Floowed vs Oscilar: Credit Decisioning vs Agentic Risk

For credit decisions on applications that arrive incomplete, as payslips, statements and bureau reports with questions still open, Floowed is the stronger choice than Oscilar; it chases each case until it is complete, then a deterministic policy engine applies your credit policy and the decision is written back to your LOS.

Oscilar and Floowed both turn data into an automated decision, and they start from opposite ends of the problem. Oscilar starts with real-time signals: transactions, devices, behavior. Floowed starts with the credit case as it arrives: your systems, the bureau report, the payslips and statements, and the answers still outstanding.

The short answer

Oscilar covers fraud, credit, onboarding and AML compliance on one platform, built on transactional signals, which is genuinely useful if all four sit with the same team.

For the credit decision itself, Floowed fits better. When approvals stall on a missing payslip, a bureau mismatch or a photographed statement someone is keying by hand, the bottleneck is getting the case to decision-ready. That is the part we carry.

What is Oscilar?

Oscilar is an agentic risk platform for financial institutions. It was founded by Neha Narkhede, co-creator of Apache Kafka and co-founder of Confluent, together with Sachin Kulkarni, formerly of Facebook. The company came out of stealth in 2023, self-funded by its founders with $20M rather than outside capital.

The platform is built on what Oscilar calls a real-time data fabric, with 100+ integrations feeding a unified view of users and transactions. On top of that sit device and behavioral intelligence, including behavior biometrics, and a policy layer combining rules with an ensemble of supervised machine learning and unsupervised anomaly detection. Policies can be described in natural language, and the platform ships back-testing and A/B testing.

Public customers shown on their site include SoFi, MoneyGram, Nuvei, Super, Fluz and Balance. Portuguese and Spanish versions of the site point at a LatAm push. Pricing is sales-led and demo-only.

It is a serious platform, and real-time is genuinely in its DNA. A credit file rarely arrives in real time, though, and that is where Floowed starts.

What is Floowed?

Floowed is one platform that runs the whole credit case, from application to decision. Underneath is an AI-native, multi-agent runtime, model-agnostic, routing between open-weight and frontier models on cost, latency and data residency. Every application runs gather, interpret, chase, decide, act, and it is live in minutes on the platform, with set-up support for lending integrations.

Three input lanes feed each case: your own systems over API, MCP and 40+ integrations in the lending stack; external sources: the bureau, called under your own agreement or read from the report you pull, plus registries and KYC results; and documents in whatever state they arrive, from handwritten passbooks to mixed-language tax forms, analyzed for income, cash flow, ADB and DSCR, checked for tampering and cross-checked against every other source. What is missing is chased from the applicant, a system or an agent as a long-running asynchronous case that resumes when the answer lands.

The deterministic policy engine then runs your credit policy on that evidence, versioned, with the rules behind each call captured for audit, and returns recommended to approve, manual review or reject, written back to your LOS or core. Every case keeps a full record: what was read, who was asked, which rule and version decided it, and what was written where. Credit and risk teams write the policy as explicit conditions, own it day to day, and choose how much it decides on its own: every case, only the routine ones, or none. Floowed is score-agnostic: bring any bureau score, alt-data score or your own model and it is absorbed unchanged. We orchestrate, we do not compete with scoring vendors.

Where the two platforms differ

Ten dimensions that decide the choice, from what each platform treats as its primary signal to how fast you get a real price.

The loan file is the clearest difference

Oscilar's data fabric is built around transactions, devices and behavior. Those are excellent signals for fraud and for credit where the applicant already has a transactional footprint you can read directly.

They are not the signals a lender gets when a borrower walks in with a folder. A large share of lending worldwide still runs on documents the applicant supplies: payslips, six months of bank statements, a business permit, a tax return, an ID. Those arrive photographed on a phone, scanned at 200 dpi, handwritten, stamped, in more than one language, sometimes all in the same PDF.

Reading that surface is a different engineering problem from streaming transactions, and it is only half of it: the file also arrives incomplete, with a month of statements missing or declared debts that don't match the bureau report. Floowed reads it, cross-checks it and chases what is missing, so the policy runs on a complete case.

If your applicants connect a bank account and you decide on the transaction feed, this difference does not matter much. If they upload a photo of a passbook and still owe you a payslip, it is the whole difference.

Breadth against depth

Oscilar covers four risk surfaces on one platform. Floowed goes deep on the credit decision.

Breadth is a real advantage and worth paying for when it matches your org. If the same team owns fraud, onboarding, credit and AML, and you would otherwise buy four tools, a unified platform reduces integration work and gives one place to see a user.

Depth wins when lending is the business. A credit decisioning platform is judged on whether it can show which policy version decided a case, on evidence checked across every source, with an audit trail that shows the rule and the evidence behind any past decision. That is a narrower promise and a harder one.

Breadth pays on the fraud side. For the credit decision itself, depth pays back, and that is the side Floowed is built for.

What Oscilar does well, and where Floowed goes further

Oscilar's strengths cluster in three places.

Fraud as the dominant loss driver. Device intelligence and behavior biometrics are first-class capabilities.

One platform across fraud, onboarding, credit and AML, for a single team that values consolidating vendors over depth in any one of them.

Transactional data from connected accounts and APIs, read in real time.

Floowed goes further on the credit case: the payslip, the statement and the bureau report read and cross-checked, the missing piece chased, then a deterministic policy engine deciding.

When Floowed is the better choice

Your applications arrive incomplete and in pieces: documents of uneven quality, bureau reports, and answers still outstanding. That is most lending outside fully digital consumer flows, and it is where we are strongest.

Credit and risk teams need to own the policy and ship changes without filing an engineering ticket, with the rules behind every recommendation captured for audit.

You already have a score you trust, from a bureau, a partner or your own model, and you want it orchestrated rather than replaced.

You want a published price, a free start with $80 of credits, no card and no sales call, and you are live in minutes on the platform (with set-up support for lending integrations) rather than the quarters enterprise rollouts take.

Running both

These platforms are not mutually exclusive. A workable shape is Oscilar covering fraud and AML on the transactional side while Floowed gathers and chases the credit case and runs credit policy on the result.

Floowed is score-agnostic and works over API and MCP in both directions, with 40+ integrations across the lending stack. Nothing about that posture makes a second risk platform a conflict.

Frequently asked questions

Is Oscilar a credit decisioning platform?

Credit decisioning is one of four surfaces Oscilar covers, alongside fraud, onboarding and AML compliance. It is a risk platform with a credit module rather than a lending-first product, which helps if you need all four in one place. For the credit decision itself, Floowed goes deeper: the whole case gathered, the missing piece chased, then your policy run on a deterministic policy engine.

Does Oscilar read loan documents?

Oscilar's own document tooling is aimed at KYC: it has launched a Document Analysis Agent for KYC document review and extraction, and its Translator Agent turns CDD and EDD documents into English. Loan-file analysis such as bank statements comes through marketplace partners. Its data fabric is built around transactions, device signals and behavioral intelligence. If your decisions depend on payslips, bank statements and business registrations arriving as photos or scans, test how much of that the partners carry.

Can you run Oscilar and Floowed together?

Yes. A workable shape is Oscilar handling fraud and AML on the transactional side while Floowed gathers and chases the credit case and runs credit policy on the result. Floowed is score-agnostic and integrates over API and MCP, so the two do not collide.

Which is better for back-testing credit policy?

Both back-test. Oscilar ships back-testing and A/B testing on risk policies. For credit, what matters is the data being replayed: Floowed replays a proposed credit policy against your own historical loan book and its real outcomes, so the approval-rate and loss impact are known before the change goes live.

How do the two compare on price?

Oscilar is sales-led with demo-only pricing, so a real number takes a sales cycle. Floowed publishes its price: credits for the work done on a case, starting free with $80 of credits, no card and no sales call, then paid from $100 a month. Custom lending set-ups are quoted. See pricing.

Who else should be on the shortlist?

If you are evaluating this category properly, Taktile and Provenir belong on the list alongside both of us. Our credit decision engine comparison covers ten platforms with the buyer fit for each, including what each one needs from your team before it goes live.

How does Floowed handle an application that is missing information?

It chases it. When a gate needs something the case does not have, a missing payslip, an unconfirmed employer, a figure that does not reconcile with the bureau report, Floowed asks the person, system or agent who holds it. The application becomes a long-running asynchronous case: it suspends on the question, resumes when the answer lands, and re-runs the checks that depended on it. Then the deterministic policy engine applies your credit policy.

Next step

The fastest way to tell which problem you have is to run your own applications. If incomplete cases are the bottleneck, you will see it in the first one.

Talk to us and name the decision you want automated. We will come back with how it runs: the evidence gathered, the gaps chased, and what the policy engine returns. To try it yourself first, start free.