Automation is expected to enter into multiple financial processes. Evaluating the creditworthiness, for a net 30, 60, etc, of applicants use to be based on proprietary algorithms focused on the FICO score.
Lately, more lenders started using alternative scoring factors such as education, rent paying or even social media behavior. Assessing so many aspects simultaneously and in-depth is a daunting task for human underwriters but can be easily performed by trained algorithms.
Big Data and Process Automation will be the tools used to replace repetitive procedures, speed up decisions, and eliminate human errors. Credit processing could be shortened from days to seconds, and the paperwork minimized or eliminated.
Here are a few ideas for how this will become a reality of the next decades. Some of these already exist, while others can be considered Sci-Fi. A first takeaway is that clerks should look for new jobs, the age of machines is here.
Automatic Risk Assessment
The main ingredient of automation for credits will be the change of the risk assessment. Right now, financial experts with a strong background in statistics develop and test models.
In the future, we can expect that Machine Learning algorithms will go through millions of records and learn from these what makes a good borrower.
Since these tools are excellent at pattern detection, they will not rely anymore on logical correlations, but will look for the truth even there where the mind would not instinctively go. Those suffering from bad credit will no longer have to make their own review of credit repair companies, but they could be redirected to one that is specialized in their situation.
Furthermore, the evaluation of a credit requirement will be analyzed in one go, no need for different departments to put their approval stamp.
Both individuals and companies move locations, and sometimes things change so fast that decade-old monitoring tools are not able to keep up.
Thanks to the Internet we are more mobile than ever, and this brings new opportunities related to earnings and income.
Companies can grow exponentially in a matter of months.
This is why real-time data can make a difference. Imagine you are the CEO of a unicorn start-up and bureaucratic rules prevent you from taking the loan you need just because your company is not one year old yet.
In fact, real-time data is more than just financial data. It can show trends, growth patterns or market demand. Usually, it’s collected from very different sources and merged seamlessly.
A high-paced world requires fast and secure transactions. The blockchain technology is almost a decade old and has proved to be able to sustain these objectives.
Furthermore, since the logs are public, every transaction is verifiable even by third parties, which reinforces the transparency feeling. These peer-to-peer networks are also highly automated, therefore using a similar model to approve credit lines would require only smart contracts instead of man-hours.
To be as effective as possible these platforms will use a high degree of integration. Supply chains will move in the cloud and vendors will connect with clients, the history of the transactions will be widely available, and the cash-flows will be easier to supervise.
This type of integration will help create even better smart contracts. These could also approve themselves if specific positive patterns are determined.
For example, if a potential borrower shows a strong track record of on-time payment and the amount they require is within their projected payment possibilities.
Last but not least all these steps will be conveniently carried out on a mobile device. We can expect to see more credit apps in the future, both in the B2C and B2B sectors.
All the information included in these apps will be updated almost in real-time and will reflect the latest changes. Following the introduction of robo-advisors, we can expect that these apps will also act as personalized financial counselors.