The role of AI and related technologies in enabling various industry and service oriented businesses to scale greater heights has been quite the subject of awe and
admiration. Artificial Intelligence helps Fin techs and financial firms address and solve human problems, and consequently improve overall efficiency. As a matter of fact, multiple technologies have empowered financial firms to almost completely transform their processes and subsequently generate superior results – technologies such as Big Data Analytics, Neural Networks, Machine Learning and breakthrough algorithms have enabled financial companies to provide customers with a more refined experience, keep data sets intact and accurate, and make highly informed decisions to offset the unfavourable impacts of risk.
If we are to look at Artificial Intelligence, in particular, the impact has been absolutely tremendous in recent years. Through AI, Fin- tech firms and lending institutions have been able to more accurately assess a borrower’s creditworthiness by collating large swathes of data and instantly making viable lending decisions. Fin -tech firms, especially new age lending firms, have very actively adopted AI to scales up the efficiency of service delivery by making more accurate and seamless credits related decisions Let’s look at some areas where AI is empowering Fin-techs to make service delivery more seamless and unified.
Determining initial loan eligibility;
When you apply for an instant personal loan from
a Fin-tech lender, your credit profile is immediately obtained from the bureau and evaluated automatically through AI-powered algorithms. Various parameters in a customer’s credit report are analysed against Qbera’s internal credit norms and approval is determined almost instantly.
When you apply for an instant personal loan from
a Fin-tech lender, your credit profile is immediately obtained from the bureau and evaluated automatically through AI-powered algorithms. Various parameters in a customer’s credit report are analysed against Qbera’s internal credit norms and approval is determined almost instantly.
Retrieving information from Bank Statements:
Fin-tech lenders require customers to provide their bank statements as part of the lending process. AI- powered algorithms help to pullout essential information from lengthy bank statements in absolutely no time, allowing for quicker and more accurate profile assessment.
Chat bots for enhanced customer interactions:
Several lending institutions have been seen employing chat bots to make customer interactions more transparent and provide customers with a smooth and troublefree experience. Chat bots communicate with customers through AI technology, helping them with solutions to their queries, tracking transactions and obtaining product and service related information.
Several lending institutions have been seen employing chat bots to make customer interactions more transparent and provide customers with a smooth and troublefree experience. Chat bots communicate with customers through AI technology, helping them with solutions to their queries, tracking transactions and obtaining product and service related information.
Tracking flow of funds and money management:
AI,along with big-data analytics and block-chain, is assisting Fin-techs in accurately tracking fund flows and manage their money better. Tracking fund inflows and outflows, commissions, operational costs, risks sharing information, profits, determining interest rates on the case-to-case basis’ through risk based pricing, and other aspects of money management are carried out through AI-powered data and information frameworks.
AI,along with big-data analytics and block-chain, is assisting Fin-techs in accurately tracking fund flows and manage their money better. Tracking fund inflows and outflows, commissions, operational costs, risks sharing information, profits, determining interest rates on the case-to-case basis’ through risk based pricing, and other aspects of money management are carried out through AI-powered data and information frameworks.
Analysing information from credit reports:
Once the initial eligibility checks are carried out, AI-driven algorithmic frameworks allow fin-techs to scan through large amounts of information form lengthy credit reports to promote more accurate and errors free decision making. Risk assessments are carried out on a case-to-case basis and by way of information retrieved from credit reports and subsequent risk-based pricing, appropriate interest rates in line with projected revenue generation, unit economics and future growth aspirations are arrived at.
Fraud detection:
Another area where AI plays a major role is in fraud detection and busting. AI technological frame-
works help to instantly detect deviations pointing to potential fraud and help Fin-techs and banking institutions to shield themselves from detrimental effects emanating from lack of foolproof systems to tackle potential fraud.
Once the initial eligibility checks are carried out, AI-driven algorithmic frameworks allow fin-techs to scan through large amounts of information form lengthy credit reports to promote more accurate and errors free decision making. Risk assessments are carried out on a case-to-case basis and by way of information retrieved from credit reports and subsequent risk-based pricing, appropriate interest rates in line with projected revenue generation, unit economics and future growth aspirations are arrived at.
Fraud detection:
Another area where AI plays a major role is in fraud detection and busting. AI technological frame-
works help to instantly detect deviations pointing to potential fraud and help Fin-techs and banking institutions to shield themselves from detrimental effects emanating from lack of foolproof systems to tackle potential fraud.
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