A borrower approves a consent request in under a minute. Their verified bank data reaches the lender seconds later. And then the application sits for two days waiting for a decision.
That gap is the real story of Account Aggregator today. The framework has done what it set out to do. India's AA network has now handled more than 45 crore consents and over 500 crore data fetches, and it processes more than 7 lakh consents on an average day. Getting verified financial data, with the customer's permission, in seconds, is no longer the hard part of lending. What happens after the data arrives usually is.
Account Aggregator delivers data, not decisions
It helps to be clear about what actually lands on the lender's side. The AA itself is a consent manager. It moves data securely and cannot read or keep it. What the lender receives is months of raw bank transactions: dates, amounts, and short, cryptic descriptions.
That is a genuine improvement on a scanned PDF statement, because the data is verified and machine-readable from the start. But it is raw material, not an answer. Nothing in it states what the borrower earns, how dependable that income is, what they already repay each month, or whether they can afford the loan in front of you. Every one of those conclusions still has to be worked out.
At many lenders, they are worked out slowly. The file joins a queue, or moves through a process designed for the era of paper statements. The speed the AA rails deliver is then lost in the days that follow.
The work is turning transactions into signals
Deciding in minutes rather than days means reading those transactions automatically and at volume. In practice, that involves:
- Sorting every transaction into what it represents, whether salary, rent, an EMI, or business receipts.
- Working out real income and how steady it is from month to month.
- Identifying existing loan repayments and other regular commitments.
- Reading cash flow patterns, which matter most for small businesses and borrowers without long credit histories.
- Reducing all of it to the handful of figures a credit model can actually score.
This is where lending on AA data is won or lost. Done well, it lets a lender assess a borrower a bureau score alone would miss, on evidence of how money genuinely moves through their accounts.
Building the pipeline on AWS
None of this is manual work, and none of it should be slow. It calls for a data pipeline that receives consented data, cleans and categorizes it, derives the signals, and passes them to a credit model within the span of a customer's attention.
On AWS, that pipeline has a natural shape. Amazon S3 holds the consented data. AWS Glue processes and catalogs it. AWS Lake Formation controls who and what can reach it, which matters because this is personal financial data and sits squarely within the DPDP obligations covered in our earlier article. Amazon SageMaker scores the result. The pipeline scales when application volumes spike and stays quiet when they do not.
The advantage is not simply speed. Every consented dataset a lender processes makes its models sharper, provided the pipeline is built to learn rather than merely to move data.
Faster decisions reach more borrowers
The commercial case is straightforward. Applicants abandon slow loan journeys, and a decision that lands in minutes converts far better than one that lands on Thursday. Beyond conversion, cash flow evidence lets a lender say yes to sound borrowers who have thin credit files, including small businesses and first-time borrowers, which is precisely the growth the AA framework was designed to unlock.
Where NileForge fits
Lenders rarely struggle to connect to the AA rails. They struggle to turn what comes through them into decisions quickly and consistently. That is the work we do on AWS: the pipelines that process consented data, the engineering that derives the signals underwriting depends on, and the governance that keeps it all defensible.
The data already arrives in seconds. If you lead lending, credit, or technology at a bank, NBFC, or fintech and want your decisions to move at the same speed, talk to our team about building it on AWS.