Oscilar is an AI-powered, no-code risk decisioning platform designed specifically to assist fintech companies in managing various types of risks including fraud, credit and compliance.

The platform's main objective is to save engineering hours through no-code automation, allowing financial technology companies to focus on their core operations.Oscilar is noteworthy for its learning capabilities, with the ability to adapt to a company's unique data and user behaviors, to automate risk decision making processes.

This automation not only reduces the manual effort required in risk assessment but also increases the efficiency of the risk analysis process.The platform also provides tools for creating rules and workflows, requiring no coding knowledge.

These rules and workflows can be easily changed, tested and gradually deployed. Additionally, Oscilar features a robust machine learning component, requiring minimal labeled data, and offering the flexibility to use hosted models or bring your own.It also offers a data hub that integrates 1st party database data and 3rd party data sources in a snap, providing a comprehensive real-time view of customers and transactions.

This allows for a thorough and up-to-date understanding of risk levels.Furthermore, Oscilar provides a case management system designed to reduce manual reviews, delivering important transaction data automatically which enables finding and flagging users exhibiting similar behavior.

Overall, Oscilar simplifies risk decision making, automates the risk assessment process, and enhances decision-making efficiency in fintech operations.

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Oscilar was manually vetted by our editorial team and was first featured on May 28th 2024.

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Pros and Cons

Pros

Designed for fintech companies

Manages fraud, credit, compliance risks

No-code automation

Saves engineering hours

Learning capabilities

Adapts to unique data

Automates risk decisioning

Efficient risk analysis process

Easy rule and workflow creation

Changes, tests, deploys workflows

Minimal labeled data for ML

Flexibility with hosted or own models

1st and 3rd party data integration

Real-time customer and transaction view

Automates case management

Reduces manual reviews

Finds and flags similar behavior

No Coding Required for Integration

Advanced ML models tailoring

Velocity counters creation

Matrix models creation

Changes risk policies in minutes

Fast decision-making (< 100ms)

Intuitive no-code UI

Decision-making flow creation

Transaction monitoring

KYC fraud prevention

Automates most decisions

Customizable decisioning workflows

Reduces manual reviews

Out-of-the-box ML models

Merchant onboarding

Account takeover prevention

Instant credit decisioning

Real-time 360 view of customers

Connects internal and external data

Rules, ML models, velocity counters via UI

Speeds up manual reviews

Iterate policies easily

Unified risk, fraud and credit platform

Cons

Fintech-specific

Assumes data availability

Limited labeled data usage

Tools for rule creation

Requires gradual deployment

Single focus on risk management

Potential over-reliance on automation

Complexity in integrating third-party data

Learning capabilities dependent on user data

Potentially unsuitable for small businesses

Q&A

What is Oscilar?

Oscilar is a no-code, AI-powered risk decisioning platform. It's designed to assist financial technology (fintech) companies in managing various types of risks, including fraud, credit, and compliance risks. The platform's main objective is to save engineering hours through automation and facilitate risk decision making, allowing fintech companies to focus on their core operations.

Who can use Oscilar?

Oscilar can be used by fintech companies in different sectors like Financial Services, Buy Now Pay Later (BNPL), Marketplaces and Banking as a Service (BaaS). In particular, roles like risk analysts and risk team members can leverage Oscilar to automate their risk decision-making processes.

How does Oscilar assist with fraud, credit, and compliance risks?

Oscilar helps to manage fraud, credit, and compliance risks by automating the risk decision-making process. It leverages machine learning models that are continuously retrained, tailored to your data and behavior of your users, and can interpret data to detect anomalies and potentially fraudulent activities. It also provides tools to enhance credit decisioning and compliance management processes.

How does Oscilar automate the risk decision making process?

Oscilar uses unique data and user behaviors to automate the risk decision-making process. It applies machine learning models that are accustomed to the specific data and behavioral patterns of the company's customers. This reduces the manual effort required in risk assessment and increases the overall efficiency of the process.

Can Oscilar adapt to unique data and user behaviors?

Yes, Oscilar can adapt to unique data and user behaviors. One of Oscilar's key features is its learning capability that uses your users' behavior and your unique data to help automate most of your risk decisions. This enables the platform to tailor its operations to the specific needs and patterns of a company's risk assessment.

How does the rule/workflow creation in Oscilar work?

Rule and workflow creation in Oscilar works through an intuitive no-code interface. This allows users to easily create and change rules and workflows. In addition, users can simulate changes using unit tests, backtests, shadow tests and A/B tests for modern risk management.

Does Oscilar require you to have a strong background in coding?

No, Oscilar does not require a strong background in coding. It is a no-code platform, designed to be user-friendly. This allows anyone in the risk team to create decisioning flows without requiring any help from an engineer or need for coding knowledge.

Can I use my own machine learning models on Oscilar?

Yes, Oscilar allows you to use your own machine learning models. While the platform itself features a robust machine learning component and offers hosted models, it also provides the flexibility to integrate and use your own machine learning models.

What is the purpose of Oscilar's data hub?

Oscilar's data hub serves as an integrated data platform that offers a comprehensive, real-time view of customers and transactions. It assimilates data from 1st party databases and 3rd party sources, allowing for velocity counters, lists, matrix models creation and more with a few clicks.

How does Oscilar offer a real-time view of customers and transactions?

Oscilar offers a real-time view of customers and transactions through its data hub which integrates data from various sources in real-time. This ensures that risk levels can be assessed with the most up-to-date understanding of customer behaviors and transactions.

What does Oscilar's case management system provide?

Oscilar's case management system is designed to reduce manual reviews, by delivering important transaction data automatically. This enables the finding and flagging of users exhibiting similar behavior which potentially represents risk, thus aiding in risk analysis and decision making.

Can Oscilar be used for fraud detection, credit risk, and compliance?

Yes, Oscilar can be used for fraud detection, credit risk and compliance. Its machine learning models and risk decisioning capabilities allow it to detect fraudulent activities, assess credit risks and manage compliance risks in real-time.

How can Oscilar rid me of the need for manual reviews?

Oscilar tackles the burden of manual reviews by implementing automated risk decision-making processes. Through case management system, it delivers important transaction data automatically, identifies and flags users showing similar behavior, and thereby reduces the need for extensive manual reviews.

What makes Oscilar efficient for risk assessment?

Oscilar is efficient for risk assessment for several reasons. It employs AI and machine learning to automate the risk decision-making process, leading to a significant reduction in manual effort. Additionally, it can adapt to unique data and user behaviors, integrate diverse data sources, provide real-time analysis, and facilitate efficient workflow creation and adaptation.

How does Oscilar help fintech companies save engineering hours?

Oscilar aids fintech companies in saving engineering hours through its no-code automation feature. This also enables risk analysts to change risk policies without relying on engineers. As a result, engineering resources can be freed up to concentrate on core business functions.

Can Oscilar integrate data from 1st party databases and 3rd party sources?

Yes, Oscilar can integrate data from 1st party databases and 3rd party sources. Users can bring together multiple data sources within Oscilar's data hub in just a few clicks, providing a 360-degree real-time view of customers and transactions.

Will Oscilar allow for gradual deployment of changed rules/workflows?

Yes, Oscilar permits gradual deployment of changed rules and workflows. Once these modifications are made, they can be tested using unit tests, backtests, shadow tests and A/B tests, before being gradually deployed from local to the staging environment and finally to the production environment.

Does Oscilar offer tools to reduce the risk of account takeovers?

Yes, Oscilar provides tools that aim to prevent account takeover incidents. Its suite of tools, encompassing decision-making workflows, machine learning models, and case-management systems, facilitates the detection and prevention of fraudulent activities, including account takeover attempts.

Can Oscilar help me in creating risk models and signals?

Yes, with Oscilar, you can create new risk models and signals without the need for coding. The platform allows you to define decisioning workflows using rules, ML models, velocity counters and more via an intuitive user interface. This helps in quickly identifying and reacting to any new risk signals.

Will Oscilar aid me in KYC fraud prevention?

Yes, Oscilar can assist in Know Your Customer (KYC) fraud prevention. Its comprehensive toolset provides capabilities like transaction monitoring, merchant onboarding, fraud detection, and prevention that play a critical role in ensuring KYC compliance and mitigating associated fraud risks.