How AI Is Transforming Lending and Loan Management
technological innovations in banking may change the way we knew and did
banking, in the very near future. Nowadays we can already do a lot by never
stepping into the bank – we can pay through debit cards, transfer money to
another account, withdraw money, and even apply for a loan online. No more
discussing with your banker face to face why you need a loan, or why you’re the
right candidate for the loan offer from the bank! Today the bank uses technology
to decide who is worthy of credit and who is not.
There are several credit ranking systems available worldwide today; they use sophisticated algorithms based on past spending and loan repayment behaviors to predict the future behavior of a potential borrower.
Read Also How Automation Impacts Mortgage Industry
What are Artificial Intelligence and Machine Learning?
AI can be seen as a subset of computer science that mimics human cognitive processes, which is achieved through learning, speech recognition, pattern recognition, and problem solving. You can say it’s an intelligence demonstrated by machines, similar to human intelligence. Machine learning is an application of AI that allows systems to ‘learn’ and improve without explicit human intervention; it uses huge volumes of historical data to do so.
Machine Learning and AI Boost Banks’ Capabilities
In banking, AI and ML are especially useful in loan application. With machine learning, computers can learn forms and expected answers. It can also simplify the jobs of underwriters and processors who review the forms and their data, using visual recognition. This releases underwriters and processors to perform high value tasks.
Through ML, officials can focus on ensuring that the mortgage process is on task, rather than wasting time on redundant tasks like document reviews. Thanks to automation, banks and lenders can concentrate of providing an enhanced customer experience instead of mere data comparison in standardized forms.
Both AI and ML are capable of learning numerous tasks and combining them to meet specific processes and demands. For example, a system can be trained to examine two wage slips and determine the wages the customer receives every two weeks, and use that to calculate annual income – and then compare it with the info on the application.
AI and Machine Learning Help Banks to Speed up Mortgage Processes
Both lenders and borrowers are interested in speeding up mortgage processes. Thanks to AI and ML, the entire mortgage application approval time has been drastically reduced. The mortgage approval process can be completed easily and the personal loan approval process can be settles in just a few days. Automated form analysis means human employees only need to review contact details, taking off days from the process.
This will help financial institutions to bring down operational costs and handle larger number of applications in the same amount of time. This will help increase the competitive capability and profitability of that institution.
These technologies can also help reduce delays and ensure that the professionals can go ahead with the process by taking action early on in case there is a deviation from the already established plan. For example, if the system identifies an unusual deposit in a borrower’s account, it will alert the relevant mortgage expert, asking for documents and information to clarify the matter.
Positive Effect of Employees
Generally when AI and ML are being talked about in a workplace, employees fear that they will be made redundant by the technology. However, here, the technology is only going to eliminate mundane tasks from their job description, and leave them free to divert their talents to higher value jobs. Employees will actually be empowered to perform better, eventually leading to customer satisfaction. However, employees would also be required to acquire new skills so that they can adapt to the technological innovations. In banking, these capabilities will enable players to bring down costs and time involved, and increase efficiency and productivity.
Other Advantages Offered by AI and ML in Lending and Loan Management
Apart from lower cost, faster processing, and employee satisfaction, there are a range of benefits offered by artificial intelligence and machine learning in financial services:
- Decreased loss of credit
- Reduced agency recourse risk
- Diminished service expenditure
- Decreased due-diligence expense
- Greater orientation revenue
- improved risk-adjustment margins
- Fewer fraud related losses
- Significant reduction in bad loan write-offs
To Sum Up
Whether we like it or not, there is no doubt that like every other industry, lending, mortgage and loan industry is also slowly being dictated by artificial intelligence and machine learning. The manner in which these technologies are being handled including reduction in cost, quicker processing, streamlined operations, greater accuracy, higher revenues, increased customer satisfaction and more, there is no doubt that more institutions are likely to join the technology bandwagon. Surely we can expect beneficial outcomes for borrowers as well as lenders – a win-win situation.