Underwriting, claims, and fraud intelligence built for modern insurers
Lognatech helps insurance carriers, MGAs, brokers, and reinsurers turn decades of policy, claims, and customer data into a competitive advantage. We build the analytics, AI, and data platforms that improve underwriting accuracy, accelerate claims handling, reduce fraud losses, and give your teams a real-time view of the book.
What we deliver for insurers
Four core capabilities, each designed around the realities of underwriting, claims, and distribution. Every solution is built on the tools your actuaries, data engineers, and claims teams already trust.
Underwriting intelligence
Risk scoring, price optimisation, and portfolio steering models that improve loss ratios and give underwriters sharper decisions at the point of quote.
Claims analytics
Automated triage, severity prediction, and settlement guidance that cut handling time and reduce leakage across motor, property, health, and specialty lines.
Fraud detection
Real-time scoring at FNOL and during adjudication, with network analysis and anomaly detection that surfaces organised fraud rings before they pay out.
Book-level insight
Executive dashboards and self-service analytics that show premium, claims, exposure, and profitability by segment, channel, and geography in real time.
Where we make the biggest difference
These are the highest-value use cases our insurance clients ask us to solve first. Each one is measured against a clear business case: loss ratio, combined ratio, handling time, or fraud savings.
Underwriting and risk selection
We combine your historical policy, claims, and third-party data into a single governed feature store, then train models that predict loss propensity, expected severity, and profitability at the policy level. Underwriters see a clear risk score and recommended price, not a black box.
The result is sharper risk selection at the point of quote, better price adequacy across segments, and the ability to walk away from unprofitable business before it is bound. Clients typically see a measurable improvement in loss ratio within the first two quarters.
Discuss underwritingClaims triage, severity, and settlement
At first notification of loss, our models score every claim for severity, complexity, and fraud risk. High-risk claims are routed to senior handlers. Straightforward claims are fast-tracked. Settlement recommendations are grounded in your own historical outcomes, not generic industry averages.
We integrate directly with your claims system so handlers see the score and recommended next action without leaving their workflow. Handling time drops, leakage shrinks, and customer satisfaction improves because the right claims get the right attention.
Discuss claims analyticsFraud detection and network analysis
We build real-time scoring pipelines that evaluate every claim, every claimant, and every provider at the point of submission. Behind the scoring sits a graph of relationships between people, vehicles, addresses, phone numbers, and providers, so organised rings and repeat offenders surface automatically.
Alerts are pushed into your SIU workflow with the evidence attached. Investigators spend their time on the cases that matter, and fraudulent payouts are stopped before the money leaves the business.
Discuss fraud detectionExecutive dashboards and portfolio steering
We deliver a complete view of the book: premium written, claims incurred, loss ratio, combined ratio, retention, and exposure, sliced by segment, channel, broker, geography, and product. Dashboards update in near real time and are built for the C-suite as well as regional managers.
With a reliable single source of truth, pricing, underwriting, and distribution decisions get faster and more consistent. Portfolio steering stops being a quarterly exercise and becomes a continuous discipline.
Discuss book insightDomain depth, engineering rigour, regulatory awareness
Insurance analytics is not a generic data science problem. It needs people who understand actuarial concepts, claims operations, regulatory constraints, and the systems insurers actually run on. Our teams bring all four.
We speak your language
Loss ratio, combined ratio, IBNR, exposure, cession, bordereaux, IFRS 17. We work with these concepts every day and build models and pipelines that respect them.
We work with your systems
Policy admin, claims management, reinsurance, and legacy mainframe systems. We integrate rather than replace, so you get value from your existing investments.
Compliance is a first-class concern
GDPR, POPIA, DIFC, SOC2, and local insurance regulation. Every model is built with explainability, auditability, and data residency in mind.
Talk to our insurance team40%
faster claims handling across delivered projects
31%
reduction in operational bottlenecks
93%
predictive accuracy on production models
24/7
monitoring and support on live systems
How we engage with insurers
We work in short, focused phases so you see value quickly and can scale investment based on proven results, not promises.
1. Discovery
Two to four weeks to understand your data, systems, and priority use cases, and to agree the business case.
2. Prototype
Four to six weeks to build a working model or pipeline on your real data so you can see the outcome before committing further.
3. Production
One quarter to take the prototype into production, integrated with your policy or claims systems, with monitoring and governance in place.
4. Scale
Ongoing optimisation and expansion into adjacent use cases, with a dedicated team that knows your book and your systems.