RESEARCH OUTPUT

FinTech Index for
Small and Medium-Sized Banks

An assessment of the fintech competitiveness of small and medium-sized banks based on annual reports and other public information, with results grouped into tiers by bank type.

PURPOSE

Why this index

Fintech now runs through banking work such as credit management, customer service and fraud prevention. Studying fintech in small and medium-sized banks faces two difficulties: public data are scarce, and banks differ in how they invest in fintech, how they account for it and even how they define it, so their fintech capability is hard to quantify and compare directly.

The group uses text analysis to extract fintech-related information from annual reports and combines it with data on organisational structure, board and senior management backgrounds, intellectual property and violation records to build an evaluation framework. The aim is to give small and medium-sized banks a reference point for their own fintech development and to follow overall fintech development in the banking sector.

FRAMEWORK

Five research dimensions

The five dimensions organise the research framework, while the model itself uses seven observable variables. One type of information can serve several dimensions, so the two do not correspond one to one.

  1. 01

    Fintech strategy implementation

    Focuses on how fintech is positioned in a bank's development strategy and how digital transformation is advanced.

  2. 02

    Talent and organisational structure

    Examines fintech-related talent, the backgrounds of management and the departments set up for technology.

  3. 03

    IT governance and risk

    Brings technology governance and related risk information into the assessment, focusing on management requirements in technology use.

  4. 04

    Fintech operations

    Examines the use of fintech in business operations and the building of technical capability.

  5. 05

    Fintech services

    Focuses on the use of technology in financial services and its support for a bank's service capability.

Information behind each dimension →
METHOD

From public information to tiered results

  1. 1

    Data collection

    Starting from the People's Bank of China list of incorporated banking institutions, collect annual reports and data on violations, patents and software copyrights.

  2. 2

    Text processing

    Convert annual reports to text, extract information on organisation, board and senior management, keywords and finances, and identify fintech-related content.

  3. 3

    Index construction

    Form seven variables: fintech-related keyword frequency, organisational structure, board and senior management backgrounds and violation records, plus invention patents, utility model patents and software copyrights.

  4. 4

    Assessment

    With existing industry rankings as the training reference, estimate variable weights by classical regression, assess the 2023 sample and form tiers by bank type.

Full technical route and variable definitions →
ANNUAL EDITIONS

Annual editions

Each edition is presented separately. No results are shown for editions not yet released.

  1. 2024PublishedBased on 2023 data, 412 banks
  2. 2025ForthcomingWill be added on release
  3. 2026ForthcomingWill be added on release