifications of account changes, and schedule transfers among many other functionalities. Six million people are reported to be using Erica and over 35 million client requests have been processed through their mobile app.

While chatbot technology continues to advance, it comes with its own set of limitations and learning that are changing over time. As more and more organizations develop use cases and expand functionalities, chatbots get smarter. The major limitation of a chatbot is still in its dialogue capabilities. Conversations with a bot do not feel natural, is impersonal, and lacks empathy and context. Bots cannot process multiple questions or conversations at the same time. They are programmed to give the right answer only when they are asked exact questions. In the real world, this creates a problem wherein different dialects, accents, and jargons/slang aren’t picked up by chatbots.

To better understand these complexities, chatbots are integrated with natural language understanding (NLU). A subset of NLP, NLU focuses on handing a narrower data set, converting unstructured inputs (human speech) to a structured form that is machine-readable (structured ontology). NLU communicate with regular end users to understand their intent; going beyond understanding words and interpreting meaning. With NLU, chatbots can enable better conversational flow using clarification techniques, detecting sentiments, and predicting customer questions. The bots now have the ability to understand context and deliver ‘contextual insights’ based on conversational banking. Fidor’s chatbot uses conversational AI and NLU to deliver real-time personalized and efficient interactions with users. It is one of the first digital banking service providers to implement virtual assistants within its technology stack. The chatbot is programmed to detect sophisticated language nuances to understand user requests and have a natural conversation.

As chatbots continue to advance, banks will need to shift their focus from mobile banking to a friendlier conversational user interface (CUI). Conversational interaction is seen as the natural evolution of mobile baking. For banks to succeed with this technology, a fundamental change is needed from both, consumers and banks, in the way they interact with each other. Not all banks are ready to make the shift to chatbots and consumers are just warming up to the idea of speaking finance to a bot.

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Robotic Process Automation in Banking

Robotic Process Automation in Banking

Robotic Process Automation (RPA), which many in the financial industry believe to be the Secret to Digital Transformation, is fast emerging as a highly efficient way to help financial institutions support their digital initiatives.

RPAs are software robots that can be deployed to automate specific tasks a human agent would otherwise carry out. Banks and financial institutions are today building localized centers of excellence deploying bots that can eliminate the issue of monotony by taking over repetitive work and reduce human error. With RPAs human tasks and decisions can be automated freeing human resource that can be utilized for higher level tasks.

There are specific areas where RPAs especially thrive. Processes such as Billing, KYC (Know Your Customer), rule-based lending decisions and Anti Money Laundering (AML) screenings are being revolutionized by intelligent software bots. RPA is the secret sauce banks are turning to make innovation possible without cost overheads.

While RPA is deployed to automate routine, human-intensive tasks, these days it works along with a wider ecosystem made of Cognitive automation which deals with automating non-routine tasks that augment human capability using AI and ML (Machine Learning). Cognitive automation helps organizations discover a new opportunity that is lying within their existing context. A third paradigm RPA works side-by-side is now termed as social robotics which deals with a combination of physical assets, AI, sensors and mobility. This brings up an environment where machines interact with humans increasing the overall capability of the domain.

Where RPAs Thrive

RPAs are already taking over the task of telecalling agents with the deployment of AI Chat boxes. With NLP (Natural Language Processing) AI chat boxes are able to converse with a banking customer as real as a human while being more accurate and fast. From online chat, other point of contact system such as mobile apps, ATMs, information kiosks are also driven by RPAs.

RPAs are especially well suited to handle the explosion of unstructured data which come in handy while triangulating with other data during KYC or AML screening.

Many banks are deploying RPAs in its billing section where every contract is digitized, classified and through AI assisted bots, they are able to automatically generate accurate invoices and also detect revenue opportunities based on SLAs. There are now sophisticated OCR and ICR tools which can read a contract and apply rules without human intervention.

With NLP and self-learning abilities, automated bots are proving to be saviors in a world where competitiveness and regulatory compliance are becoming paramount concerns. Many banks have reduced errors in billing and potential lawsuits from erroneous billing.

RPAs are typically deployed in by financial institutions such as banks and insurance companies to address tasks which involve gathering documents, organizing, searching, real-time matching of events, and analyzed for particular instances. RPA delivers a high degree of operational efficiency, auditability, security, and reliability. In back-office operations, RPA thrives since it can be incredibly precise, and provide detailed analytics of its own actions. BPOs have deployed RPA in varying degree of maturity.

One interesting facet of this “RPA can provide detailed analytics of its own actions” is that HR departments in financial industry are using it to train their staff. RPA can record and re-play the process step-by-step which comes in handy in developing self-learning modules for staff. So a learning and self-evaluation model is thriving in many banks and insurance companies.

The Gateway to Digitization

RPA ability to automate small repetitive tasks to large complex ones make it a perfect vehicle to launch the digitization in banks. Given the fact that redundancy is vital for banks, RPAs help in augmenting the human abilities bringing in a higher degree of check and balance and redundancy.

For banks, RPAs bring an easy alternative of gradually renovate and evolving their processes into digitized versions or launch a completely new entity with RPAs taking the lead role and human agents becoming enablers. There is a thriving marketplace for RPAs from where banks can buy useful bots and integrate with their banking software.

Omnipresence automation

RPAs are not just being deployed in the back end. Client user experience on the web or apps  and contact points are highly customized for each customer. On the fly upselling products and services, alerting compliances, generating invoices on demand is where RPAs shine adding a competitive edge.

RPAs are also enabling display of customized role-based User Interface and service menu options when customers visit their websites.

Human Machine Interaction

Does RPA conjure up apocalyptic imagery where humans are replaced by robots at workplace? This is misguided at its best. RPA augments human capability; it is essentially freeing human endeavor to focus on more important things. Moreover, RPA requires human intervention in decision making and overseeing its operations

Automation of tasks is not a new phenomenon but cognitive AI driven, NLP enabled, self-learning social bots are proving real game changers in the banking sector.

 

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5 Key Techniques to Improve User Experience For Mobile Banking

5 Key Techniques to Improve User Experience For Mobile Banking

Customer acceptance of mobile banking apps and mobile banking services is on an all-time high by both existing and emerging economies. However, the impact of a good user experience is often underestimated. Research points out that nearly half the millennial customers are dissatisfied with mobile banking and online banking services. With increasing dependency on mobile banking apps should be a signal for banks to rethink their mobile banking design. The digitization teams responsible for mobile strategy will have to include user experience as a value-adding differentiator to increase customer satisfaction and loyalty.

A recent study on user experience for mobile banking revealed that there is a correlation between user experience and mobile banking. It states that these two needs to go hand in hand to increase adoption and usage numbers, especially in the developing countries.

Emerging economies are utilizing mobile banking and hybrid-online payments services to empower the bottom of the pyramid (BoY) population with financial inclusion. With over 3.9 billion BoY population worldwide ( 95% – South Asia, 68% Middle-East & Africa, and 27% Latin America). A mobile banking app with a combination of high functionality and good UX design can assist in tapping the potential banking market. (Statistics source – PwC)

Given the reason, it is imperative that a good UX experience is crucial for mobile banks to be used and appreciated by its customers.

 

Here are 5 ways to improve user experience for mobile banking:-

Make security a top priority

It is quite a challenge to create a secure, yet user-friendly mobile banking app on two of the major mobile operating systems – Android and iOS) since both are completely different. Balancing security with a good UX is pivotal. Recent times has seen a surge in mobile banking trojans which topped the threats related to mobile banking. Although incorporating a multi-factor authentication can be easy, user’s response is not favorable. Almost 74% customers hated two-factor authentication to sign in.

One way of addressing this security issue can by introducing either fingerprint or voice or facial recognition technology. This biometric technology analyzes physical characteristics and behavioral patterns. This allows for a new level of security and usability by solving user friction and security lapses. Nevertheless, it is good when developers adopt a “security first” philosophy when it comes to UX design.

Bankable integration of legacy systems and customer interface

Almost 66% of customers who use mobile banking regularly demand easier and faster services that many legacy banking institutions are straining to deliver, mainly due to the true integration of the back-end systems and manual process with the front-end systems. This lack of proper integration sets back the digital transformation goals of banking and financial organizations by large measures. Not surprisingly, 50% shareholders responsible for digital transformation, in a recent survey have said that legacy systems are one of the biggest barriers to making the transformation take effect.

The current approach of integration is done by building a layer of applications around the legacy systems to provide a customer interface because a 360-degree transformation would involve replacing or extensively upgrading the existing back-end systems. For the future, the usage of a middleware – a Java or a PHP based backend to converse between legacy systems and mobile apps.

Another option would be to implement Infrastructure-as-a-Service (IaaS), through cloud computing. Even a hybrid integration, can connect legacy systems to internal applications and third-party applications through APIs.

Incorporate emerging technologies to enhance services

With evolving technology such as AI and machine learning, mobile banks applications will touch new degrees of sophistication especially with voice and facial biometrics, along with growing confidence in the beneficial nature of chatbots.

It is predicted that by 2020, 50% of all searches will be voice-based. These voices searched are predicted to be carried out by voice-enabled assistants powered by AI. Voice-enabled AI can perform searches and even initiate payments. The voice-controlled mobile application is already a reality. For example, the Royal Bank of Canada added Siri to their mobile app.

Many banks have already given a go-ahead to facial and image technology. The mobile user interface and core banking systems are connected via an Enterprise Content Management System. The inclusion of facial biometric technology as a part of user experience can ensure significant time savings and increased productivity.

Banking chatbots are enjoying widespread acceptance, so much so that by 2020, 85% customer interaction with banks will be through chatbots. Developing a conversation UI for chatbots can lead to high engagement and lower abandonment rate. Some uses of chatbot can extend beyond customer support and recommendations. For example, American Express (AmEx) employs chatbots that can identify and terminate credit card fraud.

Personalized Services to improve satisfaction

The power of personalization services through mobile banking apps has not yet plateaued. This includes both UX and content personalization. A UX personalization would involve allowing users to customize home screens, choose colors and increase or decrease font sizes. With additional how-to-guides and quick access to customer support (help buttons) would assist customers who prefer self-service. Through content personalization, geo-fence based notifications or reminders can be sent to customers when customers in near the vicinity of the bank. This location-based user experience design in real-time can increase the app engagement by 2x times.

Personalization experience can also be included in the form of budgeting tools, financial advisors for investment wisdom and even for scheduling appointments for VIP customers. AI integrated design can perform these functionalities with ease. It can also be used to extract data and financial records to cross-sell products to the right customer at the right time.

Minimize effort with streamlined navigation and reduced customer input

A good mobile banking design should ideally include proper navigation and instant redirects to point the customers to the content they are looking for. With landmarks and icons, such as search boxes, section navigation tools and labels in the app, it can appear intuitive whilst simple to use. Although, identifying where the customer is getting lost in the navigation process through touch heat maps can be used to rectify the problem areas. It is also a good guideline to tell the customer which screen they are looking at by highlighting the respective icon.

A mobile banking app that avoids demanding too much effort from the customer is the first to pleasing the customer. By automatically populating data or setting up defaults for repetitive actions can greatly reduce customer effort and errors. Auto-suggestion, spell-check and predictive text, without overdoing, can bring down the time spent on data entry.

For banks aiming to delight their mobile banking population, it is crucial to deliver high-quality user experience. In the long run, a great user experience will likely be a good pay off by increasing revenue through elevated customer satisfaction levels and by boosting customer loyalty. Also, in the future, AI will become instrumental in bringing a refined user experience in the mobile banking applications.

 

 

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The AGILE Mindset – The differentiator between doing Agile and being Agile

The AGILE Mindset – The differentiator between doing Agile and being Agile

Agile is not just about stand up meetings and sprints. To deliver superior quality of work to clients, the mindset in the organization across all layers should be flexible and open to embrace change. Agile needs to be looked at as a mindset rather than a set of tools and processes.

The way the team responds to a changes, impediments; and delivers value to the client in small timeboxes as fast as possible, to fetch continuous feedback, is a part of an Agile mindset.

The below article looks at how organizations must shift our practice-based mindsets to more behavior-based mindsets. This will allow organizations to leverage the “Agile” behaviors of collaboration and discovery, to produce valuable outcomes that move business organizations forward.

An Agile mindset focuses not just on the completion of the task. It lays more prominence on the value a certain task is going to bring to the end users. This is the reason why Agile is based on receiving continuous constructive feedback. Cultivating and nourishing this mindset, will result in amazing results – happy employees delivering great value and making clients excited with the results.

It is not just the tools or the certifications that bring about the Agile change, but more importantly the mindset and outlook of the organization which plays a pivotal role in Agile transformation.

Companies are looking forward to better ways and technologies to improve their productivity and efficiency. They can achieve this by bringing about a transformation in the mindset internally towards Agile, and also finding an experienced and expert service provider with Agile DNA.

Finding the right fit

Organization looking for Agile service provider need to take stock of where they are currently and what they want to achieve using Agile delivery models.

Backlog based delivery model – Release and iteration planning can be made easier with a well prioritized  backlog  which results in clear indication of what the service provider intends to spend time on – including the internal work that the customer might not notice. This helps in setting expectation with the stakeholders, especially when there are additional or change in requirements.

Automation using open source tools – There are certain impediments like cost, quality and coverage that might limit the expansion of automation. So it is important to have right set of open source tools and more importantly to have an automation framework in place, to succeed with test automation. The service provider with an agile DNA will exactly put the above points in place for their clients to reap the benefit of automation.

Hybrid solution – Traditional methodologies are often considered or blamed for not being able to adapt to the changes which makes software quality assurance difficult. While Agile approach has many credits to it but we need to think whether it applicable to all business scenarios. With that being said, we often see businesses using a combination of Agile and Waterfall models. This fusion is often a result of a trade-off to keep some level of planning and also reaping the benefits of iterative, collaborative and flexible approach.

A service provider with a proven Agile methodology in place in their domain area would be an added advantage.

Indicators for an organization’s agile mindset

1

        Inclination to communicate and collaborate

In a good collaborative ecosystem, team members commit to meeting a joint goal, and they’re not afraid to step outside their area of specialization to help others on the team. The era of QA department working as an isolated unit is over. Now in Agile world, QA and development team work hand-in-hand to deliver much greater business value to the clients. Agile needs to work both ways, empowering testers from the top down and taking responsibility for their development from the bottom up. It’s about aligning goals across your company so that every department and every member of your staff is pulling the team in the same direction.

2

        Understand the purpose

If a developer does not understand the purpose of a process, they will not know when to follow it and when to adapt it to their current situation. They will also not understand how to improve the process, which is a key part of developing in an Agile way. Similarly, a developer needs to understand the benefits derived out of using a particular technical practice otherwise they may not know when to use it, and when not to, or how to improvise on that practice.

It is highly recommended that senior management conduct proper training which would educate the employees regarding what being Agile is, in its true sense. This will help the team and the organization on the whole to become Agile, be flexible and learn to respond in every situation instead of reacting.

3

      Working software over comprehensive documentation

We believe that getting working software into the client’s hands early is more important than preparing labor-intensive specification documents. In reality, it’s difficult to really know what a solution should look like until someone has a chance to see it, and use an early version.

Teams need to orient themselves to carve out a feature from the high-level requirements that can be built fast and pushed to production (say, within a couple of weeks). Conventional “gates,” sign-offs, deep-dive reviews and inspections need to be replaced with suitable techniques from Agile or by suitable automation.

4

Accountability at the team level

Different teams developing pieces sequentially in different sprints makes it more difficult to understand when all the teams will complete their pieces of functionality and be ready to integrate and deliver them.  One team running late delivering their piece may impact the schedule of other teams.

Different teams working in the same sprint creates a lack of ownership for the feature.  The challenges are coordinating the teams working on the same feature and making all teams accountable for design and delivery.

5

Teams should have an open mindset to embrace change

Whenever you plan a set of features for a release, work with the customer to see if they could make use of a subset of those features. If so, release that subset first. You must then make sure that the features are really what the customer wants. At the very least you should be looking for customer feedback early and often, and building what the customer wants, rather than what you’d like to build.

Look for the following factors within your team

Factors for Agile Development

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