Connect Faster and Meet Qwist’s AI Assistant

Access Open Finance data within 48h
and try out Qlarc, our first version of AI assistant,
here to help you manage data through a conversation

Open Finance doesn’t need to be hard

Faster Integrations

Open Banking integrations require significant engineering time and ongoing maintenance, slowing down adoption. Qwist Link decreases time-to-live to 48h.

Early Commitment

Often teams must commit to long-term contracts before properly testing whether a solution fits their needs in real conditions. Through Qwist Link businesses can test out Qwist products before choosing the long-term commitment and API integration.

Early Commitment

Often teams must commit to long-term contracts before properly testing whether a solution fits their needs in real conditions. Through Qwist Link businesses can test out Qwist products before choosing the long-term commitment and API integration.

Complex Data Analysis

Financial data always comes with complexity, reinforced by legacy systems, siloes, and security barriers. Qlarc was created to allow the same simplicity from financial systems as currently available from consumer AI tools.

Qwist Link

From Integration Friction to Instant
Financial Intelligence

Qwist Link removes engineering overhead for medium size data volume and lets you validate our solutions with real data before the commitment. Going beyond API connectivity Qwist now gives clients secure access to structured financial data without any additional infrastructure.

How it works

1. Access your unique Client ID

By signing into the Qwist Console, you gain access to your unique Customer ID, the first step to creating personalized Qwist Links for your end users.

Using the Qwist Link feature in the navigation menu, you can quickly generate secure, customer-specific links designed to speed up the integration. These links not only connect your customers’ financial data directly to the Qwist Console but also provide a seamless and compliant way for customers to grant their consent through a secure authentication flow.

2. Select a Bank & Authenticate Securely

With a single click on the generated link, your end users can securely connect their bank accounts in just a few steps. They can simply select their bank and the account or multiple accounts they want to connect and complete the authentication process using their bank’s secure login flow.

Through this seamless experience, your end users can safely grant consent for access to their financial data via the Qwist Console.

3. Generate Insights and Reports

After securely granted access, Qwist retrieves balances, transactions, and account details in real time and based on your configuration (enabled AIS products), valuable outputs such as income verification, risk assessments, transaction overviews, and other financial insights are automatically generated.

Authorized console users can conveniently access and download reports in JSON format through the Qwist Console.

Try it out

Meet Qlarc

Your Open Finance AI Assistant

Qlarc is the first version of Qwist’s AI assistant. Built with MCP and LLP Qlarc is to bring the ease of pulling out and analyzing platform data while operating plain language.

Wondering what does your user base look like right now?

Example queries:

“Give me an overview of my user portfolio.”
“How many active users do I have and what’s their average income?”
“What are the most common spending categories across my user base?”

What you can expect from Qlarc:

A concise summary covering user count, average income, income type breakdown (salary vs. freelance), top spending categories, and any notable risk signals present across the portfolio. Specific numbers, not vague generalizations.

Curious to know which your customers match a specific financial profile?

Example queries:

“Which of my users have a regular salary above €2,500/month and no overdraft activity?”
“How many users could qualify for a €5,000 personal loan based on their disposable income?”
“Show me users who have gambling transactions in the last 3 months.“
“Which users have a car loan and what’s their average remaining disposable income?”

What you can expect from Qlarc:

A count of matching users, the criteria applied, and a representative sample. The agent should explicitly state what filters it used so the customer can verify the logic.

Pulling data about a specific client?

Example queries:

“Give me a financial summary of user abc123.”
“Is user xyz789 a good candidate for a credit limit increase? What does their income and spending look like?”
“What are the risk flags for user def456?”

What you can expect from Qlarc:

A structured summary covering income (amount, regularity, trends), spending breakdown by category, detected obligations (rent, loans, subscriptions), risk indicators present or absent, and a plain-language assessment. Everything in one response, sourced from the Financial Data.