Finance, banking and insurance: Leave repetitive checks to robots and decisions to your team.
We build RPA reconciliation, document-reading AI, secure mobile banking apps and 24/7 monitoring for banks, financial institutions and insurers. Our approach is to automate repetitive control work while keeping every step auditable and compliant with regulation.
Typical needs
Heavy manual checks, security and regulatory compliance
Illustrative interface
Industry challenges
Problems we often see in this industry
Manual reconciliation
Matching statements, ledgers and counterparty records line by line in spreadsheets consumes expert time.
Document workload
Re-typing data from claim files, application forms and receipts into systems is slow and error-prone.
Strict security and regulatory expectations
Banking regulation, data protection law and internal audit require every operation to be traceable and authorised.
Integration with legacy core systems
New digital channels must talk securely to core systems that have limited or no APIs.
Low tolerance for downtime
A failure in payments, transfers or policy operations turns directly into lost customers and reputational risk.
Our solutions
What we build
Mobile and digital channel apps
Secure mobile banking and customer apps designed with device binding, biometric authentication, certificate pinning and root/jailbreak detection.
RPA reconciliation and claims processing
Software robots that match bank transactions with ledger entries, route exceptions to people and log every operation.
Document-reading AI
Models that read and validate fields from policies, claim files, receipts and invoices, and ask for human approval when unsure.
24/7 monitoring
Continuous monitoring of critical services, integrations and robots, with instant alerts to the right team when something is off.
Related services
The services behind these solutions
Robotic Process Automation (RPA)
Hand rule-based work such as data entry, reporting and system-to-system transfers to robots that run 24/7.
Machine Learning and Computer Vision
Forecasting, computer vision, document processing and natural language processing models.
Mobile Apps
User-centered, high-performance and secure mobile apps for iOS and Android.
Cyber Security
Secure software development, penetration testing, vulnerability scanning and technical compliance support.
24/7 Monitoring and Managed Services
We monitor your servers, applications and services around the clock and catch issues before users notice.
Representative scenario
Claims file and reconciliation automation at an insurer
Representative scenario, not a real client project.
- Profile
- An insurance company receiving a high volume of claim files through agencies and contracted services, reconciling collections with several banks.
- Problem
- Fields such as policy number, amount and date were keyed in by hand from claim documents, and bank collections were matched in spreadsheets at month end. Closing took longer and errors were found late.
- Approach
- The process was mapped first, separating rule-based steps from those that need expert judgement.
- A document-reading model was set up to extract fields from claim documents and send low-confidence records to expert approval.
- RPA robots matched bank transactions with ledger entries daily and left only exceptions to the team.
- Robot and integration status was connected to a 24/7 monitoring dashboard, and every operation was written to an audit log.
- Solutions used
- Document-reading AI
- RPA reconciliation
- 24/7 monitoring
- Audit log
- Outcome
- Reconciliation moved from a month-end pile-up to a daily routine, experts focused on exceptions only and every automated operation could be shown to auditors.
FAQ
Frequently asked questions
Which finance processes are a good fit for RPA?
Rule-based, repetitive processes that work with digital data are the best candidates: bank reconciliation, collection matching, report preparation, data transfer between systems and first checks on claim files. We score your processes against these criteria and start with those that pay back fastest.
How is automation tracked for audit and compliance?
Every robot operation records on whose behalf it ran, with which data and with what result. Permissions are role-based and personal data is masked. These records can be reported for internal audit and regulatory requests.
What happens if the document-reading AI misreads a field?
The model produces a confidence score for each field. Records below the agreed threshold are not processed automatically and go to an expert for approval. Approved corrections can be used to improve the model.
How do you handle security in a mobile banking app?
We threat-model from the design stage: device binding, biometric authentication, certificate pinning, root/jailbreak detection, secure session management and on-device encryption of sensitive data come first. We recommend validating the app with an independent security test before release.
Can you work without touching the core banking system?
In most cases, yes. Automation can be built through existing services, middleware APIs or screen-level access with RPA, without changing the core system. We choose the route together based on your access and security policies.
Let's plan the right solution for your industry
Tell us briefly what you need and we will get back to you within one business day. The first 30-minute introductory call is free.