A Digital Pathway To Financial Inclusion In India

At the beginning of this year, Jharkhand’s ‘Pre metric Scholarship Scam’ came to light. Many poor students were deprived of their scholarships by a nexus of government officials, intermediaries, and banking correspondents. In some cases, the fingerprints of the students were utilised to open Aadhaar enabled bank accounts. The Scam came to light when the middlemen siphoned off a part of their scholarship amounts in many cases. There was also evidence of multiple fake accounts being created.
Such a scam reveals the challenges to financial inclusion at two-levels. Firstly, an apparent lack of awareness among the beneficiaries about the Direct Benefits Transfer (DBT) initiative. Even when they are aware of the benefits of the DBT, the beneficiaries lack awareness about their course of action in cases of incorrect Aadhaar mapping with their bank accounts or technical issues like when their payment getting rejected.
The Second challenge that the case revealed was the shortcomings of the Aadhaar enabled payment systems (Apps). The biometric authentication challenge presents itself as a significant vulnerability in the AePS.
Although AePS aimed to direct the country to the era of cashless transactions, a report by Live Mint revealed that the average percentage of failed AePS transactions was 39% in April 2020, ranging from 10% to 62% across providers. The reasons behind the failed transactions ranged from mismatching of biometrics to the bank accounts not being correctly linked to the Aadhaar.

The age of Digital Payments was to usher in a period of Financial inclusion. The JAM trinity launch (Jan Dhan accounts, Aadhaar and Mobile) meant promoting easy access to government services and providing a secure and easily verifiable system. The framework was further given a fillip by the measures like Strengthening of Unified Payment Interface (UPI) by the National Payment Council of India (NPCI). However, one reason for the failed transactions under AePS is the timeouts of transactions because of no response from Banks or NPCI switch.

Another barrier that put an obstacle in the digital payment ecosystem is the wide Digital Divide. The reasons are plenty. Many low-income individuals are not able to afford the technology required to access digital services. According to Digital Quality of Life (DQL), 2020, India’s performance is dismal. India’s overall rank stands at 57 out of 85 countries. It is ranked even below the countries like Guatemala and Srilanka in terms of its E-infrastructure. The only key area in which India outperforms countries like the UK and China is affordability.
However, in many areas, the government has been trying to rectify the shortcomings. For instance, the Digital India initiative rests on the nine pillars of – Broadband Highways, Universal Access to Mobile Connectivity, e-Governance, eKranti, information for all, electronics for manufacturing, IT for Jobs, early harvest programs and public internet access program. More than 1.15 lakh panchayats have been connected under Bharat Net Program. Over 12000 post office branches have been linked electronically. According to NITI AYOG, the digital payments market In India will grow up to $1 trillion by 2023, led by mobile payments growth. According to RBI data, mobile wallet transactions grew from 11.96 million transactions in April 2015 to 387.6 million transactions worth Rs 15,408 crore in January 2020.

Furthermore, several initiatives are being undertaken to improve financial literacy. RBI’s “Project Financial Literacy” and Pradhan Mantri Gramin DISHA are welcome steps in this direction. In June last year, RBI announced the setting up “Payment Infrastructure Development Fund” to provide a fillip to the cashless payments. It aims to encourage the deployment of Point of Sale (PoS) infrastructure and develop card acceptance infrastructure across small towns and cities.

Apart from strengthening the implementation of Financial inclusion strategies, what the ‘Pre-metric Scholarship Scam’ has revealed is that there is a dire need for a data protection regime that will strengthen the cybersecurity measures in the country. What probably forms the need of the hour is a solid regulatory and legal framework centred around protecting the interests of the customers, promoting fair practices, checking account of the payment intermediaries, and placing a system of checks and balances.
Another course of action can be in the form of a more Target Based Approach. According to ILO, almost 80% of India’s employed people work in the informal sector, which operates mainly on the cash-dominated economy. Having schemes that expressly set sectoral targets, deduces an action plan, and creates a close monitoring mechanism can change the fate of financial inclusion for the better.

Financial inclusion is the driver of economic growth, and technology must be leveraged in a transparent and accountable manner to fulfil the ambitious target of achieving a $5 Trillion economy.


About the author: Haripriya Arora is currently pursuing her Masters in Political Science from the University of Delhi. Her academic interest lies in areas such as Governance, International Relations and socio-economic challenges to Development.

Navigating through a data-fluent ecosystem

The COVID-19 pandemic has intensified organisations’ digital transformation, pushing them to digitise their operations, restructure their business models, facilitate access to data, and work on their workforce’s skill-up-gradation. This data-driven revolution is shifting business analysts’ focus to a plethora of new possibilities, often supporting the efficiency parameters. The development of a Machine Learning program asks for data as a fundamental input variable. The data gets used in the learning phase, and the system then becomes capable of making a decision based on that data. The effectiveness of data-driven decision-making has been a well-successful business case. Even the organisations that have previously kept themselves away from digitisation rounds have started working on a long-term data strategy. The current ecosystem has put forth the need to be data fluent. Organisations around the globe are improving their technical capacity and becoming more data-driven in their operations. The workforce needs to skill themselves with the new set of requirements that will follow this revolution.

According to Nature, DeepMind used deep learning to discover how proteins fold—a problem that has baffled biologists for years. Google and Facebook have redefined the advertisement sector, leveraging data and machine learning to improve click-through rates. OpenAI has developed GPT-3, a natural language generation system that provides intelligence to the next generation of computer applications. The New York Times can generate tweets, translate languages, summarise emails, write poetry, and even write its computer programs.
Today, more data is becoming available, computational power is growing, and statistical methods are becoming sophisticated. The confluence of data diversity, storage capabilities, algorithmic efficiency, and computing resources availability has now paved the way for a surge of innovative disruption. As we advance, the rise in the given trend will open-up new opportunities as well as challenges. Some of these trends include:

Rise in the concerns around data-privacy: Lately, there has been a blatant use of personal, often sensitive data by various companies to either train their algorithms for better results or produce any outcome that may have a direct effect on the consumers. Businesses use data variables like internet-browsing patterns, location logs, etc., to display more relevant advertisements. The idea of using one’s data to make decisions that may affect the life of that individual in many ways is often scary, if not beneficial. Various governments have already taken strict actions against the data-storing practices of organisations. This trend may be envisioned to rise, with more corporations, policymakers, academicians, and government institutions taking respective steps in the form of policies, frameworks, laws, or even debates.

Scalable Machine Learning operations to garner attention: The paradigm of a data-fluent architecture will follow sophisticated machine learning models’ operationalisation. To efficiently deploy a machine-learning program, it is essential to maintain an agile framework of processes. An organised lifecycle for continuous improvement can take care of the aspect of scalability for future iterations.

Visualisations to go mainstream: With the data scientists producing results that require the respective audience’s attention, the ease of understanding these results may rattle the designer’s creativity and aptitude. Charts and graphs often form an easily comprehendible form of data-based engineering output. Data visualisations are often the form of data that comes in a presentable condition. It encompasses the art of choosing the right set of charts to display an effective outcome out of the statistics-heavy processes.

Considerations on Algorithmic bias: Algorithmic bias is the systematic error in the computational results that create a lack of fairness in the process. Preferring male candidates over female ones, based on the (mostly) male candidates’ input data in some form, has been an example of such a bias lately. In the upcoming times, algorithms will get ubiquitous and play a crucial role in our lives. Many of our decisions will get influenced by algorithms encompassing the variety of digital systems, making algorithmic-bias a critical issue to ponder upon. Biased decisions by the digital systems may offer a privilege to a group of users over others and may exclude a section of the society out of the encompassing benefits. The algorithms get trained on data sets, and very often, these data sets are not even adequately labelled. Algorithms get better at a task when trained with more data, but the training data is usually produced with less accuracy, creating a fundamental bias to take shape.

Rise of the No-code and Low-code platforms: No-code or Low-code is a development environment to create software through graphical user interfaces (often drag-and-drop) instead of coding. Gartner forecasts that by 2024 75% of large enterprises will be using at least four low-code dev tools for both IT app dev and citizen dev initiatives, and more than 65% of the app development in 2024 will be from low-code solutions. The rise of data-driven capabilities has compelled the departments that have previously ignored its applications to adopt the same. On the other hand, the growing dependence on computer-professionals has given rise to the business case of platforms that do not require a deeper understanding of the computing concepts to operate. These solutions will overcome the dependence on computer engineers and offer others a chance to contribute to the upcoming revolution.

Interdisciplinary debates: For long, advanced computational processes have been designed and developed by professionals with a computer science and engineering background. The diverse computing mechanisms have started to influence other domains, including economics, sociology, psychology, etc. There is a need for interdisciplinary debates to take form so that computing’s social science aspects may be better understood. There will be a better chance for the future of technologies like Artificial Intelligence to take a beneficial stand if we estimate the implications from the point-of-view of diverse societal strands.

About the author: Vedang R. Vatsa is a Fellow of the Royal Society for the Encouragement of Arts, Manufactures and Commerce. He is a recent Young Researcher awardee and holds MTech and MBA degrees. He has represented the Indian delegation at various national and international stages. With 10+ years of academic and professional learnings, he currently works as an IT and Management Consultant.

COVID-19 and Gig Workers: Need to democratize the Gig Economy in India

The Gig economy in India is in a state of conflict at the moment. The Covid-19 the epidemic has hit it hard, with some critics predicting the end of the gig economy (also sometimes referred to as the sharing economy, on-demand economy, mesh economy). Others are more optimistic and feel that with work becoming remote, there will be an increase in the gig workforce, expanding to several new sectors in the economy.

The gig workers have faced the brunt of the coronavirus pandemic in the absence of safety nets. A welcome move is a Code on Social Security, 2020 passed recently by the Parliament. It aims to safeguard the interests of the gig workers by providing them with social security benefits, though shrouded in ambiguity.

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Aarogya Setu App: A Tale of the Complex Challenges of a Rights-Based Regime

At a time when the whole world is grappling with ways to contain the novel coronavirus, the Indian government is pushing its population to download the Aarogya Setu application to strengthen contact tracing and contain the epidemic. Contact tracing applications aim to track COVID-19 cases among citizens and surveillance is one of the key methods being utilised to track new cases and monitor the movement of people to record who they come in contact with.

The latest guidelines issued by the Ministry of Home Affairs makes it mandatory for the local authority to ensure 100% coverage of Aarogya Setu app among residents of the containment zones. The guidelines also make it compulsory for all the employees working in the government as well as the private sector to download the application. In a recent move, not downloading the Aarogya Setu app has been a punishable offence in Noida and Greater Noida which can land you with a fine or time in prison.
While the app may help us fight Covid-19, it also has the very real potential to produce anti-democratic, exclusionary, discriminatory practices and structures at a larger scale.

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