Regulatory technologies in traditional industries as an element of the digital transformation: perspectives for development

Study of digital business transformation. Improving the efficiency of administrative management. The main objectives of the application of regulatory technologies. Assessing the risks of data leaks, finding ways to reduce financial losses from fraud.

Рубрика Экономика и экономическая теория
Вид статья
Язык английский
Дата добавления 03.05.2023
Размер файла 330,6 K

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Аннотация

Регуляторные технологии в традиционных отраслях как элемент цифровой трансформации: перспективы развития

А. И. Алтынов, Ю. В. Туровец

Финансовый сектор является флагманом цифровизации, демонстрируя возможности внедрения цифровых технологий другим отраслям. Регуляторные технологии стали одним из ключевых направлений развития финансового сектора в связи с постоянным ростом мошенничества, а также увеличением объема и сложности процедур по установлению соответствия законодательным требованиям.

Ввиду схожести проблем к новым решениям проявляют интерес и компании традиционных отраслей. Регуляторные технологии становятся сквозным элементом цифровизации, позволяющим эффективно управлять растущей административной нагрузкой, снижать возникающие риски. Внедрение регуляторных решений может служить косвенным индикатором эффектов цифровой трансформации бизнеса, среди которых -- рост регуляторной нагрузки.

В работе выявлены основные задачи применения регуляторных технологий, актуальные для широкого круга традиционных отраслей экономики (сектора телекоммуникаций, торговли, обрабатывающей промышленности, транспорта, строительства, энергетики и ЖКХ, здравоохранения, государственного управления).

С учетом полученных результатов проведена оценка перспектив развития регуляторных технологий в указанных отраслях экономики на основе предложенного композитного индекса, который включает девять индикаторов, сгруппированных по четырем блокам, измеряющим финансовые потери от мошенничества и утечек данных, административную нагрузку, связанную с соответствием законодательным требованиям, а также уровень использования цифровых технологий. Результаты анализа показывают, что наибольший потенциал применения регуляторных технологий, помимо сектора услуг (финансы, телекоммуникации, торговля), сосредоточен в обрабатывающей промышленности и здравоохранении в связи с высокой частотой мошенничества, утечкой данных, растущими издержками и новыми регуляторными требованиями на фоне все более масштабного использования цифровых решений.

Ключевые слова: регуляторные технологии, финансовые услуги, цифровая трансформация, традиционные сектора, композитный индекс.

Appendix 1

Selection of the leading regulators and banks for the analysis

Table 1. Selection of the leading countries in FinTech

Country

The global Fintech Index 2020 (Rank)

The global Financial Centres Index 29 (Rank)

KPMG Fintech100 2019 (Rank)

Average

Rank

USA

1

1

1

1

1

UK

2

2

2

2

2

Singapore

3

5

7

5

3

Germany

11

9

6

8.7

4

Switzerland

5

10

11

8.7

5

China

21

3

3

9

6

Canada

9

11

9

9.7

7

Australia

8

18

5

10.3

8

Japan

22

7

7

12

9

South Korea

18

16

9

14.3

10

Netherlands

6

28

11

15

11

France

16

25

7

16

12

Sweden

7

31

10

16

13

Ireland

17

21

11

16.3

14

Luxembourg

23

17

10

16.7

15

Spain

13

33

8

18

16

Israel

12

41

8

20.3

17

Italy

24

26

11

20.3

18

Denmark

20

34

11

21.7

19

Belgium

26

36

9

23.7

20

Lithuania

4

62

10

25.3

21

Finland

14

56

10

26.7

22

India

15

65

4

28

23

Austria

25

54

11

30

24

Brazil

19

77

7

34.3

25

Based on: [Fintech100..., 2019; The Global Fintech Index..., 2019; The Global Financial..., 2021].

Table 2. Selecting financial organizations for analysis

Bank

Assets (Billions of US dollars), December, 2020

Normalized*

ROA (%), September, 2020

Normalized

Market cap. (Billions of US dollars), July, 2019

Normalized

ROE (%), September, 2020

Normalized

Average

1

2

3

4

5

6

7

8

9

10

Industrial and Commercial Bank of China

4913

1.00

0.77

0.85

295.65

0.79

9.04

0.87

0.88

JP Morgan Chase

3386

0.56

0.77

0.85

368.78

1.00

9.00

0.86

0.82

China Construction Bank

3652

0.63

0.91

1.00

207.98

0.54

10.45

1.00

0.79

Agricultural Bank of China

4008

0.74

0.69

0.76

181.49

0.47

8.80

0.84

0.70

Bank of America

2820

0.39

0.68

0.75

279.73

0.75

6.77

0.65

0.63

Bank of China

3627

0.63

0.60

0.66

151.15

0.38

6.96

0.67

0.58

Mitsubishi UFJ Financial Group

3354

0.55

0.37

0.41

66.20

0.14

6.89

0.66

0.44

Citigroup

2234

0.22

0.51

0.56

163.58

0.42

5.64

0.54

0.44

BNP Paribas

2946

0.43

0.29

0.32

59.36

0.12

6.38

0.61

0.37

Credit Agricole

2386

0.27

0.32

0.35

34.89

0.05

8.05

0.77

0.36

HSBC Holdings

2956

0.43

0.21

0.23

169.47

0.44

3.09

0.30

0.35

Sumitomo Mitsui Financial Group

2139

0.20

0.37

0.41

49.85

0.10

6.78

0.65

0.34

Mizuho Financial Group

2094

0.18

0.27

0.30

36.95

0.06

6.17

0.59

0.28

Banco Santander

1829

0.11

0.34

0.37

75.47

0.17

4.99

0.48

0.28

Wells Fargo

1922

0.13

0.08

0.09

214.34

0.56

0.88

0.08

0.22

Barclays

1846

0.11

0.21

0.23

33.26

0.05

4.08

0.39

0.20

Japan Post Bank

2140

0.20

0.13

0.14

39.91

0.07

2.68

0.26

0.17

Societe Generale

1632

0.05

0.10

0.11

21.27

0.02

2.13

0.20

0.09

Deutsche Bank

1627

0.05

n/a

n/a

15.77

n/a

n/a

n/a

0.01

Groupe BPCE

1463

n/a

n/a

n/a

n/a

n/a

n/a

n/a

n/a

Note:* -- all values are normalized within the mini-max formula. Based on: [The World's largest banks..., 2020; Macrotrends, 2021].

Appendix 2

Approach for measuring regtech relevance in the sectors

Table 1. The Index of RegTech relevance in the selected sectors (abs. val.)

Sector

Losses from fraud

Losses from data leakages

Compliance burden

Digital technologies adoption

Index 1

Index 2

Index 3

Index 4

Index 5

Index 6

Index 7

Index 8

Index 9

ACFE 2020 Global Study, number of fraud cases

ACFE 2020 Global Study Median loss, thousands of US dollars

Data leaks by industry, %(2019)

Average total cost of a data breach, millions of US dollars

Cost of GDPR Compliance, millions of US dollars (2018)

Estimated inefficiencies associated with reduced access to data in US, billions of US dollars

Dell Digital Maturity Index (2018)

Average security automation deployment status, % of companies with fully deployed

OECD Taxonomy of sectors by digital intensity

Telecommunications3

133b

200c

18.30

5.04d

40.3

5.00

50

28.00e

4.0

Finance

386

100

8.80

5.85

30.9

4.00

48

27.00

4.0

Healthcare

149

200

18.30

7.13

19

5.00

45

23.00

2.0

Trade

116

108

7.10

4.60

29.1

10.50

46

27.00

3.0

Manufacturing

211

337

6.40

4.99

29.4

5.00

45

20.00

2.5

Energy and utilities

111

219

8.80

6.39

24.8

7.00

46

20.00

1.0

Transport

65

150

6.40

3.58

24.3

14.50

48

18.00

1.0

Construction

80

200

8.80

3.86

19.07

5.00

47

21.00

1.0

Public administration

195

100

14.90

1.08

14.5

5.00

41

17.00

3.0

Notes: a -- “Telecommunications” sector cover technology and telecommunications companies due to differences in data sources; b -- for the telecommunication value (133) we sum the values for technology (66) and telecommunications (67) from [Report to the Nations..., 2020];c -- average of technology value (150) and telecommunications value (250) from [Report to the Nations..., 2020]; d -- Value for “Technology” sector is taken from [Cost of a Data Breach Report, 2020];e -- Value for “Technology” sector is taken from [Cost of a Data Breach Report, 2020]. Based on: [Digital Transformation Index..., 2018; Data leaks..., 2019; Measuring the Digital Transformation..., 2019; The Costs of an Unnecessarily..., 2019; Report to the Nations..., 2020; Cost of a Data Breach Report, 2020; Chander et al., 2021].

Table 2. The Index of RegTech relevance in the selected sectors (normalized values)

Sector

Losses from fraud

Losses from data leakages

Compliance

burden

Digital technologies adoption

Overall

index

Index 1

Index 2

Index 3

Index 4

Index 5

Index 6

Index 7

Index 8

Index 9

Telecommunications

0.21

0.42

1.00

0.65

1.00

0.10

1.00

1.00

1.00

6.38

Finance

1.00

n/a

0.20

0.79

0.64

n/a

0.78

0.91

1.00

5.31

Healthcare

0.26

0.42

1.00

1.00

0.17

0.10

0.44

0.55

0.33

4.28

Trade

0.16

0.03

0.06

0.58

0.57

0.62

0.56

0.91

0.67

4.15

Manufacturing

0.45

1.00

n/a

0.65

0.58

0.10

0.44

0.27

0.50

3.99

Energy and utilities

0.14

0.50

0.20

0.88

0.40

0.29

0.56

0.27

n/a

3.24

Transport

n/a

0.21

n/a

0.41

0.38

1.00

0.78

0.09

n/a

2.87

Construction

0.05

0.42

0.20

0.46

0.18

0.10

0.67

0.36

n/a

2.43

Public administration

0.40

n/a

0.71

n/a

n/a

0.10

n/a

n/a

0.67

1.88

Based on: [Digital Transformation Index.... 2018; Data leaks.... 2019; Measuring the Digital Transformation..., 2019; The Costs of an Unnecessarily..., 2019; Cost of a Data Breach Report, 2020; Report to the Nations..., 2020; Chander et al., 2021].

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