Google Cloud Platform Case Studies BharatPe: Leveraging Google Cloud for Enhanced Data Analytics and AI to Promote Digital Payments

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	BharatPe: Leveraging Google Cloud for Enhanced Data Analytics and AI to Promote Digital Payments Google Cloud Platform

BharatPe: Leveraging Google Cloud for Enhanced Data Analytics and AI to Promote Digital Payments

Google Cloud Platform

Technology Category	Analytics & Modeling - Machine Learning Networks & Connectivity - NFC
Applicable Industries	Equipment & Machinery Finance & Insurance
Applicable Functions	Sales & Marketing Warehouse & Inventory Management
Use Cases	Fraud Detection Predictive Maintenance
Services	Cloud Planning, Design & Implementation Services Data Science Services
Challenge	BharatPe, a fintech company founded in 2018, aimed to make digital payments more accessible for over 10 million small offline merchants and kirana store owners in India. However, the company faced challenges in managing the massive amounts of data generated daily from payment processing to business analysis. Prior to using Google Cloud, BharatPe managed its legacy data warehouse with limited capacity to run a large number of queries. The company ran key performance indicator (KPI) reports, without the ability to understand real-time data patterns. Loading three months of data for quarterly reports took more than 30 minutes on the legacy system, and in some cases, queries failed because the system could not scale to support analytical needs. Additionally, BharatPe operates in a multi-cloud environment for disaster recovery and needed a data platform that could run queries against data, regardless of where it resides. Read More
About Customer	BharatPe is a fintech company founded in 2018 with the vision to make financial inclusion a reality for Indian merchants. The company makes digital payments more accessible for over 10 million small offline merchants and kirana store owners in India, with its interoperable UPI QR which was the first in India with zero transaction fees. The company also facilitates loans to offline merchants in partnership with NBFCs, and launched India’s first zero rental POS machine for merchants in 2020. BharatPe also offers consumer fintech products like postpe. Named as the 'Fintech Company of the Year' at India Banking Summit & Awards 2022, BharatPe serves a network of 10 million merchants across 300+ cities in India. Read More
Solution	BharatPe turned to Google Cloud to overcome these challenges. The company used BigQuery to process up to 80TB of data each day with minimal infrastructure management. BigQuery's capabilities allowed BharatPe to query several terabytes of data within minutes, with its capacity to concurrently run 100 queries by default, along with cache capabilities. The company also used Cloud Composer to orchestrate more than 1,000 data workflows between clouds, supporting its multi-cloud strategy. Document AI and Vision AI were used to extract data and insights from onboarding documents to automate its Know-Your-Customer (KYC) process. Additionally, BharatPe used machine learning to speed up loan approval decisions with minimal manual intervention from loan officers. The company also used BigQuery to analyze transaction data and create a loan profile on each applicant that determines the loan amount. Read More Log in to view content
Contents

Technology Category

Analytics & Modeling - Machine Learning

Networks & Connectivity - NFC

Applicable Industries

Equipment & Machinery

Finance & Insurance

Applicable Functions

Sales & Marketing

Warehouse & Inventory Management

Use Cases

Fraud Detection

Predictive Maintenance

Services

Cloud Planning, Design & Implementation Services

Data Science Services

Challenge

BharatPe, a fintech company founded in 2018, aimed to make digital payments more accessible for over 10 million small offline merchants and kirana store owners in India. However, the company faced challenges in managing the massive amounts of data generated daily from payment processing to business analysis. Prior to using Google Cloud, BharatPe managed its legacy data warehouse with limited capacity to run a large number of queries. The company ran key performance indicator (KPI) reports, without the ability to understand real-time data patterns. Loading three months of data for quarterly reports took more than 30 minutes on the legacy system, and in some cases, queries failed because the system could not scale to support analytical needs. Additionally, BharatPe operates in a multi-cloud environment for disaster recovery and needed a data platform that could run queries against data, regardless of where it resides.

About Customer

BharatPe is a fintech company founded in 2018 with the vision to make financial inclusion a reality for Indian merchants. The company makes digital payments more accessible for over 10 million small offline merchants and kirana store owners in India, with its interoperable UPI QR which was the first in India with zero transaction fees. The company also facilitates loans to offline merchants in partnership with NBFCs, and launched India’s first zero rental POS machine for merchants in 2020. BharatPe also offers consumer fintech products like postpe. Named as the 'Fintech Company of the Year' at India Banking Summit & Awards 2022, BharatPe serves a network of 10 million merchants across 300+ cities in India.

Solution

BharatPe turned to Google Cloud to overcome these challenges. The company used BigQuery to process up to 80TB of data each day with minimal infrastructure management. BigQuery's capabilities allowed BharatPe to query several terabytes of data within minutes, with its capacity to concurrently run 100 queries by default, along with cache capabilities. The company also used Cloud Composer to orchestrate more than 1,000 data workflows between clouds, supporting its multi-cloud strategy. Document AI and Vision AI were used to extract data and insights from onboarding documents to automate its Know-Your-Customer (KYC) process. Additionally, BharatPe used machine learning to speed up loan approval decisions with minimal manual intervention from loan officers. The company also used BigQuery to analyze transaction data and create a loan profile on each applicant that determines the loan amount.

Impact #1	The use of Google Cloud has significantly improved BharatPe's operational efficiency. The company is now able to process data at speed and scale for real-time decision making. The serverless architecture allows BharatPe to manage pipelines with a lean team. The company is also able to scale its data processing, especially for data-intensive workflows such as machine learning. The use of machine learning has also improved credit access for small merchants by speeding up loan approval decisions. BharatPe is now able to create a loan profile on each applicant that determines the loan amount, with some merchants getting their loans approved almost immediately. The company also uses machine learning for KYC and underwriting for its consumer-facing postpe app, helping customers get instant credit for buy-now-pay-later purchases, without the hassle of applying for a credit card.

Impact #1

The use of Google Cloud has significantly improved BharatPe's operational efficiency. The company is now able to process data at speed and scale for real-time decision making. The serverless architecture allows BharatPe to manage pipelines with a lean team. The company is also able to scale its data processing, especially for data-intensive workflows such as machine learning. The use of machine learning has also improved credit access for small merchants by speeding up loan approval decisions. BharatPe is now able to create a loan profile on each applicant that determines the loan amount, with some merchants getting their loans approved almost immediately. The company also uses machine learning for KYC and underwriting for its consumer-facing postpe app, helping customers get instant credit for buy-now-pay-later purchases, without the hassle of applying for a credit card.

Benefit #1	Processes up to 80TB of data each day on BigQuery with minimal infrastructure management
Benefit #2	Supports a multi-cloud strategy with Cloud Composer to orchestrate more than 1,000 data workflows between clouds
Benefit #3	Reduced time to insight and enabled automated decisioning using AI/ML for critical business processes like fraud detection and credit decisions

Benefit #1

Processes up to 80TB of data each day on BigQuery with minimal infrastructure management

Benefit #2

Supports a multi-cloud strategy with Cloud Composer to orchestrate more than 1,000 data workflows between clouds

Benefit #3

Reduced time to insight and enabled automated decisioning using AI/ML for critical business processes like fraud detection and credit decisions

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Overview

BharatPe: Leveraging Google Cloud for Enhanced Data Analytics and AI to Promote Digital Payments

Operational Impact

Quantitative Benefit