Data collection is becoming harder 

The volume of data has increased exponentially for financial regulators everywhere. Africa is no exception. They also must deal with a significant increase in regulatory changes and many regulatory alerts. According to, the average number of daily regulatory changes increased from 10 in 2004 to more than 100 in 2020. Thomson Reuters Regulatory Intelligence estimated there were 217 regulatory updates a day globally.  

The challenges of API data collection in Africa 

Regulators need to be freed from the manual handling of data to enable them to focus on supervision. Solutions like Regulatory Data Management, machine learning, Artificial Intelligence (AI), and machine to machine reporting (M2M) can prevent regulators from becoming overwhelmed, making the transfer and analysis of data more efficient. Solutions like Regulatory Data Management, machine learning, Artificial Intelligence (AI), and machine to machine reporting (M2M) can prevent regulators from becoming overwhelmed, making the transfer and analysis of data more efficient.  

The widespread adoption of machine to machine (M2M) reporting is likely to become part of the new norm. “To keep up with the increasing competition from firms inside and outside the industry, banks should provide innovative services at the same rate as other smaller, leaner organizations do… Open APIs and open platform banking are set to change the shape of financial services completely.” (2019) 

But there are challenges that institutions in Africa, like their counterparts elsewhere, need to consider when implementing API data collection.  

  • How do you ensure the data being collected is accurate?
  • What is the financial cost of implementation and management? 
  • How secure is the data being collected? 
  • What cultural issues will you need to negotiate to ensure successful adoption and implementation?  

Key learnings of API based data collection 

M2M reporting is part of a set of modern technologies and strategies that are used to ensure state-of-the-art regulatory efficiency for the modern age. These technologies can provide a range of benefits for Central Banks and the institutions they regulate. 

A reduction in manual labour/human effort and better-quality data submitted to and published by the Central Bank. M2M reporting allows data to be processed, validated and analysed without human interaction. Humans no longer need to do the cumbersome and distracting work of scrubbing large amounts of data and moving it around. Rules or alerts call for human supervision only when certain triggers get invoked. Time is freed up to supervise and only intervene where warranted. 

Reduction in error with better quality and more reliable data. With more data than ever before, the risk of human error is increasing. M2M reporting can mitigate this threat by pre-configuring data with the appropriate level of validation and rules already in place. Once the M2M reporting solution has been delivered and effectively tested it does not make mistakes no matter how much data it processes. If a bug has been introduced that leads to inaccurate supervision, the bug only has to be fixed once. If a human makes a mistake, there’s no guarantee that they won’t make it a second or third time. 

Better timeliness of data with a reduction in time and effort to quickly use data and identify risk. When humans are the main administrators and couriers of data, it takes time to compile and submit. Data may be stale by the time the regulator gets around to viewing it. If the task of moving data from a regulated entity to the regulator and beyond is delegated to machines, it can be moved at up to real-time speeds. The data will be fresh and relevant and there will be less back and forth between parties. The chances of “right-first-time” submissions will increase greatly. 

Increased integrity and security of data. Reducing the potential for error and automating the submission process removes much of the threat of inaccurate data and eliminates some of the security issues associated with human interaction. Better integration with existing, customised applications reduces the security risk. 

Accurate reporting of data is an enabler of reform because it leads to higher standards and easier cleanup of institutions. It also helps the Central Bank to better identify inherent risk and proactively manage supervisory and regulatory decisions.  

API-based data collection in Africa: The Bank of Ghana Experience  

The reform of the banking system in Ghana in 2017 has had a sweeping impact, not least on the economic growth of the nation. A number of objectives were set out to support the reforms: 

  • To provide the Bank of Ghana with financial industry reports and dashboards for operational, tactical, managerial, analytical and policy needs. 
  • To improve information flows for all stakeholders with greater transparency, performance and accountability.
  • To extract actionable data from extensive volumes of business transactions.
  • To provide easily retrievable historical data for forecasting.
  • To provide users with a platform to run customised reports on the fly. 
  • To provide a single decision support system for the disparate database systems within the financial industry. 

The Bank of Ghana worked with us to roll out APIs that enabled Financial Institutions to push submissions to the regulator. API submission is an option for all 42 reporting obligations and the aim is for everything to travel through APIs with human interaction kept to a minimum.  

APIs can be used to push or pull but push by institutions is the most suitable method for regulators. As an M2M solution, it is equally effective in terms of real-time data collection.  The Bank of Ghana is one of the first regulators globally to achieve this level of adoption. Adopting API submission has delivered a range of benefits to Bank of Ghana and the country’s regulatory regime. 

  • Improved quality, consistency, reliability, and integrity of data submitted to and published by the Central Bank.
  • Financial institutions can easily integrate their own customised reporting applications with the Central Bank’s Online Regulatory Analytic Surveillance System (ORASS).
  • Supervisors are provided with insightful surveillance reports immediately based on collected data, along with business intelligence reports from the data warehouse. 
  • Enhanced monitoring and supervision on a standalone and consolidated basis to quickly identify inherent risks within the financial system and proactively determine supervisory, regulatory and policy decisions/actions. 
  • Improved scalability as APIs provide the data exchange formats to address the shortcomings of Excel when it comes to dealing with large amounts of data. 
  • Improved workflow efficiency by reducing the number of tasks involved in preparing and submitting reports to the Central Bank. This also brings more responsibility and accountability. 
  • Reduced costs, time and effort for more than 200 Rural & Community Banks (RCBs) to send information to the ARB Apex ‘mini’ central bank using API submission. 

The future of data processing 

It is becoming increasingly expensive and potentially risky to employ humans in the reporting process. Processing ever-growing volumes of data carries increased risks of human error and the prospect of longer turnarounds in compiling and submitting data. M2M reporting and APIs can mitigate and reduce many of these risks by automating processes, improving data quality, enhancing data integrity and providing regulatory authorities with more timely and accurate data. 

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