Nancy Marangu, Chemichemi Foundation
The artificial intelligence (AI) ecosystem can support diversified financial investments. The International Finance Corporation (IFC) brief on Artificial Intelligence Innovation in Financial Services (2020) indicates that AI has the agility to assess the identity and creditworthiness of individuals and businesses using alternative data collected from mobile phones, satellites, and other sources.
To begin with, AI possesses the capabilities to automate various processes such as customer service and customer engagement which reduce institutional operational costs. In this way, AI enables higher volumes of low-value transactions and, by doing so, begin to turn these formerly underserved individuals into potentially profitable customers and include them in the contestable market for Foreign Service Pension Systems (FSPs). To the extent which incorporation of AI by emerging market FSPs results in the extension of services to previously underserved individuals or underfunded businesses to enhance financial inclusion on one hand.
On the other hand, the extent to which AI is adopted and hence the degree to which inclusion benefits are realized, relies on efforts by policy makers, businesses, and investors to generate institutional and market settings that facilitate responsible and sustainable integration of AI into financial services.
Critically, whereas most emerging technologies are impacting diverse sectors globally, the exclusion gap for persons with disabilities continues to widen due to lack of supportive policy and enabling infrastructure for persons with disabilities.
Secondly, IFC underlines that AI applications have built-in proficiencies that analyze new and complex data sets. In turn, this capability will enhance three things: credit decisions, identifying threats to financial institutions to help meet compliance obligations, and addressing financing gaps faced by businesses in emerging markets. Regarding improving credit decisions, AI enables lenders and credit rating agencies to analyze data that informs the creditworthiness of potential borrowers. In contrast, traditional data used to generate credit scores include formal identification, bank transactions, credit history, income statements, and asset value. In emerging markets, under-banked individuals are persons with disabilities who lack access to traditional forms of collateral or identification that creditors need to extend financial services. Therefore, AI can enable this population segment to have their data accessible by using alternative data sources that include public data, satellite images, company registries, and social media data such as short message services and portfolios.
In terms of threat identification exposed to financial institutions, including cyber fraud, money laundering, and the financing of terrorism, AI can support combatting these threats. AI enables the undertaking of know-your-customer (KYC) and anti-money laundering and countering financing of terrorism (AML/CTF) compliance activities, to verify the identity of their customers, understand the purpose and intended nature of transactions between individuals and businesses, to conduct ongoing due diligence to ensure that transactions match customer profiles and to meet regulatory requirements. In emerging markets, for persons with disabilities, KYC compliance remains a challenge since a considerable segment of the population is deficient in primary identification documents.
Instead of perceiving this as a challenge, there are untapped opportunities for youth with disabilities. Stakeholders within the financial sector can provide youth with disabilities with accessible learning platforms so they can be equipped with requisite coding and programming skills. This will sharpen their skill sets in AI and enable them to invent/ innovate financial inclusion applications. This will improve inclusive compliance levels for the KYC requirements, which underpin correspondent banking relationships that allow individuals and businesses to send and receive payments locally and across borders equitably.
Significantly, AI-enabled compliance technology can reduce the cost for FSPs to meet KYC requirements and decrease fraudulent transactions through enhanced monitoring efforts by sifting through millions of transactions quickly to spot signs of crime, establish links, detect anomalies and crosscheck against external databases to verify identity using a diverse range of parameters. Regarding addressing financing gaps, globalization has increased the scope and complexity of supply chains. Foreign Service Pension Systems take on credit risk for supply chain transactions by intermediating the financial instruments such as loans and cash management that enable trade between buyers and sellers.
The application of AI by originators of supply chain finance (SCF) has the potential to help bridge the existing trade finance gap. Originators of supply chain finance now have access to an incredible wealth of data about the behaviour and financial health of supply chain participants.
Consequently, machine learning algorithms can be applied to these alternative data points.’ records of production, sales, making timely payments, performance, shipments, cancelled orders, and chargebacks to create tailored financing solutions. This, in the long run, assesses credit risk, help predict fraud and detect supply chain threats in real time, besides being cost-effective.
Although the implementation of the systems may be resource intensive during the initial set up, usability and customer reach is far reaching. However, the equation on inclusion still creates an opportunity to develop inclusive friendly systems that support persons with disabilities to thrive within the global value chains that are dynamic.
Nancy is a policy and strategy specialist with a strong passion for advocating inclusion, gender equality, and climate mainstreaming. As a technology enthusiast, she is eager to explore how geospatial technologies can drive socio-economic transformation while remaining accessible to end-users. Her professional experience spans strategic communication, planning, and management aimed at advancing disability and gender mainstreaming, fostering entrepreneurship, and conducting risk monitoring and evaluation across public, private, and development sectors.
