We can’t debate the fact that Technology has changed the banking sector in a big way. Not forgetting in the 10th century, the de facto mode of trade was barter trade. Then came the introduction of coins that was when the idea of banks came to actualization. Well, technology has been moving very fast forcing revolutions after revolutions in the sector. We all know it is now possible to send cash from one continent to another via the internet. That could have been impossible to imagine back in the A.Ds.

Banks are on their toes trying to cope up with the dynamic demands of their consumers. The market demands for secure, cheap, flexible, 24/7 hour available services from the financial institutions. With the help of technology, this has been achieved, but consumers’ demands never end. AI and ML are actively helping the sector to continuously come up with innovative inventions to keep the industry relevant to the dynamic market.

Due to the demands, the market led to the birth of Fintech, an industry that has attracted a lot of attention to the investors. Honestly, everyone is a sort of a shylock within their circle. At some point in life, you have lent some cash to your friends, neighbors and/or family members who at some point did not accrue some interest or in the worst-case scenario did not pay back the loan. Most of the Fintech deals with small loans for emergencies making it have a bigger target market.

Common! Don’t get lost, we started with Barter trade then the banks and now we have banks with innovative services and Fintechs. What keeps the banks and Fintechs relevant to the current market is the ability to provide the services conveniently and cost-effectively. It is now possible to get a loan without a bank account, without listing your property as security and without begging your uncles to guarantee the loan (Am sure Caesar can’t understand the financial dynamics of the 21st century). These, however, make lending institutions to make desperate moves by lending out money without surety of getting it back.

When venturing into the lending business, it is very important to get your strategies right before getting into the business. There are two common models in small scale lending; Volume scale and risk-averse model.

The risk-averse model involves lending to a small well-analyzed group. This means limiting your service to a defined group only. This is usually a safe model since it involves lending to customers whom you can reach and have someone accountable for their whereabouts. Well, the model does not involve lending to a bigger market, but it is always safe since the default rate is usually low. Therefore, the money you would have spent recovering unpaid loans will be recorded as income.

Volume scale lending model, as the name suggests, this is where you target to lend to as many customers as you can reach. Anyone that will have access to your lending services, they can get a loan. Well, this model will get you massive customers that will be consuming your lending services and that will mean that you are cashing out a lot of money. Of course, the model will be backed up with good and effective marketing strategies to entice the customer into using your services. The disadvantage of this model comes when collecting your money from your customers; this usually comes with a high default rate and therefore costing you handsome cash doing recoveries.

When you decide to go with Volume scale lending model, most lending institutions lend at a higher interest rate to cost-share the loss incurred by defaulted loans, and also they put in place good, secure, effective and reliable credit scoring mechanisms to help them know who are potential defaulters before lending them. The credit scoring mechanism is also used when doing a risk-averse model, it is very crucial to segment your market into groups, knowing which group is not risky to lend to and which one has a higher possibility of defaulting the loan.

Existing, yet outdated credit processes have often isolated many customers that are underbanked, underserved, and ignored. Driven by rigid score cut-offs, banks were renowned for rejecting potential consumers, even if they were only one point below. Still, under the influence of the credit crisis, banks often focused on the debt-to-income ratio based on salaries vs. total monthly payments, to generate profiles, and justify rejections for payments above 50%. Even when a consumer’s scores recovered, banks often continued to avoid their portfolios. At the end of the day, banks have spent much of the past 10 years chasing premium borrowers, yet that slice of the market is largely tapped out. To their detriment, they did not factor in how consumers managed their checking, savings, and money market accounts, and by doing so, isolated millennials, immigrant entrepreneurs and other consumer groups that showed high potential, yet did not qualify for the traditional credit cut-off.

In the world of credit scoring, Machine Learning modeling platforms are a powerful tool for gaining insights, within a relatively short time, into the potential opportunities in a market, or into the potential of new data sources previously overlooked. Based on re-engineered financial data from Mobile money, and new trusted data captured online, AI and Machine Learning technology can be used to leverage existing internal modeling processes used by lenders to perform smarter underwriting. As a result, lenders are seeking a new way of implementing AI technology in credit scoring, using a more transparent solution that is not influenced by biased figures and information

Recent advances in AI credit scoring technology, are finally overcoming major transparency and stability pitfalls, in a bid to deliver a more robust solution that is ready for full-scale adoption. This was the missing part of the first generation of AI solutions for credit scoring. Applying this next-generation AI technology can lead to more business for consumer lenders without the need to increase risk. How can advanced credit scoring technology benefit you?

Do not get into the field blindly, research, ask for advice and finally get that trusted partner that will help you with the business. Several digital lending companies can facilitate your lending business and ensure you do not make a loss. Do not hesitate to get in touch for quality, reliable services.