Life Events
Life Events is a real-time service that provides structured insight into meaningful changes in your customers’ lives. By combining 1st-party data (portfolio data) with 3rd-party data (public registries), Life Events automatically identifies and delivers relevant updates such as property purchases, address changes, or company activity. This enables proactive communication, smarter workflows, and an always up-to-date understanding of your customers.
Event Types
Life Events covers a wide range of meaningful updates, including:
- purchasing a new home or car
- changing address
- creating or closing a company
- income changes
- updates to ownership or property characteristics
Instead of relying on static profiles or outdated information, Life Events gives you a continuously updated view of what is happening as it happens.
Life Events are available for:
- Company events
- Person events
- Property events
How Life Events Are Generated
Life Events are created by combining two types of data:
- 1st-party data (portfolio data) – the persons, companies, properties, and vehicles already present in your portfolio, based on the data you hold in your own systems. This defines which entities Predicti monitors on your behalf.
- 3rd-party data (public data) – public data sources that provide updates such as property transactions, address changes, company filings, ownership updates, and demographic information.
Predicti continuously compares your portfolio with newly available public data. When public data contains a relevant change for an entity in your portfolio, Predicti generates a Life Event and delivers it immediately.
This ensures that you only receive events related to the customers and entities already included in your portfolio.
How Life Events Works
Life Events uses the combined data from your portfolio and public data sources to continuously detect changes. To give a complete and always up-to-date picture, Life Events includes:
Real-Time Events
Delivered immediately when new information is registered in public data sources.
Historical Events
Provides insight into past activity, long-term patterns, and customer history.
Event Classifications
Each event falls into one of three classifications, reflecting how the event was generated:
- Fact: Verified changes based on confirmed data (e.g., property purchased, company closed).
- Model-based updates: Events generated from statistical or ML models that estimate or update a value (e.g., updated income estimates or the likelihood of children in the household).
- Future predictions: Events that represent predicted future outcomes (e.g., that it is likely that a customer will move to a new address within the next half year).
Future-Dated Events
Some fact-driven event types can be detected before the effective date. A common example is a property purchase where the takeover date lies in the future. Even though the customer has not yet taken possession, the transaction may already be registered in public data.
Life events deliver life events as soon as they become available, allowing you to:
- reach out to the customer before the change happens
- prepare onboarding steps in advance
- trigger workflows ahead of time
- understand upcoming shifts in the customer’s situation
Future-dated events include:
- eventDate – the effective future date
- eventAvailableDate – when Predicti first detected the event
Typical Use Cases
Life Events can support many operational, advisory, and commercial workflows:
Onboarding & Activation
Trigger relevant actions when customers move, buy a property, or create a company. Future-dated events enable engagement even before the change occurs.
Customer Retention
Identify significant life changes early and follow up proactively.
Cross-sell & Upsell
Detect new financial needs when customers enter new life phases or acquire assets.
Risk Monitoring
Use ownership changes, financial filings, or property activity to support risk assessments.
Customer Timeline
Build a chronological view of personal, financial, and property-related activity across your portfolio.
Event Model & Structure
All events share the same structure, regardless of whether they relate to a person, company, or property. The only difference is the entity identifier (personId, companyId, or propertyId).
Below is the shared structure in API order:
<entity>Id
Unique ID identifying the entity the event relates to.
eventDate
Date and time when the event occurred or will take effect.
eventId
Unique identifier for the event.
eventType
Type of event, such as address change, ownership transfer, financial update, or value change.
eventValues
Object containing the values affected by the event.
newValues
The new values introduced as part of the event.
oldValues
The previous values replaced by the event.
eventDateAccuracy
Indicates the precision of the event date (exact or approximate).
eventAvailableDate
Date when the event became available in Predicti.
isExperimental
Indicates whether the event is experimental. Experimental events may evolve over time as logic or data sources improve.