Data Fabric The Future of Invisible Banking and Seamless Financial Services

With the power of data fabric Platform, banks and financial institutions can deliver personalized, relevant, and timely services to their customers, enhancing the overall customer experience and creating a competitive edge

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Transform Commercial Banking

Data-Driven Insights and Efficient Processes

The surge in information availability is remarkable. In recent years, there has been an exponential increase in the quantity of significant data - true signals, not just data – This is true for all industries and not just banking. This is how this is going to change banking we experience today.

work process
  • Data-Driven Insights

    Leveraging the rich data within our bank, we strive to create information that helps client relationship managers anticipate their clients' needs, resulting in enhanced relationship-driven commercial banking. The focus is on addressing clients' strategic needs and demonstrating our understanding of their strategies.

  • Collaborative Product Creation

    By involving our clients in the product development process, we aim to create tailored products and services that align with their unique needs and goals. Our bankers are equipped with insights from data analysis to facilitate these conversations.

  • Efficiency through Streamlining and Automation

    To improve the speed and simplicity of our processes, we focus on streamlining and automating certain aspects of commercial banking. This saves our bankers valuable time and enables them to focus on higher-value activities.

  • Empowering the Banking Experience

    We aim to empower our bankers by providing them with easy access to the knowledge and insights they need to excel in their role. A structured content management system is in place to unlock the bank's vast knowledge stores.

Charting the Future of Banking

How Data Management is Transforming Key Operational Trends

The banking industry is undergoing a profound transformation, fueled by evolving customer expectations, disruptive technologies, and the need for greater efficiency in an increasingly competitive environment. As we look towards the future of banking operations, it is crucial to recognize the key trends and changes that will shape the way financial institutions conduct business. These trends will not only redefine the operational landscape of the banking industry but also reshape the experiences of customers and employees alike, ushering in a new era of innovation and growth in the world of finance and Banking

Distinctive, Personalized Products and Services

  • Banks will shift from offering standardized products to providing customized solutions that cater to their customers' specific needs.
  • Operations staff will focus on product development and use automated systems to manage customized products and services.
  • An example of a personalized product could be a credit card where the card member can define the rewards points they receive.
  • Another example could be a loan that allows customers to specify their repayment plan and due dates.

Extensive Use of Automation and New Technologies

  • Automation and artificial intelligence (AI) will become even more prevalent in banking operations, delivering benefits to both the bank and its customers.
  • Digitizing the loan-closing process and using AI-powered customer service will make banking faster and more efficient.
  • Advanced analytics could improve dispute resolution, allowing customers to receive quick and real-time decisions

Analytics-driven Proactive Management

  • Predictive analytics will enable operations leaders to make precise and accurate predictions about customer behavior and needs.
  • Banks can use comprehensive data sets to set KPIs and understand customer behavior.
  • Analytics can transform issue resolution, making it proactive and increasing customer satisfaction.

Seamless Processes and Consistent Quality

  • Automating operations will reduce human bias and lower errors, freeing up employees to handle complex or sensitive issues that can't be addressed through automation.
  • Operations employees will have the authority and skills to resolve customer issues quickly.

Eliminating Siloes for a Simpler Organization

  • The traditional trinity of front offices, middle offices, and back offices will evolve, with back offices slimming down and call centers all but disappearing.
  • Front-line branch employees will operate as personal advisors for complex questions that can't be addressed digitally.

Use Case

Data Science Use Cases in
Banking & Finance

The banking and finance sector is at the forefront of digital transformation, with data science playing a pivotal role in reshaping its landscape. As financial institutions continue to embrace advanced analytics and machine learning, they are uncovering new opportunities to enhance operational efficiency, mitigate risk, and deliver personalized customer experiences. The global market for data science in the banking and finance industry is projected to reach $43.1 billion by 2027, a testament to the growing adoption of data-driven solutions in this sector. There are various data science use cases that are revolutionizing banking and finance, demonstrating how SCIKIQ Data fabric is transforming traditional business models and driving growth in an increasingly competitive Market


Auto-Commentary Tool


Natural Language, Data Platfrom and Architecture


Build an Auto Commentary Tool which takes data from Oracle GL/SAP to generate Commentary Packs for CFO reporting. This tool leveraged the power of Natural Language Text Processing and some pre-configured rule-based transformations to generate Balance Sheet and PnL Reports. This solution was initially tested on Management Hierarchy and then rolled out to Legal and Tax Hierarchy to provide actionable insights by integrating advanced analytical models to analyze balance sheet and PnL account lines. Even the account level ownership was mapped so that the system can trigger messages to account owner in case of variances

Auto Match Tool

Regex, Patterns, ML, Data Platfrom and Architecture

Increase operational efficiencies by reducing FTE footprint associated with manual matching of the Open Items. By implementing a matching and reconciliation tool, bank was able to match 80-90% of the items, however, due to high trade and payment volumes, the 10-20% open items became unmanageable and FTE intensive.AI/ML based solution which takes open items report from GL. The tool then runs these open items through battery of ML models to perform Exact, Tolerance and Aggregate Match i.e. 1 to many matches. The rules were tested for repeatability and accuracy which were further validated by business SME.

Accounting Hub Design

Design , Architecture, KAFKA and Data Model

Due to increased Trade Volume, the Danish bank wants to build Accounting Hub, which is responsible for creating Accounting entries and post information to Data Warehouse and ERP. It needs to ingest data from Customer, Trade and other operational systems. We helped with the design, analysis and build of the accounting hub which is scalable and meet functional requirements of end users:

Data Analysis
Source to Target Mapping
Creation of Logical and Physical Data Model
Setup Data Governance Principles for data flow
Define Data Quality Framework and measures
Define Meta Data Management Framework
Provisioning and Authoritative Source with the help of technology on a robust governed platform
Operating model setup for smooth BAU governance of all data assets
Data Architecture and Data Flow

Delivered and Implemented Data Strategy for German arm of a UK bank

Data Strategy and Implementation

Regulatory pressures dictated that the overall data strategy of the bank be reviewed. Each division was required to be compliant to Data governance standards and policies set across the bank while ensuring they had a full view of their data assets.

Approach: An end-to-end engagement revolving around setup of a CDO function from scratch. This included:
Creation of a metadata repository with requisite workflows
Identifying critical data elements and establishing ownership
Lineage for key regulatory reports
Data Quality Controls and Measures definition and implementation
Provisioning and Authoritative Source with the help of technology on a robust governed platform
Operating model setup for smooth BAU governance of all data assets

Design of Data Flow for Intercompany process for Tier 1 Bank

Arcitecture, Design and Data Model

Delivered the full data flow and Information architecture for Intercompany process for tier-1 Bank

Integrated Marketing & Sales Platform

Arcitecture, Design and Data Model

Add value to customers in all their interactions, by understanding and meeting their needs through our products, processes and services, making it easier and more rewarding for them to do business with us, our agents and our partner network, to the benefit of the customers and for our increased profit.

Account Payable Automation

OCR, AI and ML

Challenge: Manual Processes and lack of standardisation in Invoice Processing causes delay in the payout and leading to deployment of 100+ Operation Support staff to process these invoices/cheques

Approach: Open Source based OCR solution was created so that it can extract information from the invoices and the cheques - hence automate and streamline the processes along with leading to reduction of Operation staff requirement to process the same.

Automation of US Tax Form

OCR, AI and ML

Challenge: Challenge: Retrieve information from US Tax document and automate the capture and review process.

Approach: Open Source based OCR/OMR solution was build to extract data from US Tax document. The extracted data was then posted into their front-end system and Excel Spreadsheet for downstream consumption.

Data Validation across KYC and Form

OCR, AI and ML

Challenge:Retrieve information from account opening form and KYC document provided. Validate the documents provided by matching information in Account Opening form and KYC. Validate KYC by linking the CKYC database and in case CKYC doesn’t exist create a new CKYC.

Approach: Open Source based OCR solution build to extract data from account opening form, and KYC documents such as Addhar, Passport and PAN card. The data extracted is stored in a database and matched for fields like Name, Date of birth, Address across 3 documents. In case any of the fields / photo doesn’t match a error is generated for a physical review screen build on Django. If validation is successful the PAN is validated / updated in CKYC database.