Digital Lending: How data and AI scaling up the credit segment

The application of artificial intelligence and the availability of data can enable digital transition

Digital Lending: How data and AI scaling up the credit segment

By Manish Khera

The financial services industry is still being disrupted by technological advances, which have also altered how consumers conduct financial transactions. People can now easily use digital platforms to make payments online, send money between accounts, make investments, and apply for loans from any location at any time. Furthermore, for Financial Institutions (FIs), the digitization of the lending process has many powerful advantages, such as data-driven marketing, a better customer experience, quicker and smarter decision-making, better reliability in the lending process and portfolio performance, and major cost savings. Thus, with the introduction of digital lending, the lending sector has seen a substantial upheaval recently. Borrowers now have easy access to and efficiency throughout the entire lending process thanks to the use of digital channels like websites and mobile apps. The application of artificial intelligence and the availability of data have enabled this transition (AI).

Here’s a look at how data and AI are transforming the credit segment:

Data in Digital Lending

Data is the bedrock of digital lending, and it is essential in establishing a borrower’s credit. Digital lending platforms, in contrast to traditional lending, leverage a variety of data sources, such as social media profiles, online behaviours, and geolocation data, to build a more thorough and precise picture of a borrower’s creditworthiness. Lenders can build a more comprehensive real-time picture of a borrower’s credit by utilizing non-traditional data sources, which gives them the ability to make better loan decisions.

AI in Digital Lending

When dealing with large amounts of data, artificial intelligence can be helpful. Lenders can make choices in real time, as AI systems can handle massive amounts of data rapidly and accurately. Data correlations and patterns that humans might miss can also be found by machine learning algorithms. In addition, AI can also be used to automate the lending process, including the processing of loan applications and loan underwriting. Automation can assist the loan application process while lowering the chances of errors.

Personalization and Financial Inclusion

The flexibility to give customized loan offers is one of the main advantages of digital lending. Digital lending platforms can leverage data and AI to generate individualized loan offers that are catered to the requirements of each borrower. This strategy can make borrowing easier and enhance the chances that the loan will be reimbursed. Moreover, digital lending platforms can provide loans to applicants who would otherwise be viewed as excessively risky.

Mitigating Risks

Digital lending may provide advantages, but there are also concerns when using AI and non-traditional data sources. It’s potential to cause lending bias is one cause for concern. Rigid data quality and moral AI standards are necessary to reduce these perils. Thus, in order to do this, biased data must be identified and eliminated, data privacy and security must be maintained, and AI systems must be periodically audited for biases. In order for borrowers to comprehend how their loan offers were created, it is also critical to make AI algorithms transparent and understandable.

Final Takeaway!

The credit industry is changing as a result of the usage of AI and data, making lending more effective and accessible. Digital lending platforms can build a more complete and accurate picture of a borrower’s credit using non-traditional data sources and AI, allowing them to make better loan decisions. These platforms can also offer tailored loan offers, increase credit availability for underprivileged groups, and encourage financial inclusion. Thus, to reduce potential risks, it is crucial to have strict data quality standards and ethical AI procedures.

The author is founder and MD, Happy

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First published on: 05-03-2023 at 13:00 IST
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