African Financial Industry Barometer from a Data Management Perspective
Going through the African Financial Industry Barometer, released by Africa CEO Forum and Deloitte Africa (it can be downloaded here: https://www.theafricaceoforum.com/en/telechargement/), and reading it from a Data Management perspective there are a few interesting takes that I would like to share.
It’s interesting to see that most of the focus areas on the report are tendentially extremely data dependent, that their success is intimately connected to the capability of each of these organizations to build and maintain a strong data foundation to support these ongoing or programmed initiatives.
More than half of the inquired organizations points out digitalization as their priorities for the next 12 months, not surprisingly considering the current health context and the increasingly complex market in which FSIs operate.
It is essential — as we see organizations being pushed into digital transformation, to become data-driven, to achieve competitive differentiation and the necessary advantage to thrive in a rapidly evolving complex business landscape — not to lose sight of the work that needs to be done prior to these initiatives.
It is important to be aware that for most organizations the results of digitalization processes fall short from the objectives and will settle for dilution of value and mediocre performance, confronted with a situation where they simply assume that the investment was wasted and worse than that, accept to live with mediocre, under-performing solutions — expensive failures.
Open banking and open insuring
The adoption of open banking and open insuring can prove to be highly beneficial for FSIs, unlocking the potential to reach a much broader customer base.
The downside of these new business models is the obligation to provide access to customer data to third party organizations, which brings to the spotlight, all the questions related with customer data privacy, security and the quality of that data, problems that most of these organizations are already struggling to handle.
Managing to make highly siloed data ecosystems, with different levels of control, distinct quality, and governance criteria, is a challenge that can needs to be approached in a structural way, and again prior to engaging these business models.
Governance and Risk management and Regulation
It is interesting to verify that is some actions undergoing in the organization’s governance models, especially good to see that some of these suggest an increasing awareness of the importance of data.
The increasing changes in the regulatory framework and strict control from the regulators is imposing more demanding approaches to risk reporting and data collection. There is an increasing pressure on financial institutions to enhance risk management processes, supporting them on more reliable data, and to provide detailed reports to regulators on the risks and their impact on their capital and liquidity positions.
The increased use of new technologies for data analysis and collection, the growing volumes of data being produced and the increasing demand for financial and risk data, is pushing risk data management to the front line as a critical component of conducting business in the financial industry.
The Critical Role of Data Governance
FSI are a good example of the need for a robust data governance framework, taking responsibility to establish standards of conformity, integrity and reliability thereby increasing efficiency and throughput.
In the last decade regulatory requirements and industry standards in financial services increased significantly, posing overwhelming challenges on regulatory compliance and risk, customer relationship, profitability, and performance — All of them highly dependent on data, and demanding a global, organization level approach.
To comply with such comprehensive regulatory changes, governance will play a major role. In this context quality data provided through effective data governance and data quality processes is essential to achieve effective compliance reporting, ensuring accurate reporting and improving business decisions dependent on quality data.
As in other industries, the financial services are not immune to data quality, from false mortgage applications to incorrect credit ratings and balance sheets the list of data related problems is vast, adding to this bad data impairs the capability to make and execute decisions, and will constraint the outcome any digitalization process.
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