Global Talent Intelligence partnership with $70B+ New York based Insurance & Financial Services Leader

Discover How Draup Enabled AI-Driven Workforce Transformation for an Insurance & Financial Services giant

~10000

Employees

$70B

Revenue

BFSI

Industry

New York, U.S.

Headquarters

About the organization

A global leader in insurance and financial services, the organization operates across 40+ markets and serves tens of millions of customers. It is strengthening operational resilience while accelerating digital transformation, with a sharp focus on securing leadership and analytics talent and building long-term workforce capabilities across mature and emerging markets.

The Core Challenges

Unify Talent Data
Unify fragmented talent, role, and location data for enterprise-wide workforce planning.
Win the Talent Race
Attract and retain executive and analytics talent in highly competitive U.S., LATAM, and EMEA markets.
Track Emerging Skills
Define and track emerging skills in investment, data, and AI to future-proof critical roles.
Benchmark Talent Data
Use data on pay, diversity, and talent movement to benchmark peers and prioritize the right hubs.

The Solution

Data Scientist
PROFILE
LOCATION ANALYSIS
TALENT MARKET INSIGHTS
CAREER PATHS
DATA INTEGRATION
TECH STACK
The image is for representational purpose only.
01
Critical role intelligence
Standardized job families and quantified supply–demand gaps, peer bench strength, and hard-to-fill roles.
02
Competitive benchmarking
Tracked peer hiring, exec movement, and HR/tech team signals across key global markets.
03
Org structure analysis
Benchmarked reporting lines, spans of control, and workload distribution across competitors.
04
EVP + location strategy
Compared comp/benefits/EVP (incl. diversity & policy impact) and mapped talent hotspots + adjacent sectors.

Outcome

Unified global workforce strategy

Integrated leadership, investment, and data talent insights into a single decision-making framework for long-term planning.

Data-led hub prioritization

Enabled clear selection of global and U.S. hiring hubs based on talent depth, cost efficiency, and hiring feasibility.

Sharper competitive positioning

Comprehensive intelligence on compensation, benefits, and executive movement across major insurers and financial services peers accelerated proactive talent acquisition strategies.

Future-ready capability building

Clearer visibility into emerging skills and more accurate workforce planning across markets, supporting diversification, internal mobility, and targeted upskilling.
6,100+​
Locations
4M+​
Career Paths​
1.7M+​
Peer Group Companies​
28K+
Skills
3,500+​
Roles
1B+​
Professionals​
55K+​
Universities​
1B+​
Job Descriptions​
200K+​
Courses​
180K+​
Technology Solutions​
1.6M+​
Account Priorities​
Labor Market Data Contextualized with Business Intelligence for Every Decision

Analyzing 1B+ data points
daily from 100K+ sources

6,100+​
Locations
4M+​
Career Paths​
1.7M+​
Peer Group Companies​
28K+
Skills
3,500+​
Roles
1B+​
Professionals​
55K+​
Universities​
1B+​
Job Descriptions​
200K+​
Courses​
180K+​
Technology Solutions​
1.6M+​
Account Priorities​
AICPA SOC2 TYPE 2
SOC 2
GDPR Logo
GDPR
ISO 27001 Logo
ISO
EAIGG Logo
EAIGG

Ethical AI, Backed by Global Standards

Draup, an AI-first company, upholds global standards like SOC 2, GDPR, and ISO 27001. As an EAIGG member, we audit for bias and build trustworthy AI.

Data Trust &
Methodology
at Draup

Draup uses a structured methodology to reduce inaccuracies and prevent misleading information, with a focus on transparency and responsible data practices.

Data Transparency and Coverage

Draup sources data from diverse, vetted global inputs including public datasets, labor information, professional ecosystems, and industry research. Coverage varies by region and role, and we supplement limited areas with alternative sources and analyst-led modeling.

Profiles Behind the Numbers

All aggregate insights related to buyers, roles, skills, and locations are grounded in structured, anonymized human and organizational profiles rather than pure extrapolation. This ensures context, reliability, and protection of personal identities.

Data Hygiene and Integrity

We maintain a clean, accurate data environment by removing duplicates, outdated entities, and invalid records. Automated checks powered by ML models and analyst reviews work together to ensure clarity and accuracy for every entity, such as buyer, role, skill, technology, or company.

AI Governance and Bias Mitigation

Our governance framework combines automated evaluations with Human-in-the-Loop reviews. We use statistical checks, audits, and cross-source comparisons to reduce demographic and structural bias before insights reach the platform.

Compensation Guardrails

Compensation insights use blended, directional inputs such as aggregated ranges, benchmarks, modeled distributions, and market signals. We distinguish clearly between modeled and reported data and apply guardrails to prevent over-interpretation.

Hourly and Frontline Workforce Coverage

For hourly, frontline, and blue-collar roles where digital visibility is limited, we incorporate government datasets, localized labor information, and specialized partners to build a more complete and balanced view of workforce supply and demand.

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