VIEWPOINT

2024

HOW TO SHAREC U S T O M E R D ATA
IN BANCASSURANCE
Boosting data exploitation
as a differential value

AUTHORS
José González

A customer-centric approach has become anEduardo Munguía

imperative in the financial services sector,

Borja de la Cuesta

increasingly supported by the processing of vast
amounts of market and customer data, among otherRonald Engelfactors. However, the complex and ever-changing

Yoshiro Makita

regulatory environment presents challenges forAndreas Buelow

personal data sharing. This Viewpoint shares somebest practices for addressing these challenges tounlock the full potential of personal data in thebancassurance sector.

ARTHUR D. LITTLE

VIEWPOINT

UNLOCK ING THE FULLP OTENTIAL OF DATA
Banks and insurance companies collaborate tooffer more tailored products and services thanthose they can develop on their own. However,effective customization only works through a
deep understanding of the customer’s personalsituation. Thus, accessing the largest volume

EFFECTIVEC U S T O M I Z AT I O NO N LY W O R K S
THROUGH A DEEPU N D E R S TA N D I N G
OF THE CUSTOMER’SP E R S O N A L S I T U AT I O N

of meaningful personal data has become thecrucial factor in offering products and services
adapted to each client’s needs and behaviors.
The alliance between banks and insurers allows

1. Business — understanding the potential ofthem to make the most of both worlds: extensive

data, prioritize data-sharing opportunities,

knowledge of the customer and a wide sales

and define feasible roadmaps

distribution network with deep expertise that canbe translated into simple, tailor-made solutions
and products.

2. Legal — ensuring regulatory compliance,
managing customer consent, and developing
privacy policies

Despite being theoretically clear, achieving a

3. Technology — deploying the requiredsmooth collaboration is a complex challenge;
data ownership, multiple stakeholders, different
companies and roles, independent strategy

technology stack to capture and processdata properly and at the right timeroadmaps, a broad range of opportunities, and

4. Operating model — coordinating teams andprivacy and compliance constraints are some

capabilities from opportunities identificationof the challenges banks and insurers face.

to implementation

Overcoming these issues and implementation
obstacles requires an enterprise approachstructured around four workstreams (see Figure 1):

Figure 1. Four workstreams of an enterprise approach

Figure 1. Four workstreams of an enterprise approach

Business

Potential of data, usecase prioritization &roadmaps definition

Legal

Regulatorycompliance, consent
management &privacy policy

TechnologyTechnology stack,how & where to capture& process data

Operating model
Operational data
model — fromidentification toimplementation

Source: Arthur D. Little

HOW TO SHARE CUSTOMER DATA IN BANCASSURANCE2ARTHUR D. LITTLE

VIEWPOINT

BUSINES S: UNDERS TANDING
THE P OTENTIAL OF DATA
Aligning business strategies between banks andinsurance companies is essential for successful
data-sharing initiatives. Both banks and insurancecompanies (and the potential joint venturesinvolved) face a wide array of opportunities

BOTH BANKS ANDI N S U R A N C E C O M PA N I E S
FA C E A W I D E A R R AY O FOPPORTUNITIES WHEN
D I V I N G I N T O T H E D ATAWORLDwhen diving into the data world. Data-driven
opportunities are typically presented as use
cases where a specific application of personal
data processing is described for a clear objective.

- Example of short-term ambition.

Increase average number of products percustomer; include variables related to

To ensure that the identification of use cases

personal circumstances (e.g., if someone

translates into delivering real value to customers

recently became a parent or started

while providing a coherent user experience,

entrepreneurial activities) to better

it is necessary first to set clear priorities andunderstand and serve customers.

objectives. This step may involve identifying
key customer segments, drafting marketing
campaigns, designing innovative products andservices that cater to specific customer needs,
and so forth. By aligning the business strategies
among all partners, the organizations involved
can maximize the benefits of data sharing and2. Translate ambitions into data use cases(e.g., definition, dataflows, impact levers).
Upon defining ambitions, workshops may
be helpful for use case identification anddefinition.

- Example of short-term ambition

drive growth in a pragmatic and non-monolithic

translated to use case. Create a trigger

manner.

to detect when a customer becomes or

A four-step process can be a helpful tool totranslate ideas into feasible implementation
roadmaps:

is about to become a parent and offer atailored life insurance policy. Be sure to
involve experts from different areas in
the identification of use cases and consider

1. Define short- and long-term ambitions

the portfolio and business dynamics offor use of data. Each company has its own

each company since different use cases

priorities (e.g., innovative products, excellence

might have significantly different impacts.

in customer service, use of Internet of Things),

For instance, although offering simple

and these should be reflected in the ambitions.

bancassurance products at the right- Example of long-term ambition. Develop
more innovative products and customer
service; ensure offered products andcustomer service are both provided ina tailored way to each customer.

moment might have good penetration,
improving retention and renewals mighttranslate into a larger economic impact.

- Define clusters or segments to ease

identification of use cases. As shown in
Figure 2, identifying potential use cases
might be easier when thinking about thedifferent steps of the customer journey.

HOW TO SHARE CUSTOMER DATA IN BANCASSURANCE

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ARTHUR D. LITTLE

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Figure 2. Data use case identification example
Figure 2. Data use case identification example
Portfolio management•••

Tailored renewal pricing
Customized journeys for renewals
Recovery models

Claims•••Fast payout models
Efficient management of providersSmart contractsService•••

Propensity-to-pay model
Segmented actions based on lifetime value“Next best action” models

Sales•••

Actions based on events
Detection of underinsured customers
Digital support tools

Value proposition•••Price-sensitivity models
Rewards programs through IoT/wearables
Usage-based insurance

Source: Arthur D. Little

urce: Arthur D. Little

3. Classify use cases according tostakeholders’ preferences and conditions.
Classification cannot overlook economic

LEGAL : REGUL ATORYCOMPLIANCE PRIORIT Y

aspect (business cases needed), companies’The first challenge that may come to mind whencapacities, and defined ambition. These arethinking about personal data sharing is how totypically addressed in two steps:

navigate the complex legal landscape surrounding- Qualitative classification into high,personal data protection. Banks and insurance

medium, or low priority based on use

case’s enabler nature (i.e., eases future
implementation of other use cases),alignment with overall company strategy,ease of implementation, and potential
impact (high-level estimate)- Final classification, considering detailed
business cases of high-priority cases (i.e.,the “winners” of previous classification)companies must comply with regulations, suchas the General Data Protection Regulation (GDPR)
in the EU, the California Consumer Privacy Act(CCPA) in the US, or similar regulations elsewhere.
These typically require organizations to obtain
explicit consent from customers before collecting,processing, and sharing personal data. Additionally,companies must ensure data is securely stored andprotected from unauthorized access.
The legal workstream has a clear and concise

4. Establish implementation roadmap

mandate: to build a balanced and comprehensive

for priority use cases validated by all

legal framework that allows the implementation

stakeholders. It is important to consider inof data use cases in the short and long term.

which entity the use case will be deployedNotwithstanding, wording this legal frameworkas it will determine resources needed forso it is acceptable to everyone can be challenging

development.

without the proper support and guidance from- Example across stakeholders. If all thepriority use cases will be developed on thebank side, there might be delays, while theinsurance side might show spare capacity.

the business side. Additionally, customer consent
is not the only component of building the legal
framework; legitimate interest, privacy policies,
and the use of anonymization technology
solutions are powerful resources that might
speed up implementations and even provide
extra security in the eyes of regulatory bodies.

HOW TO SHARE CUSTOMER DATA IN BANCASSURANCE

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ARTHUR D. LITTLE

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Every partnership should be analyzed in depth.
Considering the particularities of each legal
setup, four key learnings can always be applied
when addressing data-sharing opportunities:
1. Define the potential use cases. A detailed
definition of the potential use cases (short-CUSTOMER CONSENTI S N O T T H E O N LYCOMPONENT OF
BUILDING THE
LEGAL FR AMEWORKterm and long-term), including which personal
data and dataflows are required, is crucial
before beginning to build the legal framework,
since it must be as specific as possible toensure robustness. Collaboration between
legal and data analytics teams is necessary
for the right trade-off between the criticalityof personal data and the accuracy of thedeveloped models. For example, geolocation
may be critical data that could instead be
replaced by postal codes without hindering
the accuracy of the resulting model.
2. Consider and leverage different legal
enablers at different stages of a usecase. Data analytics models typically requirea training stage before deployment and thecorresponding data processing in each stage
can be significantly different. Thus, the legal
framework should be ready to handle these
two ways of working with data analytics models.
3. Manage customer touchpoints. Efficient

TECHNOLOGY: DIAGNOSIS& ALTERNATIVES
Since there is no best platform alternative apriori — development of a new shared bankbancassurer platform, migration to one of theavailable platforms, coexistence/communications
between existing platforms — each caseshould be studied considering the stakeholders’particular circumstances and strategies.
Despite a plethora of alternatives, someessential analyses should be used to endorse theone selected. Among these evaluations is therelationship between entities. For example, one
stakeholder might be a subsidiary of the otherand thus its platform might be embedded in theparent environment. Other key considerations
relate to specific software licenses, security, andaccess control. These issues must be examinedmanagement of the customer touchpoints is

closely by IT security and the legal department.

key for collecting a larger share of customer

These assessments become even more complex

consent and ensuring regulatory compliance.

when linked to platform-evolution roadmaps

4. Employ anonymization techniques.

where updates and improvements occur

Anonymization techniques can enhance data

repeatedly following a sprint-based methodology.

protection. However, the anonymization

This complexity is one reason technology

process is also subject to regulation and might

diagnosis and the methods for evolution translate

shrink the potential impact of a use case if notinto endless discussions. Nevertheless, we haveapplied efficiently. There are anonymization

identified one ultimate truth: technology cannot

techniques that preserve the greatest amountdrive business opportunities or use cases. Instead,of information while ensuring the regulatory

business must point out opportunities, andcompliance of the result (typically measured

technology should be used to find the necessaryby the K-anonymity and L-diversity factors ofenablers to engender those opportunities since

the resulting anonymized base) and federated

there is always a way to make things happen.

learning techniques that allow the training ofmodels with all the available information andno “physical” data sharing between parties.

HOW TO SHARE CUSTOMER DATA IN BANCASSURANCE

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ARTHUR D. LITTLE

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OPER ATING MODEL :IDENTIFICATION TO
IMPLEMENTATION

2. Strategy and governance committee. This
committee is not only in charge of detailing
how to implement and run each use case butalso of allocating the necessary resources toOvercoming the previous challenges can bemeet the roadmap defined by the businessmeaningless without the appropriate coordination.

committee/board. Technology and legal team

The coordination needed for data use cases is evenmembers must be involved in the use case,more challenging considering that adopting a data-detailing activities since their input is crucial

driven business requires the active involvement ofto ensuring an adequate customer experience

top management roles, cooperation among teams

and regulatory compliance.

from different areas, and continuous monitoring ofresults and performance.

3. Project committee. This committee’sresponsibilities go beyond the implementation

According to Arthur D. Little’s (ADL’s) experience,of use cases, since monitoring and fine-tuninga three-level governance model (see Figure 3)

are compulsory activities for success in aallows for defining and implementing data use

data-driven business. Assigning an owner tocases with a real business impact:each use case helps generate initial traction

1. Business committee/board. Top
management roles must be responsible for
identifying opportunities and setting theafter use case deployment and provides thebusiness committee/board enough visibility
on business needs for future opportunities.

priorities to be tackled through data. TheseOnce again, every partnership should be analyzed inopportunities and priorities must be coherent

depth. The different structures of each partnershipwith corporate ambitions and interests.

(e.g., bank + insurer, bank + insurer + joint venture,

Despite the business committee not beingetc.) can add extra complexity to the definitionin charge of defining the actual use cases,of the governance model. According to ADL’s

it must set and endorse the implementation

experience, this extra complexity can be handled

roadmap to ensure necessary commitment

by ensuring the segregation of duties (as previously

among all parties.

described) and maintaining an “as reduced aspossible” audience in the different committees.

gure 3. Governance model defined at three levels

Figure 3. Governance model defined at three levels

Business committee/board
Identify opportunities & align on use case roadmap

Strategy & governance committee
Define operation & allocate resources

Project committee
Track developments & performance after deployment

Source: Arthur D. Little

HOW TO SHARE CUSTOMER DATA IN BANCASSURANCE6ARTHUR D. LITTLE

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CONCLUSIONT H E PAT H F O R W A R DO R G A N I Z AT I O N S M U S T R E M A I N A G I L E ,C O N S TA N T LY R E A S S E S S I N G T H E I R
S T R AT E G I E S A N D P R I O R I T I E SAligning business strategies and setting clear objectivesare vital steps in delivering real value to customers andproviding a coherent user experience. Organizations
must navigate the complex legal landscape surrounding
personal data protection while building a balanced andcomprehensive legal framework. Technology should not
drive business opportunities or use cases; instead, itshould find the necessary enablers to realize them. Lastly,
effective coordination between banks and insurancecompanies is essential for the successful implementationof data analytics models.
By adopting a structured approach, banks and insurancecompanies can unlock the full potential of personal data
sharing and drive growth in the bancassurance sector,
enabling innovative product and service offerings thatcater to customer needs. As the industry continues toevolve, organizations must remain agile, constantly
reassessing their strategies and priorities to ensure they
are meeting the ever-changing needs of their customers.

HOW TO SHARE CUSTOMER DATA IN BANCASSURANCE

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