India’s Finance Minister, Nirmala Sitharaman, has said that the country will use artificial intelligence (AI) and machine learning (ML) in the tax assessment process system, starting next month.
The move will make India one of the first countries to adopt emerging tech on a large scale in public tax assessment. The new system will increase the accuracy and transparency of the tax assessment process, improving the tax base and compliance.
The Steering Committee on Fintech-related issues constituted by the Ministry of Finance, Department of Economic Affairs, recently submitted its final report to the Finance Minister.
The Committee recommended the Department of Financial Services (DFS) work with public sector undertaking (PSU) banks. The collaboration could explore significant opportunities to increase the levels of automation using AI, cognitive analytics, and ML in the PSU’s back-end processes.
The Minister had announced the government’s plan earlier this year. It was the “scheme of faceless assessment in electronic mode involving no human interface”. The project was created because the existing system of scrutiny assessments in the income-tax department involves a high level of personal interaction between the taxpayer and the department, which leads to certain undesirable practices on the part of tax officials.
E-assessments will be carried out in cases requiring the verification of certain specified transactions or discrepancies.
According to the Committee, there are steps that the government, regulators and public sector firms can take to enable the growth of fintech in India, and its optimal use to solve problems. These actions span general policies, financial regulations, technology policies, government databases, and other areas where the government can act directly.
There are also things that public sector financial firms can do to foster the development of fintech in their respective domains, to improve their business and also to provide examples for other firms to emulate. Government departments and agencies can make data available and offer open APIs, to enable the development of fintech.
Financial reporting has become more numerous and complex, incurring higher compliance costs for companies. Industry experts have said that in many quarters AI could be harnessed to automate compliance processes, saving time and money. Consequently, reg-tech (regulation technology) is a fast-growing field dedicated to easing compliance processes.
Among the factors complicating ease of compliance is the need for processing vast amounts of data. AI can be employed to process large volumes of data into dashboards. Dashboards aid companies in better understanding and decision making while enabling regulators to maintain closer oversight at lesser costs. Identifying suspicious transactions becomes easier, and this contributes to better compliance with the anti-money laundering and terror financing regulations.
AI can also improve cyber-security architecture. With the rising number of cases of fraud and cyber-attacks, AI could be leveraged by financial institutions including fintech firms to efficiently respond to the same.
Tools, systems, and algorithms are being designed to detect cases of fraud or potentially fraudulent activities. AI enables companies to track the historical data of individuals through which any suspicious or outlier activity can be captured.
Innovations in fintech reduce complexity and allow banks to coordinate effectively among different functional areas to vet and test new solutions. These create the flexibility and agility needed to experiment with cutting-edge technologies and have the authority to move forward with promising prospects.
