How Artificial Intelligence is helping Financial Institutions to Function Seamlessly

(Isstories Editorial):- Mumbai, Jul 2, 2018 ( – Banks and financial institutions deal with massive swathes of data as part of their routine functioning. Speaking of which, we sure dont quite have to get into the enormity of data that banks and lending institutions deal with it is pretty much unfathomable. To process such immense volumes of information is impossible without the presence of powerful technological systems such as AI and Big-Data Analytics, which have all but become a paramount necessity in recent times. Millions of potential customers, millions of credit reports, and several millions of dollars in trade and investment.. Phew! Makes you flip out of your skin, doesnt it? As such, the importance of Artificial Intelligence hasnt been more than what it is in the present day. Banks that offer unsecured personal loans, secured credit products and investment options cannot function optimally if not for these technologies in place.  

It isnt surprising to note that even new-generation lenders such as Fintechs that offer a wide range of credit products such as instant personal loans, while also developing online platforms for investment and savings, have also started relying on Artificial Intelligence in congruence with big data technologies to function without hiccups and inconsistencies.

In this article, we look at how artificial intelligence is playing a colossal role in helping banks and lending institutions scale up their processes and improve the efficiency of service delivery.

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Fraud detection and prevention

We dont necessarily have to emphasize on the importance of fraud detection in the banking industry. Banks and lending institutions are even till date, susceptible to the ill-effects of fraud. Being doubly prepared and striving to reduce the frequency and intensity of fraud is perhaps the best way that banks can tackle this menace. In light of an increasing incidence of bank fraud which is also becoming more innovative and devious in current times – banks have constantly been increasing their spending on improving their security systems to keep a good distance from the perilous impacts that frauds entail.

Investing in artificial intelligence seems to be the only and most effective way to reduce the frequency of attacks. Through AI technology, behavioural patterns of processes are recorded, and any deviation from the usual flow of procedures will trigger an alert, helping systems to get notified immediately and prevent follow-through.

Improving customer engagement and service delivery

Artificial Intelligence technologies are significantly assisting lending institutions in improving their overall service delivery. Along with big data analytics, AI technologies help to understand customer preferences and experiences better, thereby directly contributing to improvement in service delivery. By way of this, lenders are able to engage with customers at a deeper level and devise processes that are more customer-centric in nature.

A good example of this is the emergence of the Chat-Bots that most lenders are incorporating in their service delivery and customer engagement systems these days. Through big data analytics, the most probable queries that the general consumer might have been recorded and analysed, and a chatbot automatically engages customers in answering queries that they have, instantly. This has of course, largely been made possible through the evolution of AI technologies in the recent past. Talking of how far the scope for banking processes being influenced by AI goes, it is safe to declare that the potential is pretty much limitless.

Managing the element of risk

Risk assessment, particularly in the lending industry, is supremely important. To evaluate the element of risk individually in millions of cases is technically impossible if not for the presence of a potent technological setup. Big data analytics and AI, however, literally make this easy. Risk evaluation algorithms are embedded with elements of AI to almost immediately determine risk factors, thereby helping lenders identify creditworthy customers and provide them with access to credit. This is mostly true in the case of unsecured credit as it does not involve collateral. Secured loans, on the other hand, involve legal assets to be pledged as collateral, thereby helping banks recover their money through asset sale and auction.

Lending institutions obtain information on a customers credit profile almost immediately and determine their eligibility automatically through risk-evaluation algorithms, an aspect that has particularly assisted Fintechs to expedite their processes and massively reduce turnaround times.

Algorithm-based trading

Another area where AI is enabling seamless functioning is in trade and investment. This aspect, although not very pertinent to the lending industry, is substantially important. Banks use AI embedded systems to swallow inputs from multiple sources and understand market trends to automatically carry out investments and trade. Reports reflect that a whopping 70% of investment and trade carried out by banks is powered by Artificial intelligence systems in congruence with big-data analytics.

Qbera, a leading Fintech company that offers online personal loans to salaried individuals, uses its proprietary risk-based algorithm to perform risk evaluation on individual loan applications, and generate instant approval based on a customers credit profile.

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Source :Qbera

This Press Release was originally published by IssueWire. Read the original article here.