How can collaboration between governments, financial institutions, and the private sector be optimized to unlock the full potential of digital finance and credit for achieving financial inclusion?

Financial institutions have to deal with an important issue of financial inclusion that has become a genuine concern in recent years, solving many social and economic problems, because microfinance organizations are sometimes the only alternative to traditional lending.

In turn, government organizations also retain a very important role as supervisory and regulatory authorities, guarding the personal data of borrowers. It is important to note that with the penetration of new vendors, which do not use any personal data of a customer, online businesses can mitigate operational risks really well, using advanced technological credit scoring solutions, based on the digital footprint of the device (mobile phone in particular) and add more value to the data no one of their competitors even thought to use and increase the acceptance rate significantly as well as to exclude reputational losses related to severe data breaches and help the customer to start creating its credit history. At the same time, they obtain a rather heavy competitive advantage and are now able to create more tailored solutions, based on customer needs and user experience achieving financial inclusion at the same time.

What regulatory measures can policymakers implement to create an enabling environment that fosters innovation and competition in the realm of digital finance?

We do not undertake to judge the correctness of the decisions of government organizations, but we can safely say that the use of AI and ML in the decision-making pipeline will help avoid the consequences of some regulatory prohibitions.

For instance, Google has announced an update to its Personal Loans policy recently. The new policy will restrict personal loan applications from accessing user contacts or photos. “Apps that provide personal loans, or have the primary purpose of facilitating access to personal loans (i.e., lead generators or facilitators), are prohibited from accessing sensitive data, such as photos and contacts». Basing on alternative data parameters for fraud and alternative credit scoring, credit organisation can get a response, containing risk assessment and data vector for risk strategies and your decision engine.

In your opinion, how are traditional banks responding to the emergence of neobanks in Africa, and what does this mean for the future of banking in the region?

We believe that the future relations between financial institutions and neobanks lies in partnership, related to cooperative work with the rejected flow of applications. Speaking about borrower selection, banks have more strict and rigorous approach and this trend has increased lately: the share of approved application has dropped in many countries recently. Experts are attributing this this to the measures taken by governmental bodies against the growth of household debt load as well as decline in borrowers’ income.

This situation offers great promise for cooperation between banks and neobanks in order to work with the “rejected” flow of bank clients’ applications. Development of this cooperation will allow neobanks to get access to better traffic, because the segment of potential bank borrowers usually has better payment discipline and borrowing capacity. Access to the rejected flow of large financial institutions will reduce the cost of acquisition and lead generation.

How does leveraging data contribute to providing better services for the unbanked and underbanked?

Africa region lending market may be considered to be rather developed, millions of people living in this region still do not have access to traditional financial products. By means of technological development lenders may offer more tailored solutions for the so-called “unbanked” on “underbanked” consumers.
AI and ML technologies improve the speed and accuracy of fraud detection in financial institutions indeed. What concerns accuracy, these technologies are changing the very nature of risk management. In the past, risk professionals had to constantly look for additional sources of data that might add little or no value to the decision system as a result. Now we can process huge amounts of non-personal data, which are primarily safe for the end user and provide maximum informational value.

Speaking of speed, it also applies to a complete overhaul of the entire system. If earlier risk management was more of a means of responding to incidents that have already occurred, now many solutions allow you to create a proactive approach for online companies and work proactively. Especially taking into consideration vendors experience, because they bump into various new types of fraud everyday and eager to extend the use cases to all the market players

How would you think attendees will benefit by attending the 14th Africa Bank 4.0 Summit – Pan Africa?

14th Africa Bank 4.0 Summit – Pan Africa is an excellent platform for many businesses to increase the visibility of their products and services, it is also a great place to improve the networking process, boost companies brand and get the fast feedback and face to face contact.