Experian’s latest research, conducted by Forrester Consulting, reveals how Machine Learning (ML) is transforming decision-making across Financial Services and Telcos in eleven countries in EMEA, including South Africa, and Asia Pacific. The findings show that ML is helping organisations improve access to financial services, reduce risk, and accelerate automation, while also highlighting the barriers that still hinder broader adoption.
ML as a driver of financial inclusion and sustainable growth
The report shows that ML is enabling South African organisations to expand access to financial services for underserved segments, particularly thin-file and underbanked consumers. By incorporating richer, alternative data sources, ML models allow for more accurate assessments of eligibility, helping providers make fairer, more inclusive decisions.
According to the research, 80% of ML adopters in SA agree that the technology enables them to widen access to financial services, responsibly serving new customer segments that traditional scorecards often exclude.
At the same time, 71% of respondents report that ML improves profitability by enhancing risk prediction and reducing bad debt. This dual impact, expanding access while improving financial outcomes, positions ML as a strategic asset for organisations aiming to grow sustainably.
Automation, efficiency and cost saving are top ML benefits
Close to three-quarters (70%) of ML users cite improved risk prediction accuracy and operational efficiency as key benefits. These capabilities enable lenders to confidently increase automation, with more than two-thirds (68%) agreeing that ML allows them to automate more credit decisions – which reduces manual workloads and speeds up time-to-decision. Looking ahead, close to four out of five (79%) of respondents believe that in five years’ time, the vast majority of financing decisions will be fully automated.
Generative AI is emerging as a powerful productivity tool in credit risk
Generative AI (GenAI) is emerging as a powerful productivity tool, particularly in traditionally time-consuming areas such as model documentation and business intelligence. Close to three-quarters (77%) of respondents believe that GenAI can significantly reduce the time and effort required to develop and deploy new credit risk decisioning models.
More than two-thirds (62%) agree that GenAI’s biggest advantage lies in streamlining regulatory documentation, enabling faster validation cycles and improving collaboration between risk and compliance teams.
Organisational Resistance to ML Adoption Persists
Despite these benefits, some organisations remain cautious. The report reveals that cost, regulatory uncertainty, and lack of internal expertise are the primary barriers to ML adoption. Two-thirds (62%) of non-adopters believe the cost of implementation outweighs the perceived benefits, while 55% admit they don’t fully understand the value ML can bring.
Concerns around explainability and compliance also persist, with 56% of non-adopters worried about model transparency, and a similar percentage (62%) fearing regulatory misalignment. These challenges are compounded by legacy IT and data infrastructure, which 67% say is not equipped to support ML deployment. However, the report also notes that many of these concerns stem from misconceptions, modern ML models can be explainable and compliant, and third-party platforms can help bridge skills and infrastructure gaps.
“The report highlights that improving profitability is a top priority for business leaders – the ability to enhance decision accuracy and reduce financial risk is key to achieving this. And ML enables that by unlocking richer datasets than were previously possible. This allows lenders to grow responsibly, become more inclusive and support social progress,” says Ferdie Pieterse, CEO of Experian South Africa.
“Machine Learning is unlocking access to financial services for millions who have historically been excluded from the financial system. By leveraging alternative data and more advanced risk models, ML enables lenders to make fairer, more accurate decisions, especially for consumers with limited financial histories. This technology is becoming central to building more inclusive and sustainable financial systems,” says Mariana Pinheiro, CEO, Experian EMEA & APAC.
To learn more, you can download the full report here.
