Akashic for financial services · Banks, NBFCs & insurers
Catch risk before it clears.
Fraud moves across products. Your monitoring watches one silo at a time. Akashic sees every transaction against the whole graph: one resolved customer, real-time pattern recognition, and lineage on every alert your auditor will ever ask about.
Transaction signal
Amount · counterparty · channel
Identity graph
Name · KYC · device · linked accounts
Enterprise record
Exposure · risk score · prior alerts
Structuring pattern · same entity
Flagged as it forms · evidence attached
Streams
1,240/s
Entities
1 of 3
Chain
3 hops
Systems watched together
Four systems watched. None saw the chain.
What each system saw
Three hops.
Card, UPI, savings · six minutes apart
Each transfer sat just under the reporting limit. Each system logged its own hop and saw nothing wrong.
When the alert finally fired
Weeks later
Quarterly review · buried in false positives
The chain surfaces in a review long after the money moves. The pattern that spanned three products was invisible to all of them, and the evidence is reconstructed by hand from logs that disagree.
The gap between the hops is where the money leaves, and where the audit questions begin.
Hop
Card
Hop
UPI
Hop
Savings
What the graph is already saying
RESOLVE
One entity, three accounts
Near-identical names across cards, UPI, and savings resolve to a single beneficiary.
PATTERN
Structuring recognised
Transfers parked just under the reporting limit match a known laundering shape.
EVIDENCE
Alert carries its lineage
The chain, the entities, and every source record arrive with the escalation.
1
Monitoring runs one silo at a time
Core banking, cards, payments, and lending each run their own surveillance. A pattern that spans them is invisible to all of them.
2
One customer, four KYC records
The same person exists under slightly different names across products. Exposure, risk, and suspicious behaviour fragment with the identity.
3
Evidence assembled after the fact
When the regulator asks why an alert fired, or didn't, the answer is reconstructed by hand from logs across systems. Audit is an archaeology project.
None of these are people problems. All of them are architecture problems.
Trust is your product. Architecture is how you keep it.
Scroll through your own bank: the players you already have, and what changes when their data lands on one governed record.
- 01
The players
Every channel watches alone.
Core banking, cards, payments, KYC, lending: each runs its own surveillance. A chain that spans them is invisible to all of them.
- 02
Transactions stream
Every hop lands on one graph.
Card swipes, UPI transfers and account movements stream in as they clear, not in tomorrow's batch file.
- 03
Identities resolve
Four names. One entity.
Near-identical KYC records resolve into one customer, and the chain of small transfers suddenly has a single owner.
- 04
The desk sees it
Flagged as it forms. Evidence attached.
The pattern reaches the risk desk in minutes, with entities, hops and source records already assembled.
The whole graph, watching every transaction.
Akashic sits beneath your core systems: streaming every transaction into one governed foundation, resolving every identity across products, and giving risk teams answers that arrive with their evidence attached.
01 / Unify
Every channel, one stream
Data Pipelines ingest core banking, cards, payments, and lending events in real time. Master Data resolves near-identical identities into one customer across every product.
02 / Govern
Compliance by architecture
Access rules, masking, and retention execute at the platform layer. Every query and every model decision is stamped, so the audit trail exists before anyone asks for it.
03 / Predict
Patterns flagged as they form
Models trained on your own transaction graph recognise structuring, mule networks, and credit deterioration across products, not one silo at a time.
04 / Act
Alerts that carry their evidence
Risk teams ask in plain language and get the chain, the entities, and the source records in one answer. Every escalation is audit-ready the moment it's raised.
Every module runs on the same governed foundation · every answer arrives with its lineage
What changes on the risk desk.
Same regulators. Same products. A different speed of sight.
BeforeEach channel monitored in its own silo
AfterEvery transaction seen against the whole graph
BeforeOne customer scattered across four KYC records
AfterOne resolved entity across every product
BeforeAlerts triaged weeks after the pattern
AfterRisk flagged as the pattern forms
BeforeAudit evidence assembled by hand
AfterLineage attached to every decision by default
Let's talk about your risk architecture.
Whether it's a fraud pattern your silos keep missing or a compliance programme that runs on manual evidence, we'd like to show you what surveillance on one governed graph looks like.