When it comes to harvesting vast amounts of consumer data, the global financial industry is undoubtedly sitting on a pile of gold. If we simply account for the innumerable applications financial institutions receive on a regular basis either for opening a new bank account or simply performing a credit assessment for loan origination; we will quickly see that global financial institutions are sitting on a pile of priceless information which unfortunately most do not know how to leverage.

The above scenario explains the reason as to why artificial intelligence & machine learning is the need of the hour for the global finance industry; however, the question remains as to how these institutions can leverage these technologies for their benefit.

This is exactly what we will be discussing in today's blog post.

The Role of Machine Learning & Artificial Intelligence in Lending

One of the first & most important aspects we need to understand is the essence of these technologies.

In layman terminology, artificial intelligence & machine learning can be interpreted as a set of intelligent offerings which are designed to mimic human intelligence.

Now while this is the broader use case of these technologies, in the specific context of lending, institutions can seamlessly leverage these to process vast amounts of data at unprecedented speed with precision & accuracy.

One of the most interesting reasons as to why the application of these technologies is amplified in the lending industry is simply because legacy systems & architectures do not host the capability of processing millions of applications. As a result of this, a large section of the population continues to be unbanked & underbanked irrespective of the meteoric rise in financial inclusion over the past couple of years.

In addition to processing millions of applications at scale, one distinct advantage of artificial intelligence & machine learning-enabled solutions is that they effortlessly remove the pre-existing biases in the system.

You see, the fact of the matter is that every human being, irrespective of their best efforts, is biased to a certain extent, however on the other hand, smart algorithms powered by artificial intelligence & machine learning depend on pre-programmed as well as consistently evolving logic and thus the chances of a bias impacting the outcome of a decision is few & far between.

By effectively boycotting bias in the decision-making process, not only can lenders service their products & offerings to a wider array of customers but also ensure that every creditworthy customer is able to leverage a loan they rightfully deserve.

Last but not least, by leveraging artificially intelligent lending solutions, lenders can significantly reduce their operational costs as a majority of their redundant & manual processes will now be automated, resulting in less human dependency. Not only with this contribute towards radically reducing the cost of operation but also a more focused & intuitive assignment of human resources.

In Conclusion

As financial awareness & financial inclusion increases among consumers from varied geographies & all walks of life, it is crucial that lenders develop the required skillset to process & extend financial lending instruments at scale & in a cost-effective manner & it is our belief that adopting artificial intelligence & machine learning in lending and global finance in general is the appropriate pathway to reach the same.

Thank you for reading & I will see you in the next one.


The Reference Shelf

  1. How AI and Machine Learning are Changing the Lending Landscape? [Link]