Adoption and effectiveness of ai-powered onboarding solutions in BFSI: A study among organisations in Delhi NCR
DOI:
https://doi.org/10.29070/4hny3a40Keywords:
AI adoption, customer onboarding, BFSI, Delhi NCR, digital transformation, trust in AI, barriers, effectivenessAbstract
This study aims to assess the efficacy of AI driven client onboarding solutions within the Banking, Financial Services, and Insurance (BFSI) sector in Delhi NCR, India's largest fintech and financial services region. A systematic questionnaire was employed to collect primary data from 100 top executives and leaders in digital transformation. The relationships among AI maturity, investment intensity, perceived hurdles, trust, adoption level, and a composite effectiveness indicator were analysed by multiple regression, mediation, moderation, principal component analysis, k-means clustering, and structural equation modelling (path analysis). The average adoption rate of AI in client onboarding was 71.6%, yielding efficacy outcomes of 37.9% increased customer satisfaction, 53.1% reduced drop-off rates, 21.4% cost savings, and 46.2% decreased onboarding durations. The most significant predictor of perceived efficacy, as indicated by regression analysis, is AI adoption (β =
0.492, p < 0.001), succeeded by diminished perceived barriers (β = −0.185, p = 0.006). Notably, increased adoption was positively associated with heightened perceived barriers (β = 0.238, p = 0.026), suggesting reverse causality: organisations that utilise more AI become more aware of practical obstacles. The correlation between adoption and effectiveness was not influenced by trust in AI, nor were adoption and effectiveness significantly affected by AI maturity or investment intensity.
The successful transition of AI onboarding in the BFSI sector is not adequately reflected by formal maturity evaluations or financial investments alone. To optimise perceived and measurable results, businesses should emphasise actual deployment depth rather than expenditure or maturity metrics, while aggressively addressing obstacles like as skills, integration, legislation, and ethics. This study provides primary, region-specific data on the adoption and effectiveness of AI-driven onboarding within the Delhi NCR BFSI sector, highlighting that increased AI implementation surpasses financial investment or maturity level in generating measurable business outcomes.
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