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INTERNET | Internet Software & Services / Accounting & Finance
creditvidya.com

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Founded Year

2012

Stage

Series B - II | Alive

Total Raised

$10.15M

Last Raised

$3M | 3 yrs ago

Mosaic Score

+20 points in the past 30 days

What is a Mosaic Score?
The Mosaic Score is an algorithm that measures the overall financial health and market potential of private companies.

About CreditVidya

CreditVidya is a platform that provides AI-powered credit underwriting APIs to NBFCs, other financial institutions and companies. CreditVidya helps lenders make critical decisions based on credit scores assigned to new-to-credit and thin file customers through non-traditional data sources.

CreditVidya Headquarter Location

2nd Floor, Block 2, My Home Hub,Hitech City Road

Hyderabad, 500 081,

India

040-4852 1334

Latest CreditVidya News

NABARD can use AI and ML to create credit scoring registry: Finance Ministry report on FinTech

Sep 4, 2019

A report by the Department of Economic Affairs, under the Finance Ministry, on fintech noted that fintech companies like Credit Mantri, CreditVidya and Samunnati were using AI and ML to create an alternate lending data score. It recommended that NABARD (National Bank for Agriculture and Rural Development) work along the same lines as these companies and create a credit registry for farmers for credit scoring, default analytics, predictive crop analytics, repayment monitoring, fraud control, and improving efficiency in credit services. It’s worth noting that CreditVidya was found to be embedding tracking software in certain mobile apps, which gave it the access to a person’s GPS locations, and business SMSes from ecommerce sites and banks, according to a HuffPost India report . The user data was used to power CreditVidya’s algorithms that help lending companies determine the credit-worthiness of loan applicants. It ran this code for several months in 2017. Here are some key recommendations made by the DEA surrounding AI and ML: 1. PSU banks can use AI and ML for risk management: The report recommended that the Department of Financial Services (DFS) and PSU (public sector undertaking) banks use AI, ML and cognitive analytics for risk management, compliance management and fraud control. It also said that the DFS and PSU banks should work on a roadmap to adopt these technologies in a time-bound manner. 2. AI can help in better compliance: AI has the potential to help firms detect compliance risks and make better-informed decisions about how to mitigate them, the report noted. It said that RegTech (regulatory technology) can reduce firm-level compliance risks and also reduce supervisory risks. The committee recommended that the financial sector regulators, such as RBI, SEBI, IRDAI, and PFRDA, must develop standards and use-cases for RegTech by financial sector service providers to make compliance with regulations easier, quicker and more automated for regulated entities. 3. Automation of compliance process: The FCA (Financial Conduct Authority) in the UK is experimenting with machine readable regulations, giving an impetus to the automation of compliance processes, the report said. It proposed creating a semantic web page – a web page similar to the current structure of the World Wide Web, but data and information on it can only be processed by a machine. The report said that AI can be used to construct such a web page which would in turn reduce the need for human intervention in compliance processes thus increasing the efficiency of the system. 4. AI can improve the cyber-security architecture: AI can be used by financial institutions including fintech firms to  prevent cases of fraud and cyber-attacks, it notes. It highlighted that tools, systems and algorithms are being designed to detect cases of fraud or potentially fraudulent activities. “AI enables companies to track historical data of individuals through which any suspicious or outlier activity can be captured,” it added. 5. AI and regulatory compliance: Financial reporting has become more numerous and complex, the report noted. It added that this has placed upon companies an increased burden vis-a-vis compliance costs. “It has been noted in many quarters that AI could be harnessed to automate compliance processes which would enable saving of costs and time,” it said. 6. Auto-insurance claims can be made smarter as well with the use of AI and big data by use of image-based assessment smart insurance system, the committee said. It proposed that images of the accidental vehicle could be used and a claim amount could be calculated by tapping on a database of vehicle model(s) and part(s).

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Expert Collections containing CreditVidya

Expert Collections are analyst-curated lists that highlight the companies you need to know in the most important technology spaces.

CreditVidya is included in 5 Expert Collections, including Banking.

B

Banking

1,090 items

D

Digital Lending

1,335 items

This collection contains companies that provide alternative means for obtaining a loan for personal or business use and companies that provide software to lenders for the application, underwriting, funding or loan collection process.

P

Payments

1,971 items

Companies and startups in this collection enable consumers, businesses, and governments to pay each other - online and at the physical point-of-sale.

A

Artificial Intelligence

8,323 items

This collection includes startups selling AI SaaS, using AI algorithms to develop their core products, and those developing hardware to support AI workloads.

F

Fintech

3,300 items

CreditVidya Web Traffic

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