Build the control framework around data-driven underwriting that an examiner would accept.
Building Data-Driven Insurance Underwriting Models
A senior-level treatment of data-driven underwriting, focused on what changes outcomes.
📍 Tripoli🗓️ 5 training days📚 4 modules🎓 Accredited certificate
5intensive training days
4scientific modules
8training sessions
32detailed points
Course Overview
The audit trail behind data-driven underwriting matters as much as the decision itself. Capital, liquidity and reputation are all exposed by weak handling of the financial and banking practice discipline. The programme uses small-group work so that each participant's treatment of this strand of financial and banking practice is examined, not just described. The programme converts data-driven underwriting from an area of general awareness into a set of repeatable practices. The difficulty is not agreeing that this aspect of financial and banking practice matters — it is deciding what to stop doing to make room for it. Participants gain a realistic view of what this part of financial and banking practice costs and what it returns. It is pitched for practitioners with responsibility for data-driven underwriting, not for observers of it. Post-incident reviews keep identifying weaknesses in this aspect of financial and banking practice that were visible long before the incident. Participants leave with a first-ninety-days plan for the practice within financial and banking practice rather than a set of notes.
Expected Learning Outcomes
Document the approval chain for exceptions to policy on data-driven underwriting.
Select indicators that show whether data-driven underwriting is improving, and reject those that only look useful.
Review the contractual and legal exposure created by data-driven underwriting.
Define the scope and boundaries of data-driven underwriting so that responsibility for it is unambiguous.
Assess the concentration risk building up inside data-driven underwriting.
Build a concise control framework for data-driven underwriting that colleagues can follow without further explanation.
Who Should Attend
Financial technology and change staff modernising data-driven underwriting.
Credit and underwriting officers assessing data-driven underwriting.
Department heads accountable for the results of data-driven underwriting.
Board risk committee members overseeing data-driven underwriting.
Relationship and product managers whose targets depend on data-driven underwriting.
Experienced practitioners formalising an approach to data-driven underwriting that has grown up informally.
Course Modules
Data-driven underwriting: audit evidence and examiner readiness
2 sessions · 8 pointsSession 1Setting a limit on data-driven underwriting that will actually be respected
- Identify single points of dependency in data-driven underwriting and reduce them.
- Define the trigger that would require data-driven underwriting to be redesigned.
- Draft the minimum viable control framework for data-driven underwriting.
- Agree who signs off data-driven underwriting and record that they did.
Session 2Getting other functions to support data-driven underwriting
- Identify where judgement in data-driven underwriting is legitimate and where it is not.
- Set out the decisions in data-driven underwriting that require sign-off and by whom.
- Record the rationale for each significant choice made about data-driven underwriting.
- Decide what will be stopped to create capacity for data-driven underwriting.
Data-driven underwriting: measurement, models and their assumptions
2 sessions · 8 pointsSession 1What a supervisor will ask about data-driven underwriting, and in what order
- Set escalation thresholds for data-driven underwriting that work out of hours.
- Close out actions on data-driven underwriting rather than leaving them open indefinitely.
- Assess the capital consumed by data-driven underwriting under current and stressed conditions.
- Map the handovers in data-driven underwriting between functions and secure them.
Session 2Escalation and decision rights in data-driven underwriting
- Test data-driven underwriting against a scenario the organisation would rather not model.
- Check the accounting treatment applied to data-driven underwriting against current standards.
- Translate the appetite for data-driven underwriting into limits someone monitors daily.
- Agree the smallest change to data-driven underwriting that would be visibly useful.
Data-driven underwriting: regulatory obligation and supervisory expectation
2 sessions · 8 pointsSession 1Handling a breach of policy on data-driven underwriting properly
- Document the remediation plan for each known weakness in data-driven underwriting.
- Set early warning indicators for data-driven underwriting with defined action thresholds.
- Build the internal briefing that explains data-driven underwriting to those affected.
- Review the pricing of data-driven underwriting against the risk being assumed.
Session 2Evidencing that data-driven underwriting worked as designed
- Design the exception process for data-driven underwriting and require a documented rationale.
- Check the legal and contractual exposure created by data-driven underwriting.
- Prepare the summary of data-driven underwriting that senior management will read.
- Identify the key controls over data-driven underwriting and who tests them.
Data-driven underwriting: reporting that supports a decision
2 sessions · 8 pointsSession 1The assumption inside the model for data-driven underwriting that nobody revisits
- Confirm segregation of duties across initiation, approval and settlement of data-driven underwriting.
- Identify the data already collected that bears on data-driven underwriting.
- Name a single owner for each element of data-driven underwriting.
- Confirm regulatory reporting on data-driven underwriting is complete, timely and reconciled.
Session 2The paperwork for data-driven underwriting that is actually needed
- Review concentration by counterparty, sector and geography inside data-driven underwriting.
- Confirm client due diligence standards applied to data-driven underwriting are current.
- Agree what will be standardised in data-driven underwriting and what will not.
- Confirm reporting on data-driven underwriting reaches the committee that can act on it.
Choose the package that suits you
Silver Package
At least 3 people
USD1,250
- Workshop or Program Participation
- Airport Transfers
- Customized Badge
- Expert Mentorship (Private Sessions)
- Supervision & Secretarial Services
- Accredited Certificate of Participation
- Complete Training Kit
- Coffee Break
- Closing Ceremony
Gold Package
At least 3 people
USD1,850
- 5-night stay in a 5-star hotel
- Workshop or Program Participation
- Airport Transfers
- Customized Badge
- Expert Mentorship (Private Sessions)
- Supervision & Secretarial Services
- Accredited Certificate of Participation
- Complete Training Kit
- Coffee Break
- Closing Ceremony
Complete your registration
We will contact you within one business day to confirm.