BFSI Data Use Cases Built for Business Outcomes

Customer 360 for Banking

Problem Statement

Retail and commercial banking customer profiles operate in separate silos across card networks, core systems, and lending platforms, blocking branch cross-sell attempts.

Artha Solution

Implement Master Data Management (MDM) match-merge rules to resolve customer identities across digital and physical branches.

Data Domains Involved

Customer personal profiles, debit registers, credit card accounts, mobile logins

Technology Stack

MDM, Entity Resolution, CRM Sync

Business Outcomes

Unified Customer/Member profiles index generated, resolving duplicate records and increasing branch cross-sell conversions by 24%.

Customer 360 for Insurance

Problem Statement

Insurers struggle to evaluate premium values per family because policyholder profiles across life, home, and auto are isolated.

Artha Solution

Unify policyholder details and aggregate accounts into single profiles to track total customer/household premiums.

Data Domains Involved

Policyholder profiles, auto logs, home policy lists, health registries

Technology Stack

MDM, Hierarchy Management, Lakehouse Integration

Business Outcomes

Complete household premium index established, reducing renewal drop-offs and facilitating targeted bundle offers.

Policyholder 360

Problem Statement

Insurance customer service agents operate without unified records, forcing callers to repeat details across policy lines.

Artha Solution

Consolidate policyholder personal details, claims histories, and active contract terms into single dashboard data feeds.

Data Domains Involved

Policyholder records, premium billing tables, active policy registers

Technology Stack

MDM, Data Integration, CRM API

Business Outcomes

Average call resolution time cut by 40%, elevating customer experience rankings and service scores.

Account and Relationship Data Foundation

Problem Statement

Corporate relationship managers cannot track total risk exposure because joint account owners and business guarantors are unlinked.

Artha Solution

Design a graph-like data structure that links personal accounts, joint owners, company directors, and guarantors.

Data Domains Involved

Corporate account books, personal credit records, loan covenants

Technology Stack

MDM, Relationship Mappings, Graph Database Schema

Business Outcomes

Enabled real-time corporate relationship mapping, avoiding double-crediting risks to high-exposure guarantors.

KYC and Entity Data Quality

Problem Statement

AML and KYC screening checks trigger high false alarm rates because entity names are formatted inconsistently.

Artha Solution

Implement automated data standardization, parsing, and quality rules to clean entity profiles before screening.

Data Domains Involved

KYC verification logs, entity name registries, transaction lists

Technology Stack

Data Quality Profiling, Standardization, Ingestion Filters

Business Outcomes

KYC false alarm rates cut by 35%, accelerating onboarding queues and lowering compliance costs.

Fraud Analytics Data Foundation

Problem Statement

Fraud detection algorithms miss transaction anomalies because debit card swipes, mobile transfers, and ATM logs are delayed.

Artha Solution

Deploy CDC event pipelines to stream card and bank transactions directly into a low-latency analytics lakehouse.

Data Domains Involved

Real-time card swipes, mobile transfer logs, ATM registers

Technology Stack

CDC Ingestion, Real-Time Streams, Cloud Lakehouse

Business Outcomes

Transaction monitoring latency cut from days to milliseconds, allowing immediate card blocking on fraudulent activities.

Credit Risk Data Readiness

Problem Statement

Lenders credit risk scoring engines operate on outdated, delayed customer records, resulting in bad debt write-offs.

Artha Solution

Consolidate loan performance histories, transaction counts, and external ratings into structured credit risk data profiles.

Data Domains Involved

Lending books, current account logs, historical credit grades

Technology Stack

Data Integration, Data Warehouse, Risk Analytics

Business Outcomes

Credit scoring profiles refreshed hourly instead of monthly, lowering loan default rates and optimizing margins.

Claims Analytics Data Foundation

Problem Statement

Insurers suffer high claims leakages because claims logs, assessor reports, and policy details are disconnected.

Artha Solution

Consolidate claims reports, active policies, and repair histories into a central claims lakehouse platform.

Data Domains Involved

Claims files, assessor reports, policy registers

Technology Stack

Data Lakehouse, Analytics, Data Integration

Business Outcomes

Facilitated automated claims fraud flags and accelerated claims processing times by 30%.

Regulatory Reporting Data Readiness

Problem Statement

Compiling Basel, CCAR, or IFRS reports requires weeks of manual data sourcing, lineage tracing, and balancing.

Artha Solution

Map system-to-report lineage pipelines and build pre-balanced datasets matching regulatory templates.

Data Domains Involved

Transaction registers, general ledger records, metadata mappings

Technology Stack

Data Lineage, Compliance Architecture, Data Quality

Business Outcomes

Report prep times reduced from weeks to days, and audit validation questions resolved instantly.

Finance and Risk Data Reconciliation

Problem Statement

Finance ledger counts and risk portfolio reports differ at the end of the month, triggering manual reconciliation overhead.

Artha Solution

Establish automated reconciliation rules and metadata catalog bridges to align ledger calculations with risk metrics.

Data Domains Involved

General ledger entries, credit portfolio listings, metadata definitions

Technology Stack

Data Reconciliation, Data Catalog, Governance

Business Outcomes

Manual ledger-to-risk reconciliation audits cut by 85%, accelerating monthly balance sheet closures.

Customer Churn Analytics

Problem Statement

Wealth and banking platforms lose premium customers because account activity dips and service requests are unlinked.

Artha Solution

Connect client app engagement, balance trends, and support logs to flag drop-off risk patterns.

Data Domains Involved

Mobile app transactions, service logs, account balances

Technology Stack

Data Integration, Analytics, Churn Modeling

Business Outcomes

Client retention increased by 18% through early alert dashboards that prompt account reviews.

Next-Best-Action Data Foundation

Problem Statement

Marketing personalization models suggest irrelevant offers because customer portfolios and transactions are siloed.

Artha Solution

Unify customer account records, recent transaction history, and digital clicks into a real-time feature store.

Data Domains Involved

Customer transaction details, web portal clicks, active credit card registries

Technology Stack

Feature Store, Data Integration, Personalization Data

Business Outcomes

Credit card and deposit cross-sell response rates doubled after personalization engines referenced unified logs.

Payments and Transaction Analytics

Problem Statement

Fintech firms cannot trace payments failure root causes because transaction records are scattered across processing portals.

Artha Solution

Consolidate payment transaction logs, settlement directories, and system errors into a real-time lakehouse dashboard.

Data Domains Involved

Processing portal logs, bank settlement files, card transaction registries

Technology Stack

Data Lakehouse, Analytics, Data Integration

Business Outcomes

Payment error resolution times cut by 50%, elevating platform transaction success metrics.

Lending Portfolio Analytics

Problem Statement

Credit leaders struggle to monitor loan risks because portfolios are managed across disconnected legacy applications.

Artha Solution

Unify credit books and rating metrics to deploy real-time portfolio dashboards.

Data Domains Involved

Lending account directories, payment logs, rating database lines

Technology Stack

Data Warehouse, BI dashboards, Data Integration

Business Outcomes

Enabled real-time tracking of non-performing loans (NPL), protecting capital reserves.

Branch and Digital Channel Analytics

Problem Statement

Retail banking executives cannot compare branch staffing efficiency with online app customer interactions.

Artha Solution

Link physical branch logs with digital portal events to compare omnichannel cost-to-serve metrics.

Data Domains Involved

Branch wait times, digital transaction volumes, support ticket counts

Technology Stack

Data Integration, Analytics, Omnichannel BI

Business Outcomes

Optimized branch staffing schedules and app workflow paths, saving operational budgets.

Data Governance for BFSI

Problem Statement

Wealth firms risk regulatory fines because sensitive customer assets and balances lack clear owners and lineage records.

Artha Solution

Establish metadata glossaries, assign data owners, and deploy catalog lineage scanners.

Data Domains Involved

Sensitive balance tables, customer directories, lineage traces

Technology Stack

Data Governance, Metadata Catalog, Lineage scanner

Business Outcomes

Established clear data ownership rules, reducing regulatory audit compliance risks.

AI-Ready BFSI Data Products

Problem Statement

Lending data scientists waste weeks cleaning raw card swipes and credit logs to train fraud predictive models.

Artha Solution

Publish governed, cataloged "data products" (e.g. Validated Payments) with documented schema and SLA logs.

Data Domains Involved

Structured balance sheets, clean payment logs, cataloged credit scores

Technology Stack

Feature Store, Data Product Catalogs, Governance

Business Outcomes

Fraud model training time cut from weeks to hours, accelerating fraud mitigation model deployments.

Cloud Data Platform Modernization

Problem Statement

Legacy banking database clusters cannot handle high query loads, slowing down analytics and credit assessments.

Artha Solution

Consolidate core account and transaction registries into a scalable cloud data lakehouse architecture.

Data Domains Involved

Historical account logs, legacy tables, reporting schemas

Technology Stack

Cloud data warehouse, Snowflake, Databricks, ETL Modernization

Business Outcomes

Credit reporting query speeds improved by 10x, supporting real-time lending decisions.

Legacy ETL Modernization

Problem Statement

Complex legacy ETL code is slow and expensive to maintain, stalling updates to credit risk models.

Artha Solution

Convert outdated ETL mappings into cloud-native ELT pipelines and SQL automation procedures.

Data Domains Involved

Legacy ETL scripts, database jobs, target databases

Technology Stack

ETL Modernization, SQL automation, Cloud Data Platform

Business Outcomes

Nightly batch load window cut by 60%, saving licensing overhead and server capacity.

Data Quality and Observability

Problem Statement

Corrupted ledger files or missing transaction events are only spotted after reports break, delaying regulatory filings.

Artha Solution

Implement automated data profiling, database row validation, and schema alerts on transaction pipelines.

Data Domains Involved

Schema validation parameters, database row counts, pipeline alert states

Technology Stack

Data Quality, Observability, Pipeline Alerts

Business Outcomes

Slashed ledger data errors, protecting compliance schedules and reporting accuracy.