The Digital Innovation Award - Wenalyze

1. In DataWe Trust

2. 15 to 20% of the critical data insurers collect from agents and
enterprises customers is wrong. This problem adds manual tasks while
ignoring customers real risks.
Wenalyze Solution leverages open data sources to automate
processes while adapting enterprises customers risk assessment to
real risks
Source: Accenture

3. Track Record
Process Automation
60-
100%
Loss Ratio Improvement
3%
Data Quality
Increase
80-90%
Adding Risk Indicators to IncreasePricing Models Accuracy
Updating, Completing and Verifying CurrentData
Automating Underwritingand Renewals Processes

4. 4 Steps
Data is captured 50 data points per
second
are matched from hundreds of data
sources
1
2
3
4
Insurer sends data including customer
business Name and Postal Code
Data is automatically analyzed, compared,
updated, verified and enriched
Data is delivered back to the
insurer with seamless integration

5. Bar
1602WashingtonSt,MA 02118,
UnitedStates
TorroRestaurant ToroBoston
Bar&Restaurant
Activity
Name
Address
Employees Num.
Delivery
Opinions
Rating
WenalyzeData(2021)
Update, Enrich, Buildand Optimize
Insurer’sData(2018)
Update incorrect andinaccurate data and
verifies information
1
Enrich data with non-traditional risk data
points
2
Build Risk Indicators by combining
multiple risk data points
3
4
Optimize loss ratioprediction
by implementing Risk Indicators
ReputationalRisk
ManagementRisk
Claim Propensity Medium – (3%) High– (5.7%)
LastManager Change
7.2/10
8.1/10
No
“Awful service”
2.1/5
9
2021
1704WashingtonSt,Boston,MA 02118,
UnitedStates
9
Open
Data
Analysis

6. Flexible Data Acquisition_
Processing any type ofdata, even unstructured
Global Scalability_
Polyglotnatural language processing system
Proven Risk Indicators_
Loss Ratio improvement by adding risk indicators
Why
We Are
Ahead
100%Flexible Connectivity
API, Webservice,
Browser, Tokens,
Standards, SQL,
JSON, XML, CSV,
TXT
Synthetic
Data
Missing data is filled
with Machine
Learning
Instant Implementation
5 days to implement
new data sources

7. Data Points Combined
Scope Results
 Insurer Pricing team found strong Loss Ratio correlation with 4 of Wenalyze Risk
Indicators in SMEs propertyinsurance clients
Correlated Risk Indicators
Reputational Risk
Family Business
Online Opinions
Management Risk
1st Use Case – Loss Ratio Improvement
 Risk Indicators have been developed in-house and based on 3 years of Machine
Learning training
 Implementing these 4 risk indicators in pricing enables better risk selection and
increases pricingaccuracy
3ppLossRatio Improvement per year
12
7
5
59

8. OnlineDataPoints RiskIndicator
ReputationalRisk
Scoring
ManagementRisk
Claim Propensity
1st Use Case – Loss Ratio Improvement
7.2/10
8.1/10
OpenData
Higher +5.7%
3ppLossRatio Improvement per year

9. EmployeesNumber
TraditionalPropertyUnderwriting
Name
Address
Tax ID
Location
Activity
Propertyuse
BuiltYear
WenalyzeAutomatedUnderwriting
Automaticallyfilled by
Wenalyze
2 0 ’ 1 ’
2nd Use Case – Process Automation
Name
PostalCode
EmployeesNumber
Tax ID
Location
Activity
Propertyuse
BuiltYear
60 to100% Automationunderwritingfor General Liability,D&O, Cyber, and Property
insurance

10. 3
ToroBoston
9
Bar& Restaurant
Name
Address
Employees Num.
TorroRestaurant
1602WashingtonSt,MA 02118,
UnitedStates
9
3rd Use Case – DataQualityIncrease
WenalyzeData(2021)
Insurer’sData(2017)
Open
Data
Analysis
Updated
Updated
Completed
80 to 90% of critical data is updated,verifiedand completed
Activity Bar
Numberof Shops Unknown
1704WashingtonSt,Boston,MA 02118,
UnitedStates
Completed
Verified

11. Funded Global Outreach
12 People
2 Data Scientists
5 Software Developers
5 Business Developers
Proven Results with clients
located in USA, LATAM and
Europe
Presence
Experienced Team
Funded by go:hub, an
international Utilities Company
Innovation division

12. www.wenalyze.com
wenalyze@wenalyze.com
+34 963 318 749
Thank you for reading. Please, get in touch if you
need further information!