Experian: How Machine Learning Reshapes Finance
New research highlights how Machine Learning improves access, reduces risk, and drives sustainable growth in finance.
Machine Learning (ML) is no longer just a technical upgrade; it is a strategic force reshaping financial services worldwide.
Experian’s latest research, conducted by Forrester Consulting, reveals that ML is enabling fairer, faster, and more inclusive decision-making, with clear benefits for both lenders and underserved consumers.
Unlocking Financial Inclusion
According to the study of global information services company Experian, 64 percent of ML adopters agree that the technology expands access to financial services, especially for thin-file and underbanked consumers.
By integrating alternative data, ML models allow lenders to assess creditworthiness more accurately and inclusively.
As Mariana Pinheiro, CEO, Experian EMEA & APAC puts it: «Machine Learning is unlocking access to financial services for millions who have historically been excluded».
Profitability and Resilience Go Hand in Hand
The research highlights a dual impact: while ML broadens financial access, it also strengthens profitability. 69 percent of organisations report improved profitability, driven by better risk prediction and reduced bad debt.
In Singapore, this balance is particularly significant, says Kabir Khanna, General Manager, Credit Services, Experian Singapore: «ML is no longer a technical upgrade, but a strategic enabler of sustainable growth, competitiveness, and resilience».
Automation Drives Speed and Efficiency
ML adoption is also boosting efficiency. Nearly 68 percent of users cite improved risk prediction and operational efficiency, while 61 percent confirm that ML enables more automated credit decisions.
Looking ahead, almost four out of five respondents believe that most financing decisions will be fully automated within five years, accelerating time-to-decision and reducing manual workloads.
Generative AI Joins the Toolbox
Generative AI (GenAI) is quickly emerging as a powerful complement to ML. 72 perent of respondents believe GenAI will reduce the time required to develop and deploy new credit models, while 77 percent highlight its ability to streamline regulatory documentation.
This, the report notes, will help risk and compliance teams collaborate more effectively and respond faster to regulatory demands.
Barriers Remain
Despite the promise, hurdles persist. 63 percent of non-adopters cite cost concerns, while 74 percent admit they don’t fully understand ML’s value. Issues around explainability and compliance remain, with 60 percent worried about model transparency.
Legacy IT infrastructure also poses challenges, as 70 percent say their systems are not ready for ML deployment. Yet, the report stresses that many of these fears stem from misconceptions, noting that modern ML solutions can be both explainable and compliant.
Turning Point for Financial Systems
As financial institutions embrace ML and GenAI, the potential for broader financial inclusion and sustainable growth becomes clearer.
With 94 percent of organisations already reporting improved SME financing acceptance rates and 87 percent seeing better outcomes in mortgages and consumer loans, Experian’s research underscores the pivotal role of ML in shaping the future of finance.
