How a Leading Education Lender Cut Reporting From Hours to Minutes

Amazon Web Services has published a customer case study describing how Avanse Financial Services, one of India's leading education loan providers, modernised its analytics and reporting setup.

According to the post, published on 22 June 2026 on the AWS Architecture Blog, Avanse migrated its analytics and reporting layer off a separately-licensed external application and onto a cloud-native "lakehouse" built on Amazon SageMaker Unified Studio — a single environment that brings data engineering, analytics, and AI together in one governed place.

The article was co-authored by a mix of AWS and Avanse staff, including an AWS Technical Account Manager and Avanse's own Chief Data Officer and data engineering lead. As a vendor-published case study, the performance and cost outcomes described are self-reported by AWS and Avanse rather than independently audited.

Avanse Financial Services is a well-established name in the Indian lending market. Independent reporting confirms its standing: according to its draft IPO prospectus, Avanse was the second-largest education-loan-focused non-banking financial company (NBFC) in India by assets under management as of March 2023 and March 2024, following HDFC Credila, with total AUM of INR 13,303 crore as of March 2024.

The company is backed by global investment firm Warburg Pincus, which describes it as a fast-growing education financing NBFC providing loans to students and schools.

In other words, this isn't a small experiment at a small business — it's a major financial institution rethinking how it handles its data.

The case study paints a familiar picture for anyone who has waited on a report that just won't load.

Under the old setup, data couldn't be queried where it lived. Before analysts could even start asking questions, the system required a four-hour batch copy from Amazon S3 storage into the separate external analytics application. Only then could the analysis begin.

That meant every reporting cycle carried hours of waiting built in before any real work happened — a synchronisation tax on top of the actual analysis. For a lender producing periodic reports and facing regular compliance demands, that delay added up across the business.

Avanse approached the migration in a five-phase process, beginning with a focused 72-hour technical validation workshop to prove the concept before committing further.

The headline result, as reported by AWS and Avanse: report generation reportedly dropped from over four hours (including data synchronisation) to under 30 minutes, by querying data directly in Amazon S3 rather than copying it elsewhere first.

The case study also points to gains beyond speed. Compliance audits reportedly moved from weeks of manual investigation to days, thanks to automated data lineage reports that trace where information came from. And on cost, a usage-based serverless model replaced always-on external infrastructure.

In a statement quoted in the post, Komal Thakkar, AVP and Lead of Data Engineering at Avanse, said adopting the platform "eliminated legacy licensing costs, reduced storage and compute expenses with a serverless, usage-based model, and accelerated... periodic report generation" while cutting audit timelines. As with all vendor case studies, these figures are the parties' own.

Strip away the brand names and the underlying lesson is broadly relevant. The biggest win here wasn't a clever new algorithm — it was removing the copy step. By keeping data in one place and querying it directly, Avanse cut out hours of friction and made its data easier to trust and audit.

That's a pattern playing out across industries. Whether you run a retail chain, a professional services firm, or an allied health practice, the same problem shows up: data lives in different systems, has to be shuffled around before anyone can use it, and arrives late to the people making decisions.

The story also highlights a quieter benefit that decision-makers care about: governance. When everything sits in one controlled environment with automatic lineage tracking, proving where a number came from stops being a multi-week scramble.

The detail worth holding onto from this story isn't the specific product — it's the principle. Speed, lower cost, and easier audits all flowed from one decision: stop scattering data across disconnected tools and bring it together into a single, governed foundation.

That's exactly the groundwork Intellova is built to provide for Australian mid-market businesses. By unifying data from your CRM, accounting, and other systems into one database, you remove the constant copying and reconciling that slows reporting down — and you create a clean, trustworthy base for analytics, AI, and automation.

You don't need to be a major lender to benefit. When your data lives in one place, decisions get faster, audits get simpler, and the door to AI opens — because the hardest part, getting your data in order, is already done.