By Maninder Singh Grewal, Chief Growth Officer, mPokket
As artificial intelligence becomes ubiquitous in people’s daily lives, AI-enabled digital tools have almost wholly supplanted one-to-one communication. Nearly all industries now deploy AI in their operations, including financial and lending businesses.
AI comes in two categories – supervised and unsupervised. In the first case, humans formulate specific rules and the AI software segregates the data as per these guidelines. In the second, AI algorithms are used in pinpointing patterns in information with data points that are not classified or labelled.
In essence, AI masters a lender’s underwriting norms such as collateral value, borrowers’ experiences and so on. Unlike humans, AI can check thousands of applications speedily and then categorise them according to profitability or default risk.
Speed, Reliability, Accuracy and More
Using AI, lenders scrutinise borrowers’ digital trail for creditworthiness after applicants download an app on their mobile phones. As the app feeds applicants’ data to a credit scoring portal, social media, browsing history, geolocation and other variables are scanned to create comprehensive profiles of borrowers.
To minimise delays and underwriting costs, large lenders utilise AI, helping them increase profitability per loan. A few tech entities have gone even further, deploying AI to automate the complete loan process since it ensures minimal bias and better loans.
Legacy bankers and fintech firms are constantly innovating, as adapting to novel technologies while catering to a broad customer base have emerged as the need of the hour for both. Fintech entities have successfully employed AI and ML (machine learning) for designing products that suit customers’ evolving requirements. ML has benefitted the lending segment in a major manner by permitting faster and more accurate decision-making through the analysis of customer data, trends and usage patterns.
Supported by sophisticated tech tools, lenders can onboard customers digitally, aggregating applications and auto-populating verified data into forms via various channels. Thereafter, the profiles are run through a decision-making model equipped with the required checks and balances to ensure healthy credit decisions. In this manner, the screening procedure is streamlined and any likely bad apples are identified without prejudice.
Buoyed by the benefits, AI, ML and other disruptive digital tools are gaining popularity in several segments. The fintech industry in particular has leveraged these technologies to design products that meet customers’ dynamic requirements.
After a user is given credit, the ML models work to pinpoint anomalies in the usage pattern. Varied micromodels are used in analysing and predicting creditworthiness or any changes in risk. Such models can be self-reinforcing. In essence, every time users make payments, the model identifies their standing in the credit cycle, whether payments were made on time or not, etc. Going by users’ payment history, the ML model can be used to make well-informed decisions such as reducing interest rates for borrowers paying on time consistently.
Thanks to the advent of AI-enabled lending institutions, the banking and financial services segments have been transformed. As a result, the entire lending process beginning from the loan application up to the approval and disbursal has been digitalised. While earlier lenders used conventional means to do due diligence, digital tools ensure ample data of each applicant can be procured. Subsequently, insights are gleaned from this data, making loan management simpler.
Minimising Fraud and Automating Decision-making
Similarly, AI-enabled algorithms help minimise financial fraud. Although an applicant needs to upload a government-verified identification card, make a live submission of his/her photograph and fill in relevant details, financial fraud is still a possibility. But by using biometrics, OTPs (one-time passwords) and AI-linked firewalls, digital lenders are establishing a secure and reliable framework to ascertain consumer data is not compromised or exploited. With data security tools embedded at every stage, online platforms are redesigning security networks and addressing typical data threats.
Furthermore, by using thousands of variables, including an applicant’s credit score, banking history, etc., the in-built AI-enabled system limits the chances of financial fraud by making informed credit decisions. Such agile software platforms enable business leaders to standardise decision-making with robust rules and business logic. The models are then augmented with ML capabilities that improve decision-making by continuous learning through sustained data entering the system. This limits the possibility of bias or human error, speeding up the decision-making process.
Automatic credit decision-making and risk intelligence enhance process efficiencies and customer experiences, reducing turnaround times as well as operating costs, providing greater compliance and enabling financial entities to be more proactive. Thereby, the prolonged, cumbersome paperwork and individual-centric decision-making are eliminated. Through tech tools, it is easier for lenders to shift from asset-based lending to the flow-based lending model.
Another advantage of AI-based systems is the automation of routine processes, speedy services, decrease in the costs of addressing standard issues and accuracy in processing humongous volumes of data generated daily.
Driven by the plethora of benefits from digitalisation, online lending platforms help consumers in procuring loans swiftly, apart from providing various other products and services. Given the secure platforms and robust networks, today digital loans are disbursed extremely safely and reliably.
Best of all, since digital lenders function 24×7, consumers can avail of emergency loans during times of crisis or distress. It only takes a few clicks for applicants to receive instant loans via their mobile phones. For customers who have earlier undergone the prolonged procedures of traditional financial firms and lenders, nothing could be better than receiving their loan confirmation within minutes.
