By Luther Kington Nwobodo

A 2022 study analysing emerging economies states: “Data analytics enables financial institutions to analyse customer behaviours and preferences to personalise financial products,” citing Kenya’s M-Pesa mobile money platform reaching “millions of users within a short period” as a case study.

Data analytics is transforming the finance industry, providing institutions with essential tools to gain insights and make informed decisions. As the finance sector evolves, organisations face pressure to remain competitive. Data analytics offers a crucial advantage, enabling better, data-driven business decisions.

Data-driven finance is not just technology; it’s an evidence-based approach to decision-making and performance evaluation. Chief Financial Officers can expand their strategic roles and collaborate more effectively with chief executive officers and other leaders by embracing this approach.

Risk Management and Investment Decisions

The use of data analytics in risk management is increasingly important for financial institutions. By analysing historical data and identifying patterns, organisations can better predict and manage potential risks, assess loan applicant risk, detect fraud, and identify market concerns. Machine learning algorithms play a crucial role in identifying patterns and flagging high-risk activities due to the vast data available.

Data analytics also revolutionises investment decisions. Investors and portfolio managers gain insights to inform strategies by analysing market data and trends. Artificial intelligence allows managers to process data, identify patterns, and predict market movements, enabling them to spot opportunities, identify risks, and make informed decisions, thus helping institutions to better manage portfolios and generate higher returns.

Personalised Client Experience and Benefits

According to World Bank’s Global Findex 2021 Report “The 2021 edition, based on nationally representative surveys of about 128,000 adults in 123 economies, offers a lens into how people accessed and used financial services during the COVID-19 pandemic, when mobility restrictions drove increased demand for digital services”.

The report further reads that, 76% of the world’s adult population now has access to financial accounts, up from 51% in 2011, with developing economies reaching 71% account ownership

Financial institutions use data analytics to understand customer needs and preferences better, identify cross-selling opportunities, address dissatisfaction, and create personalised products and services. Providing better service to clients and consumers is critical.

Data-driven finance organisations achieve lean cost structures, committing more resources to value-adding services, automating manual processes with artificial intelligence, enhancing forecasting abilities, and increasing automation to improve productivity and adaptability. Organisations can focus on metrics that matter, prioritising high-value activities.

According to a 2021 Oracle report, “Money and Machines,” 87% of business leaders believed organisations that don’t rethink finance processes will face risks, including falling behind competitors (44%), stressed workers (36%), inaccurate reporting (36%), and reduced employee productivity (35%).

Financial Inclusion and Emerging Economies

Financial inclusion, defined as equal access to financial services, is critical for economic development in emerging economies. Barriers, such as geographical, socioeconomic, technological, and regulatory constraints, hinder widespread adoption. Data analytics emerges as a tool to overcome these barriers and enhance financial inclusion by identifying unbanked populations, improving credit scoring through alternative data, personalising financial products, enhancing financial literacy, and facilitating digital transactions.

In Nigeria, fintechs analyse mobile airtime purchases, utility payments, and social media activity to assess risk. In 2021, Nigerian micro-lending platforms disbursed over ₦200 billion in loans using these metrics.

Kenya’s M-Pesa processed $314 billion in 2021 through a unified ecosystem. India’s Aadhaar system, which connected 1.3 billion users to a unified digital identification, offers a blueprint.

While Nigeria’s 2021 Open Banking Guidelines marked progress, the crypto ban erased $1.2 billion in fintech value overnight. A cohesive implementation of application programming interface standards, regulatory sandbox models, and artificial intelligence-driven chatbots could halve financial exclusion by 2030.

Data-Driven Future

Looking ahead, the projection for data analytics in finance is overwhelmingly positive. As technology continues to advance and data becomes more accessible, the ability of financial institutions to leverage these tools for better decision-making, risk management, and customer service will only increase. 

Expect to see greater integration of machine learning, leading to more sophisticated predictive models and personalised financial solutions. Emerging economies stand to benefit significantly as data analytics drives financial inclusion and unlocks economic opportunities for previously underserved populations. The future of finance is undoubtedly data-driven, promising a more efficient, inclusive, and resilient global financial system.

Luther Kington Nwobodo, Team Lead Data Engineer with proven expertise in designing end-to-end data pipelines, migrating infrastructure to AWS, and optimising data systems for performance, cost, and compliance. Adept at leading scalable solutions, enhancing data integrity, and enabling actionable insights through advanced analytics and governance frameworks.