How banks can avoid disruption with data analytics
Over the last decade, the number of mobile money providers and lending platforms in African markets has surged. As smartphone penetration rises and data costs decrease, a growing number of Africans are switching to digital banking.
Over the last decade, the number of mobile money providers and lending platforms in African markets has surged. As smartphone penetration rises and data costs decrease, a growing number of Africans are switching to digital banking.
Last December, three digital banks announced their launch in South Africa, the continent’s most advanced banking sector. Their lower cost structure and aggressive customer acquisition plans will help to capture a larger share of the banking market but, contrary to doomsday predictions that traditional banks will be disrupted and forced out of the market, they do not pose an existential threat to traditional banks.
With their scale and legacy, incumbent commercial lenders still dominate the banking sector, but they shouldn’t be complacent when faced with technology-driven changes in the industry. To compete with up-and-coming digital banks, traditional banks should turn to advanced data analytics which uses algorithms to analyze large data sets and draw actionable insights. Here are the 3 reasons why brick-and-mortar banks should employ data analytics.
1. Win Unbanked Customers with Innovation
Traditional financial service providers (FSPs) can use data analytics to acquire new customers, especially among the unbanked population. Over the last decade, sub-Saharan Africa has made progress in closing the financial inclusion gap — with financial inclusion rates increasing from 23% in 2011 to 43% in 2017 — largely due to surging mobile money adoption. While mobile money has focused largely on transfers and payments, the next wave of financial technology platforms has expanded into lending.
Fintech startups such as Branch, Paylater and Bank-MNO offerings like M-Shwari and Fuliza, analyze alternative data sets, such as airtime top up and bill pay, to determine credit risk and lend to unbanked customers. To compete with fintechs for unbanked customers, banks can team up with third-party data analytics providers. For example, SuperFluid Labs’ SuperScore allows lenders to manage life-cycle credit risk by building credit scores for customers from multiple data sets using the power of Artificial Intelligence.
Moreover, data analytics enables banks to hedge against loan defaults. African banks continue to struggle with a high rate of non-performing loans (NPLs). For example, in Ghana, over one-fifth of total loans are NPLs while Kenya has a 10 percent NPL rate, as compared to the global average of 3-4 percent. Using data-driven risk assessment tools, credit officers can predict customers who are likely to default on loans. These insights allow banks to expand their loan books, increase revenues from interest payments, improve recoveries and hedge risks.
2. Upsell and Cross Sell Products
Data analytics can also help banks to optimize sales from existing customers, leading to opportunities to upsell and cross-sell new products and services. The global banking industry could increase earnings as much as $1 trillion annually with one-fifth of this increase resulting from informed pricing and promotion strategies. Thanks to mobile data, African fintech companies have access to rich insights into their customers -- their age, gender, online behavior, purchasing power, and geographic location.
These insights are a gold mine as they enable companies to develop tailored products addressing users’ pain points. Banks should follow fintech’s lead, using data insights into customers to offer new products. At SuperFluid Labs, after analyzing customer data for a banking client, we observed that a large percentage of customers, clearly cash-strapped, were regularly drawing down their savings accounts. We, therefore, proposed that the bank offer a new credit product, using the savings account as collateral.
3. Develop Powerful Partnerships
With their increasing push into markets and sometimes explosive growth, African fintech startups can seem like the mortal enemy to FSPs. But, this viewpoint is more fear than reality. Fintechs and traditional banks have mutual interests in working together. Data analytics is the crux of a successful partnership, bridging the differences between the two types of companies. While the global financial services industry is increasing spending on IT infrastructure, many African banks, hamstrung with macro-economic headwinds and legacy technologies often struggle to maintain pace with rapidly changing customer expectations.
In contrast, fintech startups are early technology adopters and are much faster to experiment and innovate, giving them a first-mover advantage. In turn, traditional banks can provide fintechs and their new offerings and use cases with market access, brand credibility, guidance and improved relations with regulators.
Bank and fintechs can combine their natural strengths to pursue historically underserved customer segments, such as small and medium enterprises (SMEs), and retain existing customers through improved customer experiences. Third-party data providers play a critical role in ensuring successful partnerships between banks and fintechs. Not only do they offset limited digital and data expertise and in-house talent shortage, they can help bridge a potential culture gap between banks and fintechs by fostering a data-first ethos within brick-and-mortar banks.
Sub-Saharan Africa’s financial services industry’s poor banking and electronic transaction infrastructure was its Achilles heel and led to the rise of fintech companies. Data analytics can help banks maintain an edge against new entrants in the market. Using data, banks can ward off fintech competitors by investing in innovative data analytics solutions. Higher customer acquisition, lower NPL rates, and upselling and cross-selling opportunities are just some of the benefits that data can bring to banks. With the help of data, banks can stay one step ahead of their noisy fintech counterparts.
Timothy Kotin is the co-founder of SuperFluid Labs, a data analytics company based in Ghana and Kenya.
Source:
How banks can avoid disruption with data analytics- gist culled from
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