Burdened by a highly youthful population with a skyrocketing dependency rate and a population edging towards four hundred (400) million by 2050, the financial service sector must be bold; it must participate actively in developing localised artificial intelligence and relevant emerging technologies through research investment, design, iteration and deployment that can enhance market performance.
From the very humble days of Interswitch to Paga and, most recently, Paystack and Flutterwave, the Nigerian financial landscape has witnessed immense growth. The big boys of the ecosystem, banks and non-depository players, have played a vital role in this renaissance.
The efforts of these players have done quite a bit in bringing the unbanked into the matrix. Still, it has yielded little to no result, particularly considering that less than 10 per cent of Nigerian depositors, per Euromonitor, can access credit through the formal banking sector.
Hence, this piece highlights how artificial intelligence can drive financial inclusion, mainly as it borders on accessible consumer and micro, small and medium enterprises (MSMEs) credit lending.
Data As AI Tools in Finance
It is not magic that produces the varieties of shining ‘boy hen run’ TikTok pictures or the article on your favourite generative AI systems.
Large data sets are needed to identify patterns and develop self-learning algorithms that produce results for artificial intelligence. So, when your preferred AI platform produces an undesired result, it does not infer that the system does not work; it could result from inadequate data availability used to train the AI model.
Interestingly, Nigerian financial actors collect and store loads of data. An ideal AI-powered consumer and MSME credit products would require vast volumes of data to create data-driven, well-informed decisions on risk mitigation, creditworthiness assessment, and approval in split seconds.
AI in Finance: Looking Bank and Living in the Moment
Corporate players, notably banks and other legacy financial service actors, popularised artificial intelligence for customer service engagement and marketing purposes around 2017. From Diamond/Access Bank’s Ada, to Sterling Bank’s Kiki and United Bank for Africa (UBA)’s Leo, the list is endless.
However, more needs to be done around product delivery. Beyond the fanfare that has greeted the spread of seemingly moribund chatbot systems, the work ahead is enormous.
The capacity of thinking computer systems has been widely acknowledged in fraud management, loan/insurance underwriting, and other ancillary support services in the financial services.
In today’s hyper-connected world, the absence of credit history should not be an excuse for denying persons access to loans. Robotics can analyse various data sources such as transaction history, mobile phone usage, social media activities, and online search data to create credit scores.
One of the critical roles data technologies play in finance is the ability to manage risk effectively, ensuring proper audit monitoring. AI-based predictive analytics can conduct system performance assessments and help identify and control potential risks.
Aside from identifying potential risks, algorithmic designs anchored on machine learning can also help investment professionals. The correct AI algorithmic forecasts are recipes for a winning portfolio for fund managers on Wall Street, London’s Canary Wharf, Singapore and several global locations.
AI Use Cases in the Nigerian Financial Market
With the perennial report of fraud, going by daily social media call-outs, machine learning techniques can potentially improve the banking experience for Nigerians, expanding the fraud detection and prevention capabilities of core banking systems.
Going by the Nigerian Inter-Bank Settlement System (NIBSS) report in August 2023, the banking sector lost about nine and a half billion naira (equivalent of $10.5 Million) to electronic fraud within the calendar year.
Admittedly, face and fingerprint biometrics are commonplace; AI offers an opportunity to advance the book of play through behavioural biometrics. This security measure could serve multi-factor authentication purposes besides voice recognition and automated robocalls.
Similarly, predictive analytics AI models offer the advantage of using past trends to spotlight a possible security breach. They can, therefore, sound the alarm about potential violations before they do a lot of harm, thereby forestalling horrendous risks.
In today’s hyper-connected world, the absence of credit history should not be an excuse for denying persons access to loans. Robotics can analyse various data sources such as transaction history, mobile phone usage, social media activities, and online search data to create credit scores.
From product and consumer experience standpoints, customer-focused expense performance, dynamic and routine risk assessment, rate adjustment, and credit product recommendations are equal fundamentals in the future of AI in credit lending.
With the above in play, the need for a wholly automated approval process suffices, thus reducing application to disbursement times. A well-reported industry example is JP Morgan Chase & Co.’s Contract and Intelligence (COiN), which automated 360,000 person-hours of work by processing legal papers within seconds.
How can formal sector players (banks) scale economic opportunities that engender growth through lower-end consumer and MSME lending, considering the ballooning Nigeria’s informal sector forms a whopping 97 per cent of the businesses (per IFC)?
There is no better explanation for adopting AI for lending than that despite top Nigerian banks raking in about N50 trillion in deposits in 2022, even though most of their customers who operate within the informal sector turn to alternative credit lending sources for loans.
International Finance Corporation painted a gloomy picture when it estimated funding for formal MSMEs had a nominal one per cent of Nigerian banking deposits. Worst still, commercial banks rank third in lending volume within this period. This revelation aligns with the United Kingdom’s Enhancing Financial Innovation and Access (EFInA) report of June 2020.
How can formal sector players (banks) scale economic opportunities that engender growth through lower-end consumer and MSME lending, considering the ballooning Nigeria’s informal sector forms a whopping 97 per cent of the businesses (per IFC)?
With such an economic situation, access to credit from the mainstream actors is non-negotiable from both macroeconomic and microeconomic perspectives. Perhaps this is why the IFC’s Market Bite Nigeria report estimates an unmet credit demand of N13 trillion, equivalent to $32.2 billion.
Conclusion
According to a 2023 Pricewaterhouse Coopers (PwC) report, the economics of a composable lending platform launch is between £5 million and £8 million. This is bound to be cheaper locally, considering several dependencies. Interesting part? Such investment has a potential return in twenty-four months.
While the emergence of artificial intelligence is credited to efforts of Stanford University’s researchers dating back to the 1960s, the apparent growth is currently being championed and led by big tech companies such as IBM, Microsoft, Amazon, Google, OpenAI and Facebook.
Burdened by a highly youthful population with a skyrocketing dependency rate and a population edging towards four hundred (400) million by 2050, the financial service sector must be bold; it must participate actively in developing localised artificial intelligence and relevant emerging technologies through research investment, design, iteration and deployment that can enhance market performance. Moreso, this is its surest path to competitiveness, as technology giants are branching into financial services as a core business model.
With rapidly growing internet and smartphone penetration, localised artificial intelligence needs in finance cannot be hard to find, let alone design, test, iterate, pivot as necessary, and scale up. The legacy financial institutions and their fintech counterparts must act now.
Time is ticking!
Muhammed Moshood tweets at @themoshoodm
Support PREMIUM TIMES’ journalism of integrity and credibility
Good journalism costs a lot of money. Yet only good journalism can ensure the possibility of a good society, an accountable democracy, and a transparent government.
For continued free access to the best investigative journalism in the country we ask you to consider making a modest support to this noble endeavour.
By contributing to PREMIUM TIMES, you are helping to sustain a journalism of relevance and ensuring it remains free and available to all.
TEXT AD: Call Willie – +2348098788999
