Artificial intelligence and the world of tax litigation

Published: August 20, 2019 2:55:39 AM

Combined together, the claims for indirect and direct tax stuck in litigation (appellate tribunal and upwards) by the quarter ending March 2017 amounted to over 4.7% of GDP.

Artificial intelligence, tax litigation, ai, GDP, indirect tax, direct tax,TARC, Tax Administration Reform Commission, financial express, financial express editorialAnother secondary source is used to evaluate the reason for the poor quality of adjudication/assessment orders as well as unnecessary filing of appeals by tax departments.

By Mallika Mahajan &
Pawan Kumar Sinha

Sunny Deol’s famous dialogue ‘Tarikh par Tarikh, Tarikh par Tarikh’ from the 1993 Hindi film ‘Damini’—quoted in the Economic Survey of 2017-18—articulates people’s frustrations of delayed and, hence, denied justice. The authors feel that this malaise could find a solution in the twin tools of forensic economics and technological leveraging.

Combined together, the claims for indirect and direct tax stuck in litigation (appellate tribunal and upwards) by the quarter ending March 2017 amounted to over 4.7% of GDP. As per the Economic Survey 2017-18, there has been an upsurge by 25% in the number of cases stuck in various appellate fora, despite simplification of law, setting up of new tribunals and separate tax benches in the Supreme Court. The Survey points out that the success rate of tax departments at all three levels of appeal—appellate tribunals, high courts and the Supreme Court—and for both direct and indirect tax litigation is under 30%, and is declining. As per the Comptroller and Auditor General of India, the poor success rate is because of the poor quality of adjudication orders.

Another secondary source is used to evaluate the reason for the poor quality of adjudication/assessment orders as well as unnecessary filing of appeals by tax departments. The Tax Administration Reform Commission (TARC) was set up by the government in 2014. It produced four reports that analysed the poor functioning of dispute resolution institutions. According to it, the reason for poor quality of adjudication lies in the revenue bias of adjudicating officers (AOs), who are viewed with suspicion by their reviewing/supervisory officers if they decide a case in favour of the taxpayer. The report mentions that a recurring theme—in what they have heard from both the departmental officers as well as the industry—is that the mentality of AOs is affected by the process of review in tax departments.

The revisionary powers provide the authority to examine orders passed by subordinate officers with a view to determining their ‘legality and propriety’. The TARC has reported that the primary consideration that weighs with reviewing/revisionary authorities is the tax effect of the order and not so much its legality or propriety. Orders are routinely reviewed and appeals filed against the original orders when they are in favour of the taxpayer. This, coupled with the perceived fear of vigilance and audit, is said to have fuelled the tendency to pass pro-revenue orders without regard to merit and concerns of legality and propriety, forcing taxpayers to approach appellate authorities and courts. The second TARC report also mentions that there is a marked absence of judicial discipline and respect for precedent, which results in a plethora of avoidable disputes. This is attributable to the same risk-aversion to deciding cases in favour of taxpayers. While on the whole the majority of decisions by departmental authorities show a marked revenue bias, in many of those exceptional cases where fair and competent orders are passed, the higher authorities in the administration show a propensity to file appeals to the tribunals, high courts and even the Supreme Court. Such questioning of their orders de-motivates those officers at the junior level who act fairly and objectively, reinforcing the tendency towards arbitrary anti-taxpayer orders. Hence, the major reason for mounting tax litigation is the trust misalignment between supervisory and subordinate officers/principal-agent.

The deleterious litigious effects from the government standpoint are well-documented. The Economic Survey 2017 used data from six central ministries to show that 52 infrastructure projects of over Rs 52,000 crore have been impacted because of stay orders that were pending for an average of 4.3 years. Since project costs were predominantly debt-financed, in all likelihood project costs had increased by close to 60%. The 126th Law Commission report stated that “…the state also has to bear the (additional) expenses of setting up courts, providing personnel for manning posts.” The topic of the litigious effects on the taxpayer is under-researched. Few studies have suggested that litigation adversely affected SME investment in plant and machinery. Effective interventionistic strategies require the understanding of the economic damages caused by frivolous litigation on taxpaying firms. The authors suggest the use of ‘forensic economics’ for this.
Forensic economics enables the understanding of hidden behaviour. In our case, it will be the behaviour of firms that are subjected to litigation. The focus of forensic economics is with respect to economic loss calculations. What would firm A have earned had it not been subjected to litigation? But for litigation, what would have been the growth trajectory of firm A? It is a simple framework, only that the expert is required to proffer opinions that fall “within a reasonable degree of certainty or probability.” Some have interpreted this to mean at least 51% probability of occurring. Methodologies involve measuring comparisons. In our case, it could be regression analysis of litigation costs and investments in capital goods by the SME.

Where lies the solution to this litigious burden on both state and its taxpayers? TARC reports have suggested solutions. One is the evaluation of dispute resolution officers based on the quality of their orders evaluated for fairness and observance of judicial discipline. Another is peer reviews by panels of selected officers known for their expertise and fairness. From global best practices, the TARC has identified four practices worthy of adoption. The setting up of a dedicated organisation for dispute management, the establishment of an ‘enhanced relationship’ arrangement between taxpayers and the tax administration, and the issuance of binding technical guidance notes by tax administrations. The last solution is the adoption of ADR (alternate dispute resolution) techniques to resolve tax disputes out of court. The suggested methods are conciliation followed by arbitration, in a sequential manner. These solutions do not appear to be a perfect fit for addressing the trust misalignment between principal and agent. The authors suggest the use of artificial intelligence for overcoming risk-aversion of original adjudicating authorities and trust deficit between AOs and their reviewing supervisors.

Inbuilt in the repair design should be a revenue-neutral reviewing mechanism by supervisory authorities. The proposed remedy should be designed around: (1) Monitoring whether precedent judicial decisions of higher fora are being adhered to, (2) same decisions are being taken on the same questions of law, irrespective of the taxpayer, and (3) there is no delaying of decisions when the same questions of law stands decided by officer himself and/or higher judicial fora. Once repair is designed along the above lines, the discretionary element will be automatically circumscribed and oversight will become easy. This repair design should be based on a digital platform with one organisation tasked with the real-time seeding of judicial precedents/case law accepted by tax boards. Artificial intelligence software with prediction technology that generates results that forecast litigation outcome can be used here. Some known software that even offer consultancy, such as Ravel Law and Lex Machina, can be used. The limitation foreseen is that such software will be most effective in better-settled areas of law where there is a very large amount of relevant data.

Mahajan is commissioner, Central Board of Indirect Taxes and Customs, India.
Sinha is director, International Anti-Corruption Academy, Austria

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