Banking and Insurances

Data Science and Big Data for banking and insurance industries

Thanks to PiperLab solutions, banking and insurance companies can extract the full potential from their data: learning about and segmenting their clients, anticipating their inclined behavior or their product cancellations, or helping them improve their risk profiling, fraud and credit scoring models.

Prominent Clients
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Did you know

that consulting Borme can help you assess the risk of a client failing to pay back a loan?

that having received a fine can be positive when asking for a loan?

knowing when, what and how people tweet is a source of socioeconomic information about a region?

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Data about the Industry
of organizations
developing Data Science Projects are improving their risk profiling.
of organizations
consider improving user experience through Big Data a top priority.
of companies
use bank transactions and website visit registers as a source of information.
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Solutions
Risk Scoring
We use both internal information from the company and external data to train models that analyze accident, fraud or loan risk scores, integrating this information into existing processes.
Scoring de riesgos de negocio
Product enablement and abandonment
Our goal is to improve the client's experience in all different products of an organization. We analyses which variables are relevant when it comes to determine if a user will purchase or abandon a product, creating alerts and integrating the result of predictive models into sales or communications management tools.
Predicción de abandono con big data
Revenue generation and client segmentation
It is essential to have a global vision of a client to improve our knowledge of them and discover groups that behave in the same way, allowing us to adapt offers to their needs and preferences. We integrate all the data in an organization to detect behavioral patterns, enhancing the client profile and improving their management during the whole life cycle.
Segmentación de clientes
Microeconomics and Macroeconomics Indicators
We use unconventional data (visit logs, social media information, third party data, etc.) to estimate the evolution of stock market indexes or to monitor carefully data about economic activities such as GDP or unemployment rates. The goal is to design successful strategies in some markets or to assess the risk of investment in a particular geographical area.
Indicadores económicos
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Data we use
Icono de movimientos de banca y seguros
Bank transactions
This is gold for financial organizations. They teach you about clients and how to offer the best possible service and ensure customer loyalty.
Icono de datos y logs
Web Platform logs
in an industry engaged in a digital transformation, learning about the online behavior of clients is critical to develop internal processes.
Icono de redes sociales
Social Media
We help you learn from your clients through the information they publish in social media, detecting trends, profile information and life decisions.
Icono Open Data
Open data
Public organizations, such as INE (National Statistics Agency), BORME (Registry of Companies), BOE (Government Publication) or the land registry throw information that we integrate in our Big Data models for banking and insurance organizations.
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Quotes
Foto de Oscar de Rastreator
"At PiperLab we discovered excellent professionals, technology-innovation natives who worked with us developing projects with amazing results.
They work in a flexible way and that helped us generate outstanding projects in the Data world".
Óscar López Ugarte
Head of data de Rastreator.com
Foto de Aitor Chinchetru, CEO de Wanna
"Innovation, new challenges and good work are all characteristics describing the team at PiperLab. We posed a complex and tough challenge and they build the perfect solution: advanced in concepts and elegant in technology."
Aitor Chinchetru
CEO in Wanna & COO in Fintonic.

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