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Westpac NZ, an Infosys Finacle customer evaluated nCino Bank OS

Cantor Fitzgerald, a Kyriba Treasury customer evaluated GTreasury

Citigroup, a VestmarkONE customer evaluated BlackRock Aladdin Wealth

Moog, an UKG AutoTime customer evaluated Workday Time and Attendance

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Wayfair, a Korber HighJump WMS customer just evaluated Manhattan WMS

Swedbank, a Temenos T24 customer evaluated Oracle Flexcube

List of FinBox Account Aggregation Customers

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Logo Customer Industry Empl. Revenue Country Vendor Application Category When SI Insight
IIFL Finance Banking and Financial Services 20914 $40.2B India FinBox FinBox Account Aggregation Data Warehouse 2021 n/a
In 2021, IIFL Finance deployed FinBox Account Aggregation in the Data Warehouse category to enhance MSME lending underwriting. The implementation integrated FinBox’s Account Aggregator-enabled underwriting via BankConnect AA to ingest customer GST records and bank cash-flow statements to support GST and cash-flow based MSME lending decisions. The deployment positioned FinBox Account Aggregation as a core data ingestion and normalized financial data layer within IIFL Finance's lending architecture. Functional modules implemented included account aggregation, GST and bank cash-flow data ingestion, automated underwriting decisioning and credit adjudication workflows aligned to MSME risk profiles. FinBox Account Aggregation connected consented AA data feeds into IIFL Finance's underwriting pipelines, enabling near real-time verification of business revenue and liquidity signals for loan origination and credit assessment. The configuration emphasized data normalization, consent management and integration into existing credit decision workflows. The initiative affected underwriting, credit origination and risk assessment functions across IIFL Finance's MSME lending operations in India. The partnership produced explicit outcomes, including a 17% increase in approval rates and higher average ticket sizes, and it was recognised with a Sahamati award for AA-based MSME lending. The implementation therefore links the company, FinBox Account Aggregation and the Data Warehouse application to operational credit decisioning for MSME products.
InCred Financial Services Banking and Financial Services 1638 $110M India FinBox FinBox Account Aggregation Data Warehouse 2022 n/a
In 2022, InCred Financial Services deployed FinBox BankConnect and implemented FinBox Account Aggregation within its Data Warehouse to detect fraudulent bank statements and accelerate funnel clean-ups for its digital lending operations in India. The deployment targeted bank statement analysis and automated funnel-cleanup workflows, embedding bank statement parsing and fraud scoring into lending acceptance and verification processes. FinBox Account Aggregation is cited as part of the solution set supporting these capabilities. FinBox documentation indicates BankConnect is Account Aggregator enabled, so Account Aggregator usage is inferred for account-level data flows into the Data Warehouse. The implementation encompassed bank statement parsing, automated fraud scoring, and funnel cleanup orchestration, functional modules that align with Data Warehouse use for underwriting and operations in a digital lending context. FinBox cites outcomes for the deployment including approximately 98 percent fraud-detection accuracy, a 60 percent reduction in false positives, and three times faster funnel clean-ups.
Rentomojo India Retail 759 $30M India FinBox FinBox Account Aggregation Data Warehouse 2021 n/a
In 2021, Rentomojo India deployed FinBox Account Aggregation to automate customer onboarding and bank statement based risk assessment for its rental order processing in India. The deployment used FinBox BankConnect capabilities to ingest and normalize bank statements and to feed structured financial signals into underwriting workflows, mapping to Data Warehouse oriented ingestion and analytics patterns. Configuration focused on automated onboarding, bank statement ingestion and parsing, and real time risk scoring that fed Rentomojo’s order orchestration pipeline. Functional modules implemented included account statement ingestion, consent-driven account aggregation flows, automated risk assessment rules, and order processing triggers to reduce customer drop off and accelerate approvals. FinBox reported improvements including a 70% increase in NPS, Play Store rating uplift and 83% of orders processed within five minutes, outcomes tied to reduced onboarding friction and faster rental order processing. Account Aggregator usage is inferred because BankConnect is Account Aggregator enabled, indicating the implementation leveraged consented account aggregation flows for faster, reliable statement access and underwriting signal extraction.
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FAQ - APPS RUN THE WORLD FinBox Account Aggregation Coverage

FinBox Account Aggregation is a Data Warehouse solution from FinBox.

Companies worldwide use FinBox Account Aggregation, from small firms to large enterprises across 21+ industries.

Organizations such as IIFL Finance, InCred Financial Services and Rentomojo India are recorded users of FinBox Account Aggregation for Data Warehouse.

Companies using FinBox Account Aggregation are most concentrated in Banking and Financial Services and Retail, with adoption spanning over 21 industries.

Companies using FinBox Account Aggregation are most concentrated in India, with adoption tracked across 195 countries worldwide. This global distribution highlights the popularity of FinBox Account Aggregation across Americas, EMEA, and APAC.

Companies using FinBox Account Aggregation range from small businesses with 0-100 employees - 0%, to mid-sized firms with 101-1,000 employees - 33.33%, large organizations with 1,001-10,000 employees - 33.33%, and global enterprises with 10,000+ employees - 33.33%.

Customers of FinBox Account Aggregation include firms across all revenue levels — from $0-100M, to $101M-$1B, $1B-$10B, and $10B+ global corporations.

Contact APPS RUN THE WORLD to access the full verified FinBox Account Aggregation customer database with detailed Firmographics such as industry, geography, revenue, and employee breakdowns as well as key decision makers in charge of Data Warehouse.