Course in Solvency Assessment Using Real-Time Data
Online 300-hour course in solvency assessment using real-time data. 6 modules covering Directive 2009/138/EC (Solvency II), Delegated Regulation (EU) 2015/35 (standard formula) and Apache Kafka. Assigned tutor and enrolment open.
Take the controls.
Run a real engineering trade-off from this programme. Move the sliders, watch the model react in real time and beat the challenge.
What you will be able to do
Explain which solvency metrics should be monitored and how often.
Design a data architecture for continuous monitoring.
Build approximations of the solvency capital requirement.
Monitor market and credit risks in near real time.
Track the evolution of technical and underwriting risk.
Define alerts linked to risk appetite and the ORSA.
Establish the governance and reporting of the monitoring system.
Who it's for
- Risk and solvency analyst who wants to specialise in Solvency Assessment Using Real-Time Data.
- Capital actuary who wants to specialise in Solvency Assessment Using Real-Time Data.
- Risk data engineer who wants to specialise in Solvency Assessment Using Real-Time Data.
- Head of the risk management function who wants to specialise in Solvency Assessment Using Real-Time Data.
- Regulatory reporting analyst who wants to specialise in Solvency Assessment Using Real-Time Data.
- Financial risk controller who wants to specialise in Solvency Assessment Using Real-Time Data.
- Graduates in engineering or sciences seeking to enter insurance undertakings.
What you'll work with
- Directive 2009/138/EC (Solvency II)
- Delegated Regulation (EU) 2015/35 (standard formula)
- Implementing Regulation (EU) 2023/894 (reporting templates)
- BCBS 239 Principles (risk data aggregation)
- Regulation (EU) 2022/2554 (DORA)
- EIOPA Guidelines on ORSA
- ISO 8000 (data quality)
6 modules · 300 h
1.1Own funds, minimum and solvency capital requirement1.2Economic balance sheet and market-consistent valuation1.3Regulatory reporting frequency versus management needs1.4Why quarterly reporting is too slow for some decisions1.5Indicators that can be observed daily1.6Internal sources: policies, claims, treasury and portfolio1.7External sources: markets, interest rates, currencies and spreads1.8Latency, data quality and data governance in real time1.9Difference between continuous monitoring and full calculation1.10Workshop: inventory of signals available daily
2.1Data model of the economic balance sheet2.2Incremental capture of business movements2.3Integration of market data and discount curves2.4Analytical warehouse versus transactional system2.5Fast approximate calculation and full recalculation2.6Workflow automation and error control2.7Traceability and reproducibility of every figure2.8Security and access segregation2.9Common tools and selection criteria2.10Practice: design of a daily indicator workflow
3.1Light recalculation methods for the capital requirement3.2Sensitivities and main risk factors3.3Reaction curves of the ratio to market movements3.4Replicating portfolio approximation3.5Polynomial and regression approximations3.6Validation of the proxy against the full calculation3.7Acceptable error and recalculation thresholds3.8Periodic updating of coefficients3.9Documentation and internal approval of the proxy3.10Practice: proxy for an entity's solvency ratio
4.1Interest rates: duration, convexity and matching4.2Equities, property and alternative assets4.3Credit spreads and rating migration4.4Currency and position hedging4.5Liquidity: collateral, derivatives and cash requirements4.6Concentration by issuer, sector and country4.7Early warning signals in markets4.8Impact of a sudden movement on the ratio4.9Interaction between assets and liabilities4.10Practice: daily market risk dashboard
5.1Evolution of frequency and average cost in near real time5.2Early detection of large claims5.3Catastrophic events: rapid exposure estimation5.4Cancellations, renewals and portfolio mix5.5Provisions: signs of deterioration before closing5.6Reinsurance: use of layers and recoverables5.7Operational and process risk5.8Leading indicators of technical result5.9Escalation thresholds for the risk committee5.10Practice: early warning for a catastrophic event
6.1Risk appetite framework and operational limits6.2Protocol for action when a threshold is breached6.3Daily, weekly and quarterly reporting: content of each6.4Relationship with the own risk and solvency assessment6.5Supervisory expectations for continuous monitoring6.6Independent validation and internal audit6.7Communication with management and the board6.8Model risk and version control6.9Common mistakes in solvency dashboards6.10Final project: real-time solvency dashboard
How you'll learn
100% online training on the SEIUM campus, with downloadable material, recorded lessons and an assigned technical tutor. No fixed timetables: students progress at their own pace within the intake, which makes it possible to combine study with work.
Each module combines theory, guided reading of the original standard and applied exercises. The working software is Apache Kafka, Databricks, Python (pandas), Power BI, CCH Tagetik, in free, academic or evaluation versions. Assignments are based on real procedures for designing solvency dashboards, calculating approximations of the SCR and alert systems for appetite limits. Assessment is continuous per module plus the final integrating project.
Build it end to end
Your final project follows the real engineering workflow, step by step, reviewed by your tutor.
Explain which solvency metrics should be monitored and how often.
Design a data architecture for continuous monitoring.
Build approximations of the solvency capital requirement.
Monitor market and credit risks in near real time.
Track the evolution of technical and underwriting risk.
Where this takes you
Requirements
- No prior qualification is required.
- Internet connection and a computer capable of running the programme's software.
- Sufficient level of Spanish to follow technical regulatory reading.
Ready to start?
Send your application today. Our admissions team replies within 72 hours with your study plan and funding options.
Frequently asked questions
The programme totals 300 hours spread over 3 to 5 months. That is an average of 10 to 15 hours per week, compatible with a full-time job.
The programme works with Apache Kafka, Databricks, Python (pandas), Power BI, CCH Tagetik. Free, academic or evaluation versions are used, and the tutor indicates the free alternative where one exists.
A SEIUM Institute diploma upon passing the continuous assessment and the integrating project. It is in-house training, not an official Ministry qualification.
Yes. Modules passed in a Course or Postgraduate Diploma in the same area are credited towards the advanced programme. Check the recognition policy when you enrol.
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