Sunday, May 30, 2021 / 08.00 AM / Teslim Shitta-Bey,
Managing Editor, Proshare/Header Image Credit: The Courier
Banking is changing. Banks, and their customers, are riding a wave of innovation, reimagination, and reinvention thereby intensifying retail competition and how customers are serviced. Not only has technology 'cancelled' routine teller functions but it has also placed less repetitive jobs in the crosshairs of software developers aiming at automating lending and loan recovery decisions as financial service operators increasingly use big data to hedge loan risks and guide loan selection. The AI of banking is not on its way, it is here.
Market analysts note that the anonymous customer no longer exists, and growing digital footprints have given Nigerian lenders an insight into the psychology of borrowers and the potential buying habits of customers. The character of customers can be gleaned from the pile of data buried in their income statements, spending habits, investment choices, and saving cycles. These digital footprints apply to both corporate and individual customers.
Indeed, access to massive data on individuals and corporations means that unlike in the past where knowing the customer was a hit-or-miss affair, the new data age of machine learning (ML) and artificial intelligence (AI) unpacks the customer and his or her lifestyle. What might still prove difficult, however, is determining a customer's character, but this is not entirely impossible, or at least it could be made less random by using AI and ML as guardrails for assessing behavioural patterns and assessing customer reliability.
With more data about individuals and corporations becoming available to lenders daily, the once far-fetched concept of 'open' banking is moving from fringe speculation to mainstreet implementation. Local banks are accessing customer transaction data to build financial solutions that meet customers at their points of pain and are opening up wider opportunities to properly appraise services such as temporary overdrafts to meet short-term cash flow deficiencies based on such things as salary expectations. Loan repayment cycles could be used to establish a digital footprint of a customer's ability and willingness to repay loans to form a 'character map'.
In places like East Africa, such character mapping has improved rural financial inclusion and greater female economic participation, but not everybody has caught the bug.
The Nays Have Their Say
In October 2015, the European Parliament approved a new Payment Services Directive, called PSD2. The new rules were intended to promote the development of innovative mobile online payments through 'open' banking.
However, some financial reviewers were unconvinced that this was the way to go. Mr. Mick McAteer of the UK's Financial Inclusion Centre thought that only digital natives would benefit from the development. He said that open banking was "a daft idea", which could worsen the financial exclusion of lower-income individuals. McAteer argued that it was naÃ¯ve for regulators to expect consumers to take ownership of their data and negotiate good deals with the banks. He noted that consumers could be exploited by banks based on the higher cost of sundry new products such as payday loans and the misuse of data and personal information that customers could inadvertently make public.
The pushback against open banking has not gained broader market support as fintech companies and banks have continued to fill out the 'white spaces' between customers and financial service providers. The gaps in service delivery in banking are being addressed by institutions that have taken advantage of the spread of telecommunications and the increased penetration of mobile telephony in frontier economies to meet customer service needs.
As good as AI applications and open banking appear to be on the surface, they could create major challenges to individual data privacy. In the process of trying to understand the customer's service experience banks could find themselves facing the morality of customer data mining and the selective bias of customer profiling. Highly-priced services could be offloaded onto undiscerning customers who find themselves paying premium prices for services they could either ignore or perhaps defer (predatory lending).
This issue is raised and debated in a March 2021 article in the International Monetary Fund's (IMF's) magazine Finance and Development. The writer Nikita Aggarwal, a researcher at the University of Oxford, England, notes that there is a need for a balance between the rise in digital lending and the need for consumer protection, an issue that is yet to be resolved satisfactorily in the new digital marketplace.
She observed that 'datafication' of debt had its uses in increasing loans to poorer customers, but she noted that this comes at the cost of predatory pricing of services by banks and the loss of data privacy. Analysts have observed that the loss of data privacy may, nevertheless, be accompanied by an improvement in the ability of lenders to assess whether a loan will go bad or not, in other words, loan delinquencies would fall as NPLs decline. There is still much debate on the extent to which customer's data is compromised by open banking, but Nigeria's Federal Competition and Consumer Protection Council (FCCPC) has more than a few months of work to figure out how to protect financial service customers using digital financial platforms.
But what is clear is that the age of AI and ML is here. Financial service delivery going forward will be more preemptive than reactive and service providers will be more aware of customer's service expectations and experiences than they were in the past (see illustration 1 below).
Illustration 1 Financial Service Delivery in the Age of AI
Nigeria's e-Banking: The Hookup
But while the FCCPC gathers its thoughts on the pricing of digital financial services the lending train appears to be moving along. Local banks have continued to push the digital payment and lending services hard and fast as e-banking revenues rise as a proportion of gross bank earnings.
For example, in financial year (FYE) 2020 FBNH recorded gross earnings of N579.4bn of which N48.68bn or 8.40% came from its e-banking activities while its close rival Access Bank made gross earnings of N764.72bn with N56.09bn or 7.33% attributable to electronic banking activities of the bank. UBA came third in the e-banking-to-gross earnings log with the bank posting gross earnings of N620.4bn and an e-banking income of N44.25bn or 7.13%.
At the other end of the table, Stanbic IBTC had the lowest proportion of e-banking income to gross earnings of 1.17% with gross earnings of N234.45bn and e-banking income of N2.94bn at FYE 2020. Second, from the bottom was Fidelity Bank with gross earnings of N206.2bn and an e-banking income of N2.46bn or an e-banking income as a proportion of gross earnings of 1.19%. What analysts found a bit surprising was that GT Bank despite steady growth in its retail banking operations in the last few years saw its e-banking income as a proportion of its gross earnings crawl at a relatively slow 2.59% with e-banking income of N11.77bn over gross earnings of N455.23bn in financial year (FY) 2020 (see table 1 below).
Table 1 The Nigerian e-Banking Logbook in 2020
Analysts have noted that the recent Q1 2021 data on e-banking revenues show that FBNH despite the drama around the sacking of its Board of Directors and its hitherto unknown forbearance status with the Central Bank of Nigeria (CBN) was able to pull off an impressive e-banking revenue coup with the highest e-banking revenue to gross earnings ratio for all banks listed on the NGX, this may be explained by the Holdco's large and expanding agency banking network of over 86,000 agents across the country.
FBNH's agency banking operations appear to have been the hub of a fast-moving and aggressive service delivery wheel. Indeed, looking into the future, analysts believe that the holding company could strategically position itself to use its massive market data to provide open banking services that would increase its market penetration, broaden its gender inclusion and refine its user experience and customer interaction (UX/UI) across new market segments. Analysts believe that increased adoption and deployment of artificial intelligence (AI) and machine learning (ML) could help the lender to derisk its loans and improve its non-performing lending assets (NPLs) as its loans-to-deposit ratio (LDR) rise. Of the thirteen (13) banks listed on the local stock market (NGX), FBNH had the lowest loan to deposit ratio in Q1 2021 meaning that it would likely have incurred one of the largest CBN penalties debited against its cash reserve ratio (CRR) for the quarter (see table 2 below).
Table 2 A Quick Look at Nigerian Banks Q1 2021 NPLs and LDRs
Bridging the Present, Past, and Future
The old days of banking without sophisticated analytical tools had their strengths in that it required the development of individuals into behavioural analysts, accounting experts and subject matter industry specialist.
However, human beings with their foibles provide less reliable interpretation of data and are potentially influenced by sentiments and personal biases making the outcome of their decision-making less dependable. With artificial intelligence, machine learning and big data the basis of preempting customers needs and meeting their expectations becomes less arbitrary. Financial lenders in contemporary times can break down customer data into a series of reports that onion slice the needs of each customer given the constraints of the business environment and the future outlook of an industry. At an individual level, the use of AI and ML will produce reports that would enable lenders to build services around the customer's experience journey and aspirations.
The new Nigerian financial lender is a cyborg with machines running complex and critical calculations to complement the banker's deep industry knowledge and unique customer insights. Today's financial service manager or banker will metamorphose further as data becomes broader and deeper and machines develop better analytical capabilities.
The new AI game will produce winners and losers.
The winners will include:
Illustration 2 The New Digital Ecosystem
The Losers will include:
Illustration 3 Eyes on New Technologies
The Future of Now
Technology has taken a swing at old-world economics and is establishing new paradigms of how people interrelate and collaborate. The emerging trends establish the fact that payment transactions will become faster, more flexible and broader by penetrating hitherto difficult locations to reach.
Indeed, the ability to exactly dimension a borrowers spending and saving habits suggest that micro-lending, micro-insurance and micro-leasing will increase and grow rapidly as lending institutions prepare themselves with the right amount of data and the enormous power of analytics to establish risk profiles and make carefully measured lending decisions.
Another shift in the evolving lending architecture would be the adoption of digital records of borrowers with a permanent register of delinquent loan-takers. The profiles of hardcore debtors would be on a referable digital register that would allow lenders easy access to information across lending platforms and institutions. A platform that has taken a headstart in providing such an archived and searchable digital database is Debtors. Africa.
In a report published in 2019, the delinquent debtor digital database managers noted that "If there is one characteristic that will define the success of winners and losers in the new loan ecosystem it is transparency, banks hiding delinquency behind a stump of grass will soon discover that their nakedness is as clear as that of a day-old baby. The only way for banks and their borrowers to create a sustainable credit environment is for them to stand digitally undressed, with the delinquent borrower's character open to the world to see and make judgment calls" (www.debtorsafrica.com/).
"In God we trust, everybody else must bring data"
Data is the haemoglobin of the financial payment and loan systems. The customer and lender's journey experiences in 2021 will be increasingly anchored on the amount of shared data that exists within the credit and payment ecosystem. The more data that exists and is shared the better the system becomes and the easier it would be to create retail loan assets with minimal default risk this should see deposit money banks comfortably raising their LDRs and reducing their NPLs, of course, the high Central Bank of Nigeria (CBN) cash reserve ratio (CRR) of 27.5% would rein back lending growth but the pull would be less severe with lower lending risks.
The rise of the data age will intensify technology applications in financial markets and increase transaction speed, data-induced resource distribution, investment allocation and loan creation. Analysts generally agree that the future of data is here.
With the Nigerian economy (GDP) growing at 0.51% in Q1 2021 and inflation towering at 18.12% both fiscal and monetary authorities have found themselves in a sticky place with the policy choices requiring fiscal and monetary expansion to pull the growth rate up but without prodding a rise in domestic inflation, so far the policy gymnastics has not been pretty.
However, it does appear that a ready tool for faster GDP growth is credit expansion, but this must be done without creating larger non-performing loan assets. This could be where artificial intelligence and machine learning adaptations prove to be welcome gems in the rough. The normality of adaptive technology in financial transactions may just be what the doctor prescribes for an economy in need of credit to support growth.
3. Banking Sector Records 3.46bn Volume of Transaction in Q4 2020 - NBS
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