BANKING

The most valuable asset in the bank is Data

Make Sense

The banking industry must constantly keep pace with evolving and tighter regulatory compliance norms and savvier customers. The primary focus of banks using big data and analytics is on customer analytics. Large investments are being made in AI to enhance customer service and in mobile banking. The banking industry relies on business analytics in other areas like - 

 

banking-infographic

Fast Data,

Faster Banking

We have worked with several leading banking companies, bringing our Data Innovation partnership model that combines our business and technology solutions, partner eco-system, decade long proven track record of customer success and execution capability to deliver assured business value.

Get a jump start
“Inteliment Team helped us in building a unique solution for our needs. Their understanding of Analytics makes things easy around us.”
Head BI
Leading Bank
“Our business goals and corporate strategy was defined, and Team Inteliment was instrumental in implementing our project well and within time and helped us leverage the investment we had made in Analytics tools.”
HR Head
A major player in Banking sector

Our banking solutions make sense

Risk and compliance

Risk and Compliance

Conduct asset and liability analysis; visualise aggregated market risk across asset classes and portfolios, credit risk and compliance risks.

Customer segmentation

Customer Segmentation

Obtain customer profitability performance, credit risk analysis and identify potential opportunities for cross-sales. 

Digital marketing

Digital Marketing

Identify buying habits, lifestyles and preferences. Understand how social relationships influence purchase behaviours and loyalty. 

Cross Sell and Upsell

Cross Sell and Upsell

“What if” analysis on the benefits of new products and promotions.
Improve sales through regional and local sales analysis, and customer segmentation analysis.

Fraud analytics

Fraud Analytics

Recognise patterns of fraudulent transactions, use these to be one step ahead of fraudsters, predict the next fraud in progress and make recommendations.

Top N analysis

Top N Analysis

Quantify customers’ potential value, differentiate marketing and service, find valuable prospects, increase revenue and margins.

Churn prediction

Churn Prediction

Prevent attrition, take action with at-risk customers, improve marketing ROI, understand what lowers CSAT.

Fraud detection

Fraud Detection

Identify patterns of fraud, monitor activity for signs of fraud, stop fraud quickly, reduce costs, improve service.

Case Studies

1 min read

Credit Risk Management

A Fortune 500 bank which offers various financial services to it’s global customers, faced the challenge of analysing...

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Centralising Data

One of our customers who is among India’s Top 5 private sector banks wanted to improve decision making. Centralising...

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Recruitment Performance

The customer, one of the largest banks in APAC region, needed to be more competitive in talent acquisition, eliminate...