Digitalization in Finance
Plan, Costs, Techs, Skills
Since 2007, ScienceSoft has been helping companies digitally transform and innovate their financial management processes.
Digitalization in Finance: Summary
Digitalization in finance aims to innovate the corporate finance processes with the help of modern tools and advanced technologies. It allows companies to automate up to 90% of finance-related tasks and, thus, drive significant time and cost savings and improvements in financial data accuracy.
|
|
|
|
|
Key project steps: business analysis and requirements engineering, finance digitalization planning, a feasibility study, PoC development, modernization of the existing financial software and IT infrastructure, developing new financial solutions, integration, quality assurance, and user training. Timelines: 15–30 months on average. Cost: $700K–$5M+, depending on the project complexity. Team: a business analyst/a digital transformation consultant, a project manager, a solution architect, a UX/UI designer, a DevOps engineer, a front-end developer, a back-end developer, a data scientist, a QA engineer. |
|
|
|
Having deep expertise in large-scale digitalization projects for Fortune 500 businesses, ScienceSoft knows for sure how to help companies reimagine and smoothly transform their financial management processes.
Accounting
Automate up to 90% of accounting-related routine, boost the team’s productivity by 80%+, and make the accounting process up to 25x faster. Harness the power of blockchain to get an immutable record of all financial transactions and ensure world-class security of your data.
Billing and invoicing
Drive up to 90% cost savings per invoice due to fully automated invoice generation and processing. Get end-to-end visibility of the due and received payments to timely trigger collection procedures, achieve up to 2x reduction in DSO, and prevent revenue leakage.
Revenue management
Enjoy automated revenue reconciliation and simplify revenue recognition compliance with up-to-date accounting standards (ASC 606, IFRS 15, etc.).
Tax management
Avoid the risk of penalties with full automation of your tax-related activities: from tax calculation and payment to tax filing and submission.
Treasury
Enhance the team’s productivity by 75%+ due to automated aggregation and processing of treasury transactions. Get real-time view of all operational, investment, and financing activities. Reduce the idle cash by up to 50% and ensure high-ROI investments with minimized financial risks due to AI-based guidance on optimal treasury-related decisions.
Financial planning and analysis
Turn your corporate finance into a value driver for the entire business with the paramount capabilities of AI-based big data analytics. Analyze and model finance up to 100x faster, forecast financial outcomes with 90%+ accuracy, and increase the company’s overall profitability with data-driven decisions on financial and strategic transactions.
A Roadmap to the Successful Digital Transformation of Finance
Below, ScienceSoft describes the key steps of a digitalization project and shares best practices to maximize ROI from the financial management revamp. Note that our roadmap is not a go-to action plan: in our projects, we always design an individual digitalization strategy and a launch a tailored plan for each client.
To plan the digitalization of finance with full insight into the client’s financial management pains and needs, ScienceSoft’s consultants:
- Examine the client’s overall business situation and strategic business goals.
- Analyze the client’s financial management, incl. in the context of other business processes (e.g., HR management, operations management, supply chain management).
- Conduct a SWOT analysis of the existing financial software.
- Assess the complexity of the financial analytics the company currently relies on.
- Analyze the regulatory requirements, e.g., GAAP (specifically ASC 606 and IFRS 15), SOC1 and SOC2, SOX, PCI DSS, GDPR (for the EU), ZATCA regulations (for Saudi Arabia), and more.
Based on the analysis results, we introduce a detailed requirements specification for the financial management digitalization, which comprises:
- The finance areas that digital transformation should cover.
- Requirements for the modification of the existing financial software (if applicable), for example, migration to the cloud, rearchitecting or refactoring.
- Requirements for the functional capabilities that new corporate finance software should provide.
- Non-functional requirements for the digital finance solution: performance, availability, scalability, security, etc.
- The types of data the software should be able to process (financial data, asset-related data, supplier and customer data, etc.).
- Role-specific requirements for the UX and UI.
ScienceSoft
At this stage, ScienceSoft’s team forms a high-level vision of your corporate finance digitalization and introduces a detailed action plan to turn the digitalization initiatives into reality. It includes:
1. Determining long-term digitalization goals and short-term objectives.
2. Creating a custom digital transformation strategy with a company’s financial management goals in mind.
3. Designing the new financial software and/or redesigning the existing financial solutions. This step may include:
- Feature road-mapping – preparing a detailed list of features for the digital finance solution and prioritizing them based on the cost-benefit analysis.
-
Architecture (re)design – designing a secure, scalable, high-performing architecture for the corporate finance solution.
-
Integrations planning – preparing a plan of financial software integrations with relevant corporate solutions (e.g., operations management software, HRMS, vendor portal, asset management software) and external systems (bank accounts, financial data marketplaces, etc.).
-
UX and UI (re)design – designing role-specific UX and UI (e.g., for accountants, treasurers, financial data analysts, etc.) and introducing UI mock-ups.
4. Selecting the proper tech stack.
ScienceSoft’s best practice: In our projects, we employ proven frameworks, ready-to-use app components (e.g., authentication services, messaging services) and integration components (banking APIs, financial data APIs) where possible. This helps us streamline financial software development, ensure high quality of the solution, and optimize the project budget.
5. Planning the project deliverables, timelines, budget, team, KPIs.
6. Introducing a risk mitigation plan that covers such risks as operational complexity, financial data leakage, non-compliance with sectoral regulations, project cost and time overruns.
User adoption remains the key factor defining the success of digital transformation. ScienceSoft takes great care of encouraging your team to shift to the new tech-driven workflows. Already at the planning stage, we prioritize the initiatives that bring prompt and clear improvements to the regular finance-related tasks, thus showing the innovations in an appealing light.
ScienceSoft estimates the TCO and ROI for each digitalization initiative and analyzes the economic feasibility of transformations. Additionally, we can develop a proof of concept to assess the viability of an innovative finance solution.
ScienceSoft
At this stage, ScienceSoft’s team gradually implements the planned initiatives. Particularly, we may:
- Advance the existing IT infrastructure:
- Perform cloud migration.
- Establish cloud automation, CI/CD pipelines, and container orchestration.
- Implement modern infrastructure security mechanisms, e.g., AI-powered XDR and deception tools.
- Develop new corporate finance software and/or modernize the existing financial management solutions.
ScienceSoft’s best practice: We develop financial software iteratively to introduce the fundamental functions first and drive faster payback from digitalization.
- Run quality assurance procedures in parallel with development and fix the discovered defects.
- Deploy financial software to the production environment.
- Integrate the software with the required internal and third-party systems.
- Introduce financial analytics (this may require designing, training, and tuning data analytics models).
- Implement security policies, procedures, and controls.
Additionally, we can provide after-launch support of the delivered financial software and upgrade it with new functionality when needed.
Due to being complex and long-running, finance digitalization projects demand flexibility. For example, it may turn out that the digitalization strategy requires some tuning at the implementation stage due to the altering business situation. When this happens, we help our clients promptly tune the strategy and the implementation plan without causing any negative impact on the project flow and the outcomes.
ScienceSoft
Upon the implementation of each particular digitalization initiative, ScienceSoft designs a dedicated training program and conducts user training in a convenient format. This helps the finance team quickly learn how to apply the innovations and improve their daily operations.
In addition, we draw up user manuals and self-training materials and share them with the client’s IT team.
ScienceSoft
Consulting on digitalization in finance
We create a digitalization strategy aligned with your ambitious financial management goals and advise on the best-fitting advanced techs to power your corporate finance. We also deliver a detailed digital transformation roadmap with cost and time estimates and a comprehensive risk mitigation plan.
You benefit from risk-free finance digitalization, optimized project cost and timelines.
Implementing the finance digitalization
Digital transformation doesn’t have to be a years-long headache. We design a finance digitalization strategy and roadmap, modernize your existing financial tools, implement the new corporate finance techs you need, and conduct user training to take the finance innovation burden off your shoulders.
You benefit from prompt finance digitalization, topflight quality of financial software, high user adoption.
Why Trust ScienceSoft
|
|
|
Our Customers Say
Owing to ScienceSoft’s experience in distributed modular systems, we cooperated with them on the evolution of our Azure-based product for accounts payable management. ScienceSoft was to cover end-to-end development of an intelligent paperless invoice processing module for the product.
The new software module performs stably even under heavy load, which helps provide a high-quality user experience for our customers. ScienceSoft proved to be a reliable tech partner.
Wadih Pazos, Chief Operating Officer, Paramount WorkPlace
Business Analyst/Digital Transformation Consultant
Analyzes the current business situation and corporate finance processes, sets up and prioritizes digitalization goals, creates a custom digital transformation strategy.
Project Manager
Plans the project (goals, timeline, budget), coordinates the project team(s), prioritizes the scope of work and monitors its execution, reports the progress to the stakeholders.
Solution Architect
Designs the architecture of the finance IT ecosystem and specific solutions, including integration points with the required systems. Re-designs the architecture of the existing financial software (for modernization).
UX/UI Designer
Designs the role-specific UX and UI of financial applications.
DevOps Engineer
Configures the IT automation environment (container orchestration, CI/CD pipelines, cloud automation, etc.).
Front-end Developer
Delivers the UI of financial software and fixes the defects reported by QA engineers.
Back-end Developer
Delivers the server-side code of financial software (including APIs), establishes the required integrations, and fixes the defects reported by QA engineers.
Data Scientist
Designs financial analytics models powered with ML.
QA Engineer
Creates a test strategy, a test plan, and test scenarios to perform functional and non-functional testing. Reports the detected defects and validates the fixes.
|
|
|
|
|
NB! Depending on the project specifics, ScienceSoft can involve additional talents, for example, blockchain developers to build blockchain-based financial software. |
|
|
|
|
|
|
|
|
NB! Depending on the client’s needs, ScienceSoft can:
|
|
|
|
A Featured Success Story by ScienceSoft
Digital Transformation of Finance for a Large Mobile Operator
ScienceSoft helped a telecom provider with 5M clients digitally transform their invoicing and debt collection processes. Particularly, our team:
- Brought together the functions of 21 existing invoice-related tools in one solution, optimizing the number of scripts and the code quality.
- Designed and developed a new invoicing solution that enables automated generation of customer invoices, designing custom invoice templates, invoice e-signing, and more.
- Delivered custom debtor management software that automates debt collection procedures and integrated the solution with the customer’s accounting system.
Customer’s benefit: 24x faster invoice processing, more than 3x faster monthly billing campaigns, 100x lower invoicing software maintenance costs, significant increase in debtor management capacity.
ScienceSoft’s Tech Stack for Finance Digitalization
To deliver effective digital financial management solutions, ScienceSoft relies on a range of robust technologies and tools, including:
Programming languages
Back end
Practice
19 years
Projects
200+
Workforce
60+
Our .NET developers can build sustainable and high-performing apps up to 2x faster due to outstanding .NET proficiency and high productivity.
Practice
25 years
Projects
110+
Workforce
40+
ScienceSoft's Java developers build secure, resilient and efficient cloud-native and cloud-only software of any complexity and successfully modernize legacy software solutions.
Practice
10 years
Projects
50+
Workforce
30
ScienceSoft's Python developers and data scientists excel at building general-purpose Python apps, big data and IoT platforms, AI and ML-based apps, and BI solutions.
Practice
10 years
Workforce
100
ScienceSoft delivers cloud-native, real-time web and mobile apps, web servers, and custom APIs ~1.5–2x faster than other software developers.
Practice
16 years
Projects
170
Workforce
55
ScienceSoft's PHP developers helped to build Viber. Their recent projects: an IoT fleet management solution used by 2,000+ corporate clients and an award-winning remote patient monitoring solution.
Practice
4 years
ScienceSoft's developers use Go to build robust cloud-native, microservices-based applications that leverage advanced techs — IoT, big data, AI, ML, blockchain.
Front end
Practice
21 years
Projects
2,200+
Workforce
50+
ScienceSoft uses JavaScript’s versatile ecosystem of frameworks to create dynamic and interactive user experience in web and mobile apps.
Front end Javascript frameworks
Practice
13 years
Workforce
100+
ScienceSoft leverages code reusability Angular is notable for to create large-scale apps. We chose Angular for a banking app with 3M+ users.
Workforce
80+
ScienceSoft achieves 20–50% faster React development and 50–90% fewer front-end performance issues due to smart implementation of reusable components and strict adherence to coding best practices.
ScienceSoft uses Meteor for rapid full-stack development of web, mobile and desktop apps.
By using a lightweight Vue framework, ScienceSoft creates high-performant apps with real-time rendering.
With Next.js, ScienceSoft creates SEO-friendly apps and achieves the fastest performance for apps with decoupled architecture.
When working with Ember.js, ScienceSoft creates reusable components to speed up development and avoid code redundancy.
Mobile
Practice
16 years
Projects
150+
Workforce
50+
ScienceSoft’s achieves 20–50% cost reduction for iOS projects due to excellent self-management and Agile skills of the team. The quality is never compromised — our iOS apps are highly rated.
Practice
14 years
Projects
200+
Workforce
50+
There are award-winning Android apps in ScienceSoft’s portfolio. Among the most prominent projects is the 5-year-long development of Viber, a messaging and VoIP app for 1.8B users.
Practice
11 years
Projects
85+
Workforce
10+
ScienceSoft cuts the cost of mobile projects twice by building functional and user-friendly cross-platform apps with Xamarin.
ScienceSoft uses Cordova to create cross-platform apps and avoid high project costs that may come with native mobile development.
ScienceSoft takes the best from native mobile and web apps and creates the ultimate user experience in PWA.
Practice
8 years
Projects
300+
ScienceSoft reduces up to 50% of project costs and time by creating cross-platform apps that run smoothly on web, Android and iOS.
ScienceSoft will save you from double or even triple expenses associated with platform-specific coding by creating cross-platform apps in Flutter.
With Ionic, ScienceSoft creates a single app codebase for web and mobile platforms and thus expands the audience of created apps to billions of users at the best cost.
Desktop
Practice
34 years
Workforce
40
ScienceSoft's C++ developers created the desktop version of Viber and an award-winning imaging application for a global leader in image processing.
Practice
4 years
Workforce
40
We used Qt to deliver a cross-platform desktop app for a global leader in image processing, a desktop version of Viber, VoIP messenger with over 1 billion users, and an anti-procrastination app acknowledged by The Daily Telegraph and BBC.
Practice
19 years
Projects
200+
Workforce
60
Our C# developers created the world’s largest PLM software. Their recent projects: development of SaaS for vCIO services management and underwriting software for a global aviation insurer.
Practice
15 years
Workforce
~40
We have delivered WPF-based solutions for a leading market research company and a global leader in image processing.
We use Objective-C to implement native macOS features in desktop apps.
Practice
10 years
Workforce
30
We use Python for rapid development of cross-platform desktop apps.
Databases / data storages
SQL
Our Microsoft SQL Server-based projects include a BI solution for 200 healthcare centers, the world’s largest PLM software, and an automated underwriting system for the global commercial insurance carrier.
We’ve implemented MySQL for Viber, an instant messenger with 1B+ users, and an award-winning remote patient monitoring software.
Azure SQL Database is great for handling large volumes of data and varying database traffic: it easily scales up and down without any downtime or disruption to the applications. It also offers automatic backups and point-in-time recoveries to protect databases from accidental corruption or deletion.
ScienceSoft's team has implemented Oracle for software products used by GSK and AstraZeneca. We’ve also delivered Oracle-based SCM platform for Auchan, a retail chain with 1,700 stores.
ScienceSoft has used PostgreSQL in an IoT fleet management solution that supports 2,000+ customers with 26,500+ IoT devices. We’ve also helped a fintech startup promptly launch a top-flight BNPL product based on PostgreSQL.
NoSQL
Our Apache Cassandra consultants helped a leading Internet of Vehicles company enhance their big data solution that analyzes IoT data from 600,000 vehicles.
ScienceSoft has helped one of the top market research companies migrate its big data solution for advertising channel analysis to Apache Hive. Together with other improvements, this led to 100x faster data processing.
We use HBase if your database should scale to billions of rows and millions of columns while maintaining constant write and read performance.
With ScienceSoft’s managed IT support for Apache NiFi, an American biotechnology corporation got 10x faster big data processing, and its software stability increased from 50% to 99%.
ScienceSoft used MongoDB-based warehouse for an IoT solution that processed 30K+ events/per second from 1M devices. We’ve also delivered MongoDB-based operations management software for a pharma manufacturer.
Cloud databases, warehouses and storage
AWS
We use Amazon Redshift to build cost-effective data warehouses that easily handle complex queries and large amounts of data.
We use Amazon DynamoDB as a NoSQL database service for solutions that require low latency, high scalability and always available data.
Azure
We leverage Azure Cosmos DB to implement a multi-model, globally distributed, elastic NoSQL database on the cloud. Our team used Cosmos DB in a connected car solution for one of the world’s technology leaders.
Azure SQL Database is great for handling large volumes of data and varying database traffic: it easily scales up and down without any downtime or disruption to the applications. It also offers automatic backups and point-in-time recoveries to protect databases from accidental corruption or deletion.
Google Cloud Platform
We use Google Cloud Datastore to set up a highly scalable and cost-effective solution for storing and managing NoSQL data structures. This database can be easily integrated with other Google Cloud services (BigQuery, Kubernetes, and many more).
Big data
By request of a leading market research company, we have built a Hadoop-based big data solution for monitoring and analyzing advertising channels in 10+ countries.
A large US-based jewelry manufacturer and retailer relies on ETL pipelines built by ScienceSoft’s Spark developers.
Our Apache Cassandra consultants helped a leading Internet of Vehicles company enhance their big data solution that analyzes IoT data from 600,000 vehicles.
We use Kafka for handling big data streams. In our IoT pet tracking solution, Kafka processes 30,000+ events per second from 1 million devices.
ScienceSoft has helped one of the top market research companies migrate its big data solution for advertising channel analysis to Apache Hive. Together with other improvements, this led to 100x faster data processing.
We leverage Apache ZooKeeper to coordinate services in large-scale distributed systems and avoid server crashes, performance and partitioning issues.
We use HBase if your database should scale to billions of rows and millions of columns while maintaining constant write and read performance.
We leverage Azure Cosmos DB to implement a multi-model, globally distributed, elastic NoSQL database on the cloud. Our team used Cosmos DB in a connected car solution for one of the world’s technology leaders.
We use Amazon Redshift to build cost-effective data warehouses that easily handle complex queries and large amounts of data.
We use Amazon DynamoDB as a NoSQL database service for solutions that require low latency, high scalability and always available data.
ScienceSoft used MongoDB-based warehouse for an IoT solution that processed 30K+ events/per second from 1M devices. We’ve also delivered MongoDB-based operations management software for a pharma manufacturer.
We use Google Cloud Datastore to set up a highly scalable and cost-effective solution for storing and managing NoSQL data structures. This database can be easily integrated with other Google Cloud services (BigQuery, Kubernetes, and many more).
AI
Machine learning platforms and services
Machine learning frameworks and libraries
Platforms
Practice
14 years
Projects
25+
Workforce
10+
A certified Microsoft partner, ScienceSoft creates CRM and ERP solutions powered by Dynamics 365 and optimizes most effectively a range of business operations.
Projects
10+
ScienceSoft achieves at least 20% increase in sales and 30% improvement in case resolution with well-thought-out and business-tailored Salesforce solutions.
Practice
11 years
Projects
20+
Workforce
10+
A certified Adobe Solution Partner, ScienceSoft builds on robust functionality of Adobe Commerce to create highly automated and scalable ecommerce solutions.
Practice
15 years
Projects
100+
Workforce
20+
Solid expertise in SharePoint services has earned ScienceSoft a place in Clutch’s list of Top SharePoint Developers in 2023.
Practice
12 years
A certified ServiceNow partner, ScienceSoft offers a proprietary 4-level implementation model that helps deliver the best value from ServiceNow adoption.
Practice
7 years
ScienceSoft sets up Power BI to process data from any source and report on data findings in a user-friendly format.
SAP products are powerful and intricate. ScienceSoft will help you understand and realize the full value they can offer to your business.
DevOps
Containerization
Automation
CI/CD tools
Monitoring
Blockchain
Smart contract programming languages
Frameworks and networks
Cloud services
Cost Factors of Digital Transformation in Finance
The general factors that affect the cost and duration of the finance digitalization projects are:
- The number and specifics of corporate finance areas to digitalize.
- The possibility to reuse the existing financial software and infrastructure components.
- Requirements for the evolution of the existing software.
- The functional complexity of new financial software, including the implementation of advanced features (e.g., AI-powered financial analytics, blockchain-based bookkeeping).
- Performance, availability, scalability, security requirements.
- The number and complexity of integrations between the financial software and the required systems.
- The number of user roles for the digital finance system and the role-specific requirements for UX/UI design.
- Regulatory compliance requirements.
- The chosen sourcing model.
Here are sample costs for the finance digitalization projects:
$700K–$5M
Corporate finance digitalization for an upper midsize company.
$5M+
Finance digital transformation for a large multi-entity enterprise.
About ScienceSoft
ScienceSoft is a global IT consulting and software development company headquartered in McKinney, Texas. We provide end-to-end digital transformation services to help companies innovate their financial management processes with the help of robust digital tools and cutting-edge technologies. In our digital transformation projects, we employ mature quality management and data security management systems backed by ISO 9001 and ISO 27001 certifications.