Market coverage
- Austria
- Germany
- Switzerland
Valuable insights into the needs and characteristics of users helps support consulting, sales and marketing
A superior database and continuous development boosts in-house analytics and multiple use cases
Shared learning effect: central data processing of sensitive data in the cloud enables outstanding data quality, which is constantly improving
- Overview
- Applications
- Endpoints
With the power of KI and Machine Learning, Contovista turns payment information into valuable assets and insights for consulting, sales, marketing and in-house analytics teams.
Rules-based, in-house solutions, are often slow and out-dated resulting in inaccurate transactional data. Moreover, they are not up to date on payment counterparties due to the longtail.
The Contovista Enrichment Engine structures, cleans up and refines unstructured customer data, opening up new possibilities including:
- Optimised User Experience: Create a digital banking experience tailored to the unique needs of each client.
- Data-based sales decisions: Optimise the entire cross-selling process with machine learning methods that offer customers the products and services that best fit their requirements.
- Customer advice: Inspire customers with tailor-made solutions. Create more relevance, increase digital touchpoints and long-term customer loyalty.
- Risk Management: Use artificial intelligence to identify risk factors earlier and automate KYC and KYT processes to save costs and time.
Accelerate innovation using Contovista’s powerful and flexible API to integrate analytics solutions into existing ecosystems quickly and easily.
A unique hybrid architecture (on-premise analysis of sensitive data combined with the analysis of sensitive data in the cloud) and state-of-the-art machine-learning algorithms guarantee outstanding analytics results.
The enrichment engine is based on transaction data from different sources:
- PSD 2 aggregators
- Core banking systems
- Data warehouse providers
- Credit card issuers
Transaction data is cleaned up and enriched with a variety of meta-data:
- Input and output categories (> 200 categories)
- Geo-location for POS transactions
- Used payment schemes
- Extensive system of various merchant-related attributes
In addition, proven algorithms identify customer-related events and characteristics, for example.
- Budgetary account as a basis for credit decisions
- Recurring payments
- Fixed vs. variable costs
- Third-party bank relationships
- KYC-related information (e.g. employer change)
- Irregularities in payment behaviour (e.g. unusually high payments)
- Customer-related characteristics (e.g. frequent travellers, tenants vs. homeowners etc.)
About the provider
Contovista enables data-driven banking.
Launched in 2013 as a fintech pioneer, Contovista is now Switzerland’s market leader for data-based banking.
Contovista’s white-label software, data and analytics solutions integrate smoothly into existing banking systems, allowing banks and financial institutions to optimize the customer experience across their digital channels.
With data enhancement and machine learning, Contovista helps banks and financial service providers to better understand customers, to better advise them and to make banking more personal. As a result, inspiring increased customer loyalty and share-of-wallet.
The company, reaches more than 5 million customers through its partner banks. Contovista is headquartered in Zurich, Switzerland.