Press release

19 Feb 2024 Mumbai, IN

GenAI set to boost Indian Financial Services; potentially add USD$ 80 billion to GVA by 2030: EY Report

Mumbai, 19 February 2024: According to the EY report, 61% respondents in the Financial Services sector believe that Gen AI will have a huge impact on the entire value chain, making it more efficient and responsive to market dynamics. The report titled, 'The AIdea of India: Generative AI’s potential to accelerate India’s digital transformation,' highlights that financial firms have recognized the transformative potential of Gen AI, as 78% of survey respondents have either implemented the technology in at least one use-case or have plans to pilot it over the next 12 months.

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  • The AIdea of India : Generative AI’s potential to accelerate India’s digital transformation

  • 61% anticipate a substantial impact of GenAI on the value chain
  • 78% have either implemented the technology or plan pilot it over the coming year
  • Customer experience and cost reduction, two areas poised for most transformation

Mumbai, 19 February 2024: According to the EY report, 61% respondents in the Financial Services sector believe that Gen AI will have a huge impact on the entire value chain, making it more efficient and responsive to market dynamics. The report titled, 'The AIdea of India: Generative AI’s potential to accelerate India’s digital transformation,' highlights that financial firms have recognized the transformative potential of Gen AI, as 78% of survey respondents have either implemented the technology in at least one use-case or have plans to pilot it over the next 12 months. 

The report also revealed that GenAI's impact on the Gross Value Added (GVA) within the Financial Services sector is most significant, ranging from 22% to 26%. Consequently, GenAI could contribute a potential addition of USD$66-80 billion to the GVA by the year 2030.

A majority of survey participants highlighted focus on two key areas: customer service and cost reduction. When asked about the facets of business that GenAI would impact most, 94% firms mentioned ‘customer experience’, followed by 78% citing ‘cost reduction’ and 61% believed it would have the most impact on ‘driving innovation’. 

Commenting on the findings, Abizer Diwanji, Head – Financial Services, EY India said, “In India's fast-evolving financial services sector, GenAI is a game-changer, fostering innovation and competitiveness. It promises growth, efficiency, and enhanced customer experiences. However, responsible adoption is key, ensuring ethical data use and transparency with customers. Financial firms must promote AI awareness and cultivate a culture that increases its potential for positive impact, while curtailing misuse.” 

Pratik Shah, Partner and Financial Services Consulting Leader, EY India, added “For a long time, AI has pushed the digital evolution of the sector, but with the emergence of Gen AI, we are at the cusp of a significant shift. GenAI promises to revolutionize various facets of financial services, from customer acquisition to service and collections. In the realm of customer experience, GenAI offers personalized experiences tailored to individual needs and preferences. It further holds immense promise in risk management and fraud detection. Globally, financial institutions foresee a timeframe of 5 to 10 years to fully leverage the potential of Gen AI. In alignment with this, Indian financial services organizations are proactively forming specialized cross functional teams and allocating dedicated funds for Gen AI deployments.”

Strategies of GenAI implementation

Firms are investing in areas that offer tangible and readily achievable benefit. After prioritizing the use cases, organizations must make a careful decision regarding the implementation strategy. When asked about executing their GenAI strategy, a majority of 83% said they envision partnering with external tech providers whereas 67% expressed confidence in developing LLMs/in house capabilities. While the latter would help them ensure tailor-made solutions, CXOs also cited that it may carry an execution risk including talent availability.

Key challenges in GenAI adoption

Financial institutions worldwide are typically exploring only 7-10 crucial use cases on average. The survey confirmed this pattern, as 44% of participants have emphasized that identifying use cases and skills gap are among the primary obstacles when implementing Gen AI. The biggest challenge for financial organizations is, however, the enhanced regulatory scrutiny surrounding governance and standards around building LLMs, data privacy, model validation, and financial data cybersecurity.

Striking balance between technology and risk

For CXOs in the FS sector, striking the right balance between execution risks, costs, and viability is of paramount importance. During the survey, FS leaders cautioned that each strategy entails a certain amount of risk. Financial institutions have embarked on their Gen AI journeys, but concerns regarding large-scale use cases, technological maturity, and the risks prevail. Insights reveal that the need of the hour is for organizations’ functional and technical divisions to work together, aligning with leadership’s long-term strategy, to ensure successful Gen AI implementation.

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Note to the editor:

Prediction methodology

To evaluate Gen AI's economic impact on India, EY has developed a macro framework utilizing sectoral shares and input and output ratios. This is then combined with insights drawn from EY’s sector leaders based on their expertise and client interactions regarding Gen AI’s efficiency effects in terms of cost reduction and output expansion over the period from FY23-24 to FY29-30. A bottom-up approach has been used wherein the additional gross value added (GVA) in each sector on account of Gen AI adoption is estimated. This is then aggregated to arrive at the economy wide additional GVA. Finally, by adding suitably estimated net indirect taxes (indirect taxes minus subsidies), we arrive at the additional GDP attributable to Gen AI.  

The assessment of the economic impact of Gen AI is range bound instead of a point estimate. In an optimistic scenario (broad- based adoption), the impact may be closer to the upper end of the range. But if the adoption rates are less than envisaged, the lower limit may materialize.

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