Use cases

Enterprise &
legacy data
Quantemplate’s power is its flexibility.
Whatever the size and shape of your data challenges,
Quantemplate can help you unlock strategic value.


Solve your spreadsheet problem
Integrate disparate data sources and capture IP

Tens of thousands of spreadsheets flow through insurance companies each year. Whether it’s monthly bordereaux or SoVs, the challenge is capturing the information, applying business validation and integrating with existing systems.
It’s expensive, error-prone and hard to scale. Moreover, much of the value remains in the heads of employees, leading to operational inefficiencies and key-man risk.

Quantemplate’s user-friendly tools leverage machine learning to enhance your data operations.

Your data is rapidly harmonised and made available for analytical querying or downstream systems, allowing you to monitor your exposure in real time. The more you use Quantemplate, the smarter it gets, locking-in your institutional knowledge.

Improve operational efficiency by orders of magnitude
Exceed requirements for auditability and compliance
Get business insight from your data faster
Get better data: eliminate errors and improve quality from cedants

& legacy data

Drive digital transformation
Unlock legacy data and break down silos

In a typical insurer, data is fragmented and siloed across multiple warehouses, often segmented by business lines, geography, M&A activity, and the time the system was built. This prohibits a comprehensive view of customers, claims-to-underwriting insights, market intelligence, etc. Auditing is challenging, business logic and rules are cumbersome to update, and rolling-up the books for auditors, financial disclosures, or during market- or catastrophe-driven events takes months. With IFRS 17 on the horizon, insurers need a more efficient and flexible way of consolidating their enterprise-wide data for financial reporting

Quantemplate works in a non-invasive manner to connect data from all your systems.

Easy-to-configure tools automate data matching, apply business rules and logic, and assign results to appropriate lines, coverage, and contracts. Quantemplate can distribute data throughout the organisation: from feeding underwriting and pricing systems, to exposures on CAT systems, to general ledgers, reserving, and claims. And because Quantemplate is so easy to use, data-driven decision making can permeate your organisation.

Unlock insights from your legacy data
Get a whole-business view of exposure by dissolving silos
Ensure enterprise-wide data consistency
Drive digital transformation
throughout your organisation


Transform your productivity
Expedite your exposure and model processing

Processing Schedules of Values (SoVs) drives some of the biggest costs and operational inefficiencies in P&C business lines. Frequently all of the exposure and policy data to feed models or other systems resides in differently-formatted spreadsheets, stored queries, and employees’ heads. Large-scale outsourcing of manual processing is common, meaning scaling operations is expensive and making audit-trails, rule-enforcement, and institutional learning challenging.

Quantemplate uses machine learning to help transform your data inputs into a format your downstream models and systems can use.

Once your data pipelines are set up, processing is automated, dramatically reducing the timelag between receiving data, running models, pricing business and quoting to brokers. Eliminating manual processing, your business can be scaled cost-effectively and core IP developed, retained and shared.

Price risks faster – be the first
to quote to your brokers
Slash costs and decrease analysis lag time
Scale your business cost-effectively
Spend less time formatting spreadsheets, more time on value creation
See how Quantemplate can help you
Get in touch

Program business

Get insight into your intermediaries
Rapidly integrate and optimise program business

Program business is a key lever in growing your book of business without a proportionate growth in costs. However, onboarding and servicing these partnerships requires ongoing effort to merge their data with yours. Labour-intensive processing of spreadsheets can be costly, slow and error-prone, limiting insight and transparency into the risks you’re underwriting, and your intermediaries’ performance. The overhead of bringing on new partners limits your capacity to grow into new markets and business lines.

Using Quantemplate, insurers have slashed integration overheads and reduced multi-month onboarding processes to less than a week.

By automating dataflows and creating machine-learning based schema mappings, Quantemplate drives operational efficiency. Incoming data is validated to ensure it meets your underwriting guidelines and mapped to allow rapid insight into your intermediaries’ performance, allowing lines of business, coverage or portfolio composition to be adjusted with minimal lag.

Slash your data processing overheads
Understand the risks your intermediaries are underwriting
Benchmark portfolios and take the right measures to improve performance
Grow and diversify
by onboarding new partners faster

Underwriting capacity

Grow your premium and profitability
Write more business and unlock insights

A typical commercial specialty insurer might see thousands of data submissions for new business per year, all from different sources, in differently formatted spreadsheets and requiring manual processing to feed pricing models and downstream systems. Triaging and responding to all incoming submissions is a challenge, so most insurers focus on renewals, missing potential new sources of premium growth.

Beyond the missed market opportunity, without the resource to evaluate the data in each submission in detail, simplifying assumptions need to be made. Without a full understanding of the risks and how they correlate to the rest of the book of business, pricing may not be fit-to-market.

Quantemplate accelerates the processing of large volumes of submissions, meaning you can evaluate a higher proportion.

Stop turning business away because you don’t know what it comprises: systematically assess risks and rapidly pass on to pricing and downstream systems. Faster insight from your submissions leads to faster quoting, building relationships and creating competitive advantage. Easy-to-use analytics allow instant interrogation of your data, unlocking insights into year-on-year performance.

Increase your underwriting capacity and grow your business profitably
Choose better business by rapidly analysing the content of your submissions
Apply validation rules to check that incoming risks meet your underwriting guidelines
Analyse your book of business by account, region, producer, year-over year, etc.

Claims efficiency

Analyse faster, reserve more accurately
Accelerate your claims data processing

Legacy claims processes often mean claims and policy data is fragmented across systems, compounded by third-party adjusters providing data in disparate formats. This slows claims assessment, meaning reserving is based on old data, whilst the data needed to identify trends – including fraud – is fragmented and harder to access. The claims landscape is changing, and those companies that can understand and leverage their data will have a significant edge in improving loss outcomes.

Quantemplate works with your existing systems to bring all your claims data into one place.

From your unified data identify trends or opportunities for better underwriting or actuarial analysis. Apply your validation rules to prioritise claims and flag potential fraud, improving your loss ratio. From your unified data, feed your Loss Development models with timely accurate information, enabling proper reserving.

Integrate new claims data and sources
Apply your validation rules to flag potential fraud
Implement better reserving due to lower lag
Assess claims efficiently and accurately for higher customer satisfaction