48
REGULATORY AND SUPERVISORY TECHNOLOGIES FOR FINANCIAL INCLUSION
APPENDIX LIST OF ORGANIZATIONS INTERVIEWED > Bangko Sentral ng Pilipinas, Philippines
> European Banking Authority
> Bank of Ghana
> Monetary Authority of Singapore
> Bill & Melinda Gates Foundation
> Nepal Rastra Bank
> CNBV Mexico
SUMMARY OF SELECTED CASE STUDIES COUNTRY
IMPLEMENTING ACTOR
DESCRIPTION
TECHNOLOGIES INVOLVED
CORRESPONDING THEME(S)
GHANA
Bank of Ghana
Implemented an integrated financial surveillance system to track loans taken by women and men.
AI, ML, big data
Women’s financial inclusion.
INDIA
Unique Identification Authority of India (UIDAI)
Provides a unique identity number to residents of India, and resident’s Aadhaar number is linked to their demographic and biometric information, which is stored in a centralized system.
KYC utility
Data collection, usage and management.
MEXICO
The National Banking and Securities Commission in Mexico
Partnered with R2A and tech vendor Gestell to develop new data infrastructure and a data storage platform that can house transactional data submitted by supervised entities through APIs.
API, data warehouse
Detection and prevention of financial crime.
NEPAL
Nepal Rastra Bank
Helps track financial progress in the country through a financial inclusion portal.
GIS
Data collection, usage and management.
NIGERIA79,80
Central Bank of Nigeria
Assigned users Bank Verification Numbers (BVN), a unique identification number that can be used to track bank transactions and identify theft and fraud.
API, data warehouse, biometrics
Data collection, usage and management.
Created a centralized database of fraud data for banks to verify watch-listed individuals.
Prevention of financial crimes.
PHILIPPINES
BSP
Chatbot commissioned NLP and AI/ML to help enable consumer protection in the Philippines.
API, NLP, AI, ML
Consumer protection and market conduct.
RWANDA
National Bank of Rwanda (BNR)
BNR developed an electronic data warehouse (EDW system) for automating and streamlining reporting processes.
Data warehouse
Data collection and management.
Published a paper that showed how machine learning tools could be used to extract timely economic signals from newspaper text. The report found that “these improvements are most pronounced during periods of economic stress when, arguably, forecasts matter most”.83
NLP, ML
UNITED KINGDOM
Bank of England82 81
Remote supervision and reporting. Emergencies and crises.
79 Central Bank of Nigeria. 2017. The regulatory framework for bank verification number (BVN) operations and watch-list for the nigerian financial system. Available at: https://www.cbn.gov.ng/Out/2017/BPSD/Circular%20on%20the%20Regulatory%20Framework%20for%20BVN%20%20Watchlist%20for%20 Nigerian%20Financial%20System.pdf. 80 Central Bank of Nigeria. Bank verification number (BVN) enrollment for customers. Available at: https://www.cbn.gov.ng/Out/2017/OFISD/CIRCULAR%20 ON%20BVN%20OF%20OFIs0001%20(3).pdf. 81 Bank of England. 2020. Eleni Kalamara, Arthur Turrell, Chris Redl, George Kapetanios and Sujit Kapadia. Staff working paper No. 865. Making text count: economic forecasting using newspaper text. Available at: https://www.bankofengland.co.uk/-/media/boe/files/working-paper/2020/making-text-counteconomic-forecasting-using-newspaper-text.pdf?la=en&hash=E81EC91956CEA4FC6F63C4DC5942F0E9D4580558. 82 Central banking. 2020. The winners of the 2020 FinTech and RegTech global awards. Available at: https://www.centralbanking.com/awards/7703456/thewinners-of-the-2020-fintech-and-regtech-global-awards. 83 Bank of England. 2020. Eleni Kalamara, Arthur Turrell, Chris Redl, George Kapetanios and Sujit Kapadia. Staff working paper No. 865. Making text count: economic forecasting using newspaper text. Available at: https://www.bankofengland.co.uk/-/media/boe/files/working-paper/2020/making-text-counteconomic-forecasting-using-newspaper-text.pdf?la=en&hash=E81EC91956CEA4FC6F63C4DC5942F0E9D4580558.
