Data Analytics In Banking

Data Analytics in Banking is a scholarly construct that integrates statistical, computational, and machine learning techniques within the domain of banking to systematically extract actionable insights from financial data, thereby enabling evidence-based decision-making in risk assessment, customer behavior prediction, fraud detection, and operational efficiency.

412

Publications

22.3K

Citations

1.1K

Authors

556

Institutions

Publications per year

2017–2026

300

Authors

1.1K

  1. VR
    Vadlamani Ravi

    Institute for Development and Research in Banking Technology, India

    6 publications · 656 citations

    6

    h-index

  2. AA
    Anil Ari

    International Monetary Fund, United States

    5 publications · 208 citations

    5

    h-index

  3. LC
    Longbing Cao

    University of Technology Sydney, Australia

    5 publications · 559 citations

    5

    h-index

  4. LR
    Lev Ratnovski

    International Monetary Fund, United States

    5 publications · 208 citations

    5

    h-index

  5. SM
    Sérgio Moro

    Iscte – Instituto Universitário de Lisboa, Portugal

    4 publications · 1.2K citations

    4

    h-index

1–5 of 1.1K

Venues

  1. SSRN Electronic Journal

    Repository · 14 publications · 596 citations

    12

    h-index

  2. Expert Systems with Applications

    10 publications · 1.1K citations

    10

    h-index

  3. 6

    h-index

  4. Research in International Business and Finance

    5 publications · 782 citations

    5

    h-index

  5. European Journal of Operational Research

    5 publications · 1.1K citations

    5

    h-index

1–5