“Intelligence is the ability to adapt to change.” – Stephen Hawking

How did David emerge victorious in the battle with Goliath? With a slingshot. From the five stones he had picked up for the battle, David just needed one stone to defeat the giant (Book of Samuel, Old Testament). While much has been written about his intelligence and valor, his aim streamlined and precise was just as important in ensuring Goliath’s defeat. From a purely technical standpoint, since we are in the technology and data business, had David been late by a split second, or had his aim not been streamlined or precise, the story of David and Goliath would have had a different ending.

Similarly, in financial and capital markets, there is a lot that can be achieved (or lost) when processes are not streamlined, particularly in critical areas like invoice processing. Just as David’s perfectly timed and streamlined shot delivered maximum impact, a streamlined invoice processing mechanism shields organizations from irritants such as delays, errors, and penalties, and future proofs them from disruptions and missed opportunities.

Understanding the Essence of Invoice Processing

In simplest terms, invoice processing is defined as the series of steps that takes place right from the time when the supplier invoice is received to the time when it is paid and recorded in the general ledger. The invoice can be received via mail, or as a PDF attached to an email, or as an e-invoice. Whatever the format, the invoice must be manually/automatically scanned into the accounting system, digitized, ETL performed, data validated, and later inserted in the workflow approval and payment system.

Why Manual Invoice Processing is No Longer Viable

While earlier, invoice processing was largely dependent on human effort, most organizations are now moving to some forms of invoice automation solutions. This shift is primarily driven by the complexities of global financial and capital markets, which involve multiple asset classes. Manually processing invoices is impractical due to the higher likelihood of errors introduced by humans and the significant amount of time it takes, such as a lengthy 19-day process. Consequently, implementing automated workflows with Straight-Through Processing (STP) becomes a strategic investment that empowers firms to improve their spending practices and enhance efficiency.

Getting there: Why Rules-Based AI/ML Engine Critical for End-to-End Automation

While hedge funds and asset managers invest in intelligent platforms like Coupa and SAP Concur, they are still unable to accrue the true benefits. Many still rely on manual labor at some stages of invoice processing. For example, while an automated platform makes the processes of extraction of relevant information easy from the plethora of document types, there are other more complicated information that must be extracted for non-PO invoices, such as allocation and tax withholding, which require a more advanced invoice processing solution than just plain data extraction or OCR. It requires the application of pertinent business rules for ensuring that invoices are processed correctly and do not result in compliance or regulatory failures. While a centralized invoice receipt, digitized information (including data from emails, faxes, and email attachments) and optimized processes – internal sources and outsourced integrations) are prerequisite for ensuring productivity and efficiency, but for true transformation, additional value with quality and compliance, absolute traceability, and control end-to- end is also necessary. And hence the need for a platform like Magic DeepSightTM for both structured and unstructured invoices.

Magic DeepSightTM : When your need is for a Streamlined and Advanced Solution

Since we are talking about the David and Goliath, all it takes to sort out the invoice processing problems is well-sorted, streamlined solution like DeepSightTM, that can be easily integrated with existing invoice processing platforms and organization-wide workflows, organizations can counter traditional invoice processing woes related to lack of efficiency, high costs, no real-time financial visibility, non-compliance, penalties, reputation damage, business disruptions, and revenue leakage with ease.

DeepSightTM brings together the best-of-breed technologies such as AI, Robotic Process Automation (RPA), machine learning, a rules-based engine, and analytics, to integrate seamlessly in existing systems and transform how your businesses handle invoice data. Highly advanced, DeepSightTM builds up the right momentum for modern enterprises (enriches data quality with a rules-based, deep learning/self-learning approach), and facilitates institutions to make well-informed decisions. Its user-friendly interface is a significant value-add as it helps finance teams be aligned and on the same page.

What makes DeepSight an Exceptional Tool for Automated Invoice Processing

  1. Complete End-to-End Solution
    DeepSight is the ideal solution if you seek an end-to-end approach. It ensures a smooth and efficient invoice processing experience, whether you’re dealing with PO or non-PO invoices, requiring minimal human intervention. While conventional automated Invoice Processing platforms, even the most intelligent ones, focus on data classification, extraction, and cleansing, they fail to utilize business rules for determining the appropriate invoice allocation for non-PO invoices, necessitating manual work. However, DeepSight stands apart with its intelligent data technology. Its AI/ML engine not only extracts data but also offers significant value by performing critical analytical functions. This capability proves invaluable for Hedge Funds, Investment Managers, and Brokerages handling a vast number of non-PO invoices alongside their PO invoices.
    DeepSight utilizes a pre-built, highly intelligent, advanced, and comprehensive rule-based AI/ML engine to effortlessly determine allocations and tax withholding. This process effectively meets essential compliance and stakeholder requirements while preventing revenue losses. The enhanced invoice information, also referred to as the golden data, is securely stored in the internal accounting system through Magic FinServ’s API for accurate record keeping. By offering a single window or centralized single source of truth, it promotes transparency and traceability.
    DeepSight’s continuous upgrades and updates enable it to adapt to new information using its pre- trained AI/ML and rule-based data extraction capabilities. This results in an end-to-end automated solution that learns with minimal supervision, making it an exemplary version of such a comprehensive solution.
  2. Rules-Based Data Extraction through Pre-Trained AI/ML Models
    DeepSight’s intelligent document content recognition performs accurate identification, classification and segregation of documents. Critical data elements from documents are recognized and extracted by pre- trained ML/AI models through a rules-based engine. Incorrect, Out-of-date, Redundant, Incomplete, Incorrectly Formatted extracted data is cleansed utilizing DeepSight’s reverse lookup algorithm and pre- trained models. So, more insights and less effort.
  3. Straight Through Processing (STP)
    One of the key requisites for future-proofing any process is STP. Data from invoice documents is extracted, cleansed, transformed and invoices are created in Coupa without requiring any manual intervention or active monitoring is required.
  4. Streamlined Exception Management
    The system will be implemented with an exhaustive exception workflow to alert users for any manual input (if required). Real-time exceptions resolution mechanism available in the system (Review UI) aims to reduce redundant effort of filling same information every time with onset of new legal entities/funds/deals Our rule-based user interface ensures clean and consistent data, reducing errors, and streamlining the process for Coupa customers.
  5. Enabling Traceability with Regimented and Well-defined Processes
    One of the major requirements when it comes to invoice processing is traceability. DeepSight system provides audits in exception handling, error handling, and changes in rules. These are performed in a well-defined and regimented manner. All activities are documented as version changes or user actions as appropriate and can be accessed via the audit table or in the form of reports for further audit.
  6. Create Standardized Nomenclature
    All of the business rules/key parameters will be picked from a Single Golden Copy (maintained in DeepSight). This nullifies the chances of inadvertent human errors that can result in data integrity issues.
    By embracing streamlined and automated invoice processing, it is possible for organizations to unlock multiple benefits. They can eliminate bottlenecks, improve accuracy, enhance visibility into financial operations, and achieve greater control over their accounts payable function. They are also in a better position to direct their time, effort and resources for more strategic and value-added tasks.

DeepSight futureproofs Invoice Processing for a Global Alternative Investment Manager

A global alternative investment manager that was facing problems due to its archaic largely manual- oriented invoice processing, was able to tackle high-level issues related to redundancy, productivity, costs, etc., with DeepSightTM. The customer’s business across different asset classes such as credit, private equity, and real estate, was difficult to manage due to the extremely high volumes of invoices. Manually mapping the complex business rules related to charges and tax withholdings was not an easy task to accomplish manually. With Magic FinServ’s DeepSightTM, the client was able to override the obstacles of time, operational costs, and errors while bolstering efficiency and productivity. Provided below is a step-by step guide of how DeepSight was able to meet the client’s objectives.

  • Parse through diverse invoice formats whether it is an image, PDF, excel, etc., with ease
  • Using DeepSight, the global alternative investment company, was able to extract information smartly and accurately related to different vendor invoices and carrying varied templates.
  • One of the biggest advantages of the tool is its ability to self-learn user’s action and feedback, thereby making it easier for the tool to auto populate from new learnings.
  • Our advanced and highly comprehensive solution based on AI/ML, fixated issues related to tax withholding and allocation with a rules-based approach.
  • For ensuring seamless end-to end processing, data was enriched via RPA and an RPA-enabled workflow was implemented for approvals and authorizations processing.
  • Using APIs for seamless integration with the core platform

The use case above exemplifies how DeepSightTM can be easily integrated with existing workflows or platforms to provide the results that firms had been looking for.

A truly transformative Invoice processing with DeepSightTM

While productivity and cost savings are the essential pillars of automated invoices, truly transformative invoice processing is one that focuses on increasing stakeholder satisfaction, improving agility and ensuring better management of working capital. For true transformation, additional value with quality and compliance, absolute traceability, and end-to-end control is also necessary. As a new shift is surfacing in the business ecosystem, it is time to redefine invoice processing and shift from the traditional approach to the DeepSightTM approach powered by AI technologies. With a highly refined and comprehensive solution that self learns with little help and has the gigantic capacity to scale up while ensuring end-to-end automated invoice processing of both PO and non-PO invoices, organizations not only can significantly reduce the percentage of errors and improve efficiency, but more essentially, they get a head start because of the deep insight they have gained thanks analytical capabilities of DeepSight (with rules-based approach) and an end-to-end solutioning of invoicing and prevention of revenue leakage.

For more information on how we can transform and enrich invoice processing with DeepSightTM, drop us a mail, at mail@magicfinserv.com to know about our invoice automation solutions. Even if you already have invested in an IP platform, you will be surprised to find what you are missing and how we can ensure a true end to end automation, where you will not have to worry about manual work ever again.

Though for years, overwrought developers had secretly been wishing for a genie who could automatically make their troubles vanish by automatically generating source code, that idea seemed far- fetched. But not anymore.

What seemed like wishful thinking once is now within reach thanks to the Developer Companion, an Artificial Intelligence-enabled platform designed specifically for the harried developers and development teams walking the thin line between contradicting business interests. The Developer Companion can do a lot more than just write a line of code, as you are about to find out very soon. But before that, a sneak peek into the developments that are underway in software programming.

Coding Goes through a Shift in Financial Software Development

The approach to financial software development has been undergoing a massive shift thanks to Artificial Intelligence and Machine Learning. Though Integrated Development Environments (IDEs) have been around for some time now, providing autocomplete features that take away some of the pains of coding, AI has been ushering in a paradigm shift underway in the world of software development. AI- assisted coding is simply the use of artificial intelligence/machine learning models to generate code automatically. AI-assisted code generation marks a new epoch because it relies on prebuilt code modules to build applications without the developers writing much (or any) code themselves. Instead, AI-assisted coding tools generate custom code entirely from scratch based on comprehensive training data and smart algorithms. Or to say, the central premise of these tools is the LLM model, that includes training on massive amounts of data existing source code — which usually comes in the form of publicly available source code produced by open-source projects. All that the developer has to do is ascribe in natural language what they want from the code. And viola! The tool does the rest.

With More Time in their Hands, Developers Turn into Superheroes

Artificial intelligence powered coding provides a new lease of life to financial software developers. With the power of AI, we are unlikely to see them frantic, their heads buried in the computer screen figuring out the next line of code or fixing a bug. Assuredly, when writing a boilerplate code for uploading a file, is no longer their sole preoccupation thanks to artificial intelligence and machine learning, they would have time to focus on the real core activities such as:

  • Brainstorming with product teams and carrying out requirement analysis
  • Bettering systems design and designing engaging user experience,
  • Planning the development and other implementation details to ensure timeliness and accelerated time to market
  • Continuously update and better their skills set
  • And in the process metamorphizing from a mere developer to a superhero

Now, let’s move on to the tool that turns them into a superhero and how it accomplishes this.

Developer Companion: Elevating Platform Engineering for the Ultimate Developer Experience and Efficiency

The Developer Companion is an artificial intelligence powered coding companion or rather a teammate for developers. The Developer Companion empowers developers by taking away the mundane aspects of their work and providing them time to focus on core valuable and higher-level activities instead of repetitive administrative tasks. Whether you’re starting from scratch or enhancing existing applications, Developer Companion is here to empower you every step of the way, here’s how:

Increased productivity: With the Developer Companion, developers can save time, improve quality, and increase efficiency. By slashing down the administrative work drastically, the Developer Companion can enable developers to focus more on the design and functional aspects of the coding work, along with other valuable and higher-level activities.

Accelerate the time to market: Thanks to the Developer Companion, and AI-based code prompters, developers can ensure a faster time to market. Instead of carrying out mundane and time-consuming tasks, like writing unit tests or translating code from one language to another, developers can complete the tasks much quicker.

Empowering developers: Whether you’re starting from scratch or enhancing existing applications, Developer Companion is here to empower you every step of the way. It does much of the heavy lifting, leaving developers to focus on truly critical aspects of work.

Extremely intuitive: It will not only predict the next line of code, but to understand your intent and infer context from what you’ve already written (including comments) to generate valid code. Not to mention, it makes mundane and time-consuming tasks, like writing unit tests or translating code from one language to another much easier.

Advantages of Developer Companion that You Cannot Afford to Miss!

Provided below are the tangible benefits of Developer Companion, that you cannot afford to miss out on:

Generate Code Snippet with Ease: Code snippets are templates that make it easier to enter repeating code patterns. Developer Companion can automatically generate code based on high-level descriptions or specifications. For example, AI models can analyze natural language descriptions of a desired program and generate corresponding code snippets or even complete programs. This can help automate the initial stages of coding and reduce development time.

Review the Code with Confidence: Developers have to accept (or reject) automatically generated code as they work. For some developers, the need to review code constantly could be distracting. They may be able to work more efficiently if there was a tool to review all code.

Navigate Complex Codebases with Code Comprehension: Whether it is complex code or legacy code, navigating through both is tricky on account of the complexities involved, lack of documentation, interdependencies, scale (number of lines of code, file size, terms of lines of code, number of files, and overall project scope, and in the case of legacy code there are multiple iterations, updates, and maintenance issues involved as well). Codebase or source code also encompasses multiple modules, libraries, and frameworks. However, the Developer Companion can easily navigate through the complexity of the codebase.

Extract knowledge from the existing code and make enhancements faster and error-free: Complex codebases/source code often involve multiple levels of abstraction. They may consist of high-level architectural components, intermediate modules, and low-level implementation details. With Developer Companion, programmers can extract the relevant details quickly and efficiently.

Bridge the Gap between Programming Languages through Code Conversion: Whether you are migrating a codebase from an archaic programming language such as COBOL to a modern one like Java or C++ or translating functions between C++, Java, and Python 3, the process is difficult and resource- intensive, and moreover requires expertise in the source and target languages. With Developer Companion, developers can bridge the divide through code conversion.

Test Code with Automated Test Case Generation: Automatic test case generation is the process of identifying and creating test cases for an application without the need for any manual intervention. It involves utilizing various techniques and tools to automatically generate test cases for software applications or systems. The primary objective is to automate the creation of test cases, leading to enhanced test coverage, improved efficiency, and reduced effort required for manual testing.

Discover Hidden Code Vulnerabilities: Instead of racking your brains regarding what could be wrong, or where the gap exists, developers can unearth the hidden vulnerabilities with ease using Developer Companion.

Unravel the Data Maze with Unique Database Query Console: Do not get lost in the maze of data, as a unique query console gets you inputs way faster.

Unleash the Power of Developer Companion Today!

In essence, an AI assistant for developers was long due for ridding the irksome, repetitive, and mundane pieces of work that they are saddled with daily. An AI-enabled assistant not only grants them a new ease of life but raises the bar as well when it comes to programming. It improves the time to market, efficiency, while minimizing problems such as legacy code and tackling risks such as shortage of skilled labor, attrition, testing challenges, etc., with AI. Developer Companion is all set to revolutionize AI in financial software development by extending the possibilities and taking it to a new level.

Now, if that was not enough to ask for a demo right away, we will be more than glad to satisfy your curiosity and any further questions that you might have. You can write to us for more information on how we could give coding a new lease or reach out to us at mail@magicfinserv.com for fintech solutions.

Standardizing Broker to Regulatory Authority (SEC/FINRA) Communication with DeepSightTM

We trust you were able to read our first blog (Are you ready for Sec T+1 Settlement reforms?) on the impending shift to T+1 settlement in the US, where we highlighted the reasons why broker-dealers and clearing brokers must automate and standardize communication related to trade. Here in this blog, we evaluate why regulatory filings must be automated as well.

Once a trade has been executed, the broker-dealer is expected to update the regulatory body as the case might be, with appropriate details related to the trade transaction. These reports or regulatory filings are a comprehensive summary of the trade that is submitted to the regulatory bodies on a timely basis. Regulatory filings involve trade status and timestamp details for all the actions like Order Initiation, Execution, confirmation, affirmation, matching, settlement, partially settle, rebook etc. In case there is a settlement failure or a rebooking, the broker dealer is expected to update the regulatory authority on that as well. The sole objective of this regulatory filing is to ensure transparency and to enable the regulator to assess and supervise the business being transacted by individual Counterparties within the marketplace. It is critical for protecting the interests of the investor and keeping the integrity and the security of the capital markets intact.

Typical Challenges in Regulatory Filings

Provided below are some of the typical challenges that broker-dealers face in ensuring a timely delivery of regulatory filings:

Operational Risk: Broker/dealers carry out trade lifecycle operations across multiple platforms and FinTech systems, often relying on complex manual processes to bridge the gap between these disparate platforms. However, they frequently face challenges due to outdated legacy processes and system performance issues and most importantly Data transfer issues due to Data compatibility, which hinder their ability to file regulatory reports in a timely manner.

Asset challenges: Investment managers face challenges related to diverse Asset types, including equity, fixed income securities, and ETD derivatives. Regulatory requirements for each instrument depend on the market in which it is traded, such as Organized Trading Facility (OTF) or Regulated Market (RM), as well as the specific guidelines set by regulatory bodies like the SEC, FINRA, and CFTC. As a result, the regulatory filing process becomes complex when broker-dealers do not automate or use a rule-based approach for FO-MO-BO data reconciliation and transformation.

Data quality and governance challenges: Excessive reliance on manual labor only for the classifying, aggregating, consolidating, and validating data during the multiple stages of the trade – initiation, confirmation, affirmation, rebooking, settlement constitutes a problem when it comes to meeting regulatory timelines or ensuring that all data is up-to-date and accurate.

STP challenges: All broker-dealers are typically required to report trade details to the SEC and other regulatory bodies in a timely manner. The reporting frequency and specific deadlines for filing these reports can vary based on the size and activities of the broker-dealer. In the absence of automation and STP, timely regulatory filings are difficult.

Finding the right vendor: Finding the right vendors for automating processes without impacting the existing business activities might not be as easy as expected. And that’s why broker-dealers need a partner with a thorough understanding of the capital markets and are capable of designing solutions that are tailored to fit.

Automating Regulatory Filing with Magic DeepSightTM : The 7-point advantage

Capitalizing on its immense experience in Capital and Financial Markets, and bespoke AI/ML platform that customizes solutions as per need, Magic FinServ ensures that regulatory filings are seamless and smoother than before – beginning with faster, smoother, aggregation and consolidation of data (using automation) and benefiting from a rules-based approach that adapts to evolving regulatory environment (including shift to T+1, and others) easily.

Sec T+1 Settlement Reforms for US
  1. Ensures data quality and governance: An AI-enabled platform like DeepSight can make a huge difference in the quality of data. Instead of inaccurate, inconsistent, and incomplete data, from manual data entry, broker-dealers are assured of clean, complete, consistent, and accurate data, for submission to the SEC and other regulatory bodies. DeepSight also validates and cross-references data, further minimizing the likelihood of errors and discrepancies. Most importantly is also creates an audit trail thereby enabling replaying of the transaction if needed.
  2. Simplifying reconciliation/transformation of trade data: An AI/ML and rules-based solution can ensure a faster, smoother, and more accurate reconciliation and transformation of trade data emanating between the front, middle, and back office when compared to the manual approach. This is most critical as the Data Models, Formats and Templates differ for each application and area, a key reason why the manual approach is simply not feasible for the impending T+1 settlement cycle.
  3. Easy integration: DeepSight can be easily integrated with existing systems. It supports data in all formats. The platform is format-agnostic and has the capability to support all sorts of data formats such as Excel files and spreadsheets, CSV files, emails and attached documents, API integration from multiple systems, and unstructured data.
  4. Shared database for data multi-purposing: Whatever the file format, DeepSight parses through data seamlessly from disparate sources such as back office, middle office, front office and processes, transforms, enriches it, and creates a single source of truth in a shared location or database.
  5. Enables timeliness and compliance: With DeepSight, broker-dealers can ensure that regulatory filings are done as per the timelines set by the regulatory authority. By automating the workflows, extracting the data from multiple sources (the back, middle, and front offices) and compiling it together becomes easier.
  6. Single solution: Straight through processing (STP) results in seamless and smoother regulatory filing. This integration enables seamless data flow and enhances overall workflow optimization. It reduces manual data transfer and improves the accuracy and efficiency of the trade reporting process.
  7. Adopt new regulatory changes easily with a rules-based approach: In an evolving regulatory environment, a rules-based solution makes it easier to reconcile data and file reports with the regulatory body becomes easier.

As the market gears up for T+1, this was how we could enable your transition to it. For more you can write to us mail@magicfinserv.com.

Enhancing Broker and Dealer Transition to new Sec T+1 Settlement with AI/ML Intelligent Data Automation Solution

In trading, time is of the essence, as every moment wasted in settling or reconciling a trade incurs higher costs and greater risks. Today, as the US proposes a shift to the T+1 settlement cycle, the primary objective is reducing the time it takes to settle a trade. And in the process, decrease the risks. That seems justified as the markets have experienced severe shockwaves in the last two years, due to market volatility, pandemic, fall of meme stocks, etc.

The T+1 settlement cycle essentially means that all settlements relative to trade must be carried out the next day and is expected to yield benefits like reduced costs, increased market efficiency, and reduced settlement risks.

So, while earlier, the settlement cycle (t+2) looked like this:

T+2 Trade Processing Workflow
Source: PWC’s T2 Settlement Information Report

Now we have a settlement cycle (T+1) that looks like the one below:

Source: State Street

Implications of Transition T+1: Unveiling the Key Challenges in Broker-Broker (Executive and Clearing Brokers) Communication

Though the transition to T+1 provides multiple benefits, the shift from T+2 to T+1 is not easy. We elucidate this using the example of brokers/dealers, who are a vital part of the trading chain. T+1 settlement of institutional trades lowers margins for broker/dealers. Brokers are required to pledge cash and securities to a clearing house, benefit enormously from the lower margin requirements (difference between the current value of the security offered the collateral and the value of loan granted). But it is not a win-win situation for them yet.

One of the biggest challenges in transitioning to the T+ 1 settlement cycle is the lack of automation in any communication emanating between broker-broker or the Executing Broker and the Clearing Broker when it comes to Trade File Processing. This broker-broker communication is centrally a part of the back-and-forth information processed by the middle office (MO) and settlement information/status received from the Clearing House or Back Office (BO)system.

Another significant challenge is the reconciliation of trade files and other reports. Without automation, manually updating these details, typically in Excel or spreadsheet format, can be quite cumbersome. The executing broker shares trade details with the clearing broker, usually in the form of spreadsheets, which are then processed and imported by the analyst team into the clearing system.

When investment manager, broker-dealer, clearing dealer rely more on manual processes than automated, time lags and delays are bound to happen as everything happens sequentially instead of bi- directionally. With automated processes, the majority of trades can be processed on the same day without requiring manual intervention.

Markets and prices are in a state of flux when it comes to trading. Hence, broker dealer, clearing broker must always be in a state of alert. Even remote chances of error or trade fails must be rooted out, unfortunately with manual mistakes that can have major consequences are higher.

Additionally, there are other unresolved issues such as:

  • Manual entry of data from documents received via email or fax from the investment manager when a trade is blocked. There is also a substantial amount of manual effort involved in the reconciliation and communication between the executing broker, the clearing broker, and other parties, for final clearing and settlement that must be automated for ensuring SDA(Same Day Affirmation).
  • There is still a substantial amount of paper involved
  • Sliced, dicing, and digesting the unstructured data in emails and faxes in time for T+1
  • Most firms are burdened by a crumbling legacy architecture that cannot scale up fast enough. If that were not concern enough, building a new one that could ensure adherence to t+1 from scratch would be time-taking and excessively expensive.
  • For (T+1), broker/dealers and clearing broker must speed up affirmations, confirmations, and allocations processes. But how do they do that when they have not yet automated their processes and there is no STP.

So better late than never! We are here to help firms navigate the transition to T+1, by redefining and re- strategizing the options and integrating our magical solution DeepSightTM that leverages the power of AI and ML to ensure a win-win. But first here’s a brief on T+1:

Automation is pivotal for T+1: How AI/ML and RPA helps reach the magical Same Day Affirmation (SDA)

The biggest challenge for T+1 transition is the lack of automation in institutional “allocations and affirmations.” This is one area that requires massive transformation to achieve the proposed settlement cycle timeframe. An automated solution can play a crucial role in facilitating same- day affirmation (SDA) processes for broker-dealers and clearinghouses.

With automation, broker-dealers and clearing houses can also:

  • Reduce the risk: As the volume of unsettled trades over a single trading day and the time between trade and settlement are reduced, counterparty, system-related, and operational risk is reduced.
  • Trade capture and validation: Perform real-time validations, ensuring that trades meet pre- defined criteria and are eligible for SDA.
  • Enables seamless transition: By automating various aspects of the settlement workflow, broker- dealers and custodians can minimize manual intervention, reduce operational risks, and enhance overall operational efficiency.
  • Eliminates the need for manual intervention and errors: Eliminating the need for manual intervention and reducing the risk of trade discrepancies.
  • Exception handling made easier: Automatically identify and flagging trades that require manual intervention. focuses on the resolution of exceptional cases promptly, paving the way for smoother SDA processes.
  • Seamless data validation and reconciliation: Validate trade data and reconcile it with external sources, such as market data providers or reference databases.
  • Prompter resolution of errors: Potential discrepancies or errors can be identified and resolved promptly, reducing risks associated with inaccurate or incomplete data.
  • Enables straight-through processing: Eliminates the need for manual rekeying or intervention at different stages.

Revolutionizing T+1 Settlement: Empowering Broker-Dealers and Clearing Houses with DeepSightTM

Now is the time for broker dealers and clearing houses that have not yet implemented automation to take to aggressively pursue automation if they are to abide with the proposed new rules. For broker dealers and clearing houses, the focus would be on ensuring SDA.

Here’s how Magic FinServ’s AI Optimization framework – DeepSightTM that has at its core AI/ML and Data builds tailored solutions that reduce the need for human intervention stoking up processes and ensuring optimal levels of efficiency for processes related to confirmation, allocation and affirmation and trade matching.

Magic FinServ’s innovative digital solution leverages the power of data and AI/ML technology to standardize business processes related to trade file processing by automating the broker-broker communication. Our highly intelligent and scalable solution shifts through data sources in different formats: Excel/spreadsheet/CSV files/Email body/Email attachment/API integration from multiple systems/ and other unstructured formats with ease and creates the “Reconcile Report” for other market player. It also supports the setup of the Golden Copy Data Management for multiple other sub activities related to the trade lifecycle. Other aspects of our solution include – Exporting the reconciled trade file, configuring any Business Rule/Mathematical rule which is required for generation of trade file, and generating reports based on customer need, i.e., in JSON, API, excel or any standard template.

While DeepSightTM can help automate processes, the move to T+1 settlement will still require fundamental changes throughout the trade processing lifecycle.

  • Consolidation of data feeds between new and legacy systems to centralize data management.
  • It is necessary to adopt technology (e.g., DTCC’s ITP CTM) and/or messaging protocols (e.g., FIX) to automate the communication of allocations and CTM’s Match to Instruct to facilitate more timely trade affirmations.
  • As firms move to T+1 settlement, they must adopt technology (e.g., DTCC’s ITP CTM/M2i) and/or messaging protocols (e.g., FIX) to automate the communication of allocations.

The Incredible Benefits of DeepSightTM

When broker-dealers, whether they are small boutique firms or subsidiaries of investment banks, consider their options, they can reap several benefits.

Eliminate the friction: Firms can eliminate the friction that exists at multiple touchpoints when data is entered manually. They can leverage the AI/ML capabilities to extract relevant data from documents, pdfs, mails/faxes, etc.

Fasten the post-trade agreement and affirmation by almost 50%: A solution like DeepSightTM can scale quickly and is ideal for periods when trade volumes are high or market volatility is high or both, as it trained to extract the appropriate data from the swathes of information available infinitely faster than humans.

Benefit from data-driven approach: Trade is ultimately about data. As the data experts, we can quickly identify which are the processes that would require automation. So, whether investment managers/portfolio managers who need help analyzing their performance or peers and counterparties/broker-dealers, custodians, our solutions can ensure that the transition to T+1 is smoother.

Reduce operational risk: With standardization and STP, operational risks are reduced considerably. When organizations opt for a solution like Magic Deep Sight, that leverages the power of AI and ML, and that can be easily integrated with existing systems, allocation, conformation, and central matching is given a boost. With SDA, firms can easily ensure the next day’s settlement.

Reference data management: Reference data management is a critical part of data management. To ensure transparency and efficiency, firms must update their reference data (e.g., the asset type, counterparty information), security pricing data, and standardized settlement instructions (SSIs). With DeepSightTM , the processes are streamlined and there is no chaos.

Easy and seamless integration with legacy architecture and workflows: No need to replace legacy: DeepSightTM biggest advantage is the heuristic approach wherein firms do not have to replace the existing workflows, as our solution can be integrated with traditional workflows and legacy architecture.

Exception Management: This metric assesses the ability to identify and resolve exceptions or discrepancies promptly during the settlement process. Efficient exception management helps streamline operations, reduces manual intervention, and enhances overall settlement efficiency.

Conclusion: A Shorter Settlement Cycle Benefits All!

Shorter settlement cycles benefit all. Some of the benefits are:

Shorter settlement cycles benefit all. Some of the benefits are:

  • Improved straight-through-processing (STP)
  • Quicker settlement
  • Less margin required
  • Reduction of operational and systemic risk
  • Decrease in costs and resources from reduced number of unsettled positions

Irrespective whether it is an investment manager, broker dealer, clearing dealer or clearing house, custodian, or settlement agent, T+1 is good for all. Ideally, T+0 settlement cycle offers the best deal; however, it would require a massive overhaul of the existing architecture, hence the SEC and other regulatory bodies have opted for transition to T+1 for the time being. Though some amount of re- strategizing is required to get in sync.

By embracing automation and STP, broker-dealers and custodians can enhance their operational resilience, reduce settlement risks, and improve client experience. They can focus on value-added activities and provide faster and more efficient services to market participants. If there is more that you would like to know as a broker dealer or clearing house, you can drop a mail at mail@magicfinserv.com

If the world is an oyster, airplanes are the TARDIS, and airports are the veritable blue box (from Doctor Who) – mostly noisy and often claustrophobic. The airport experience is rarely pleasant. Anxiety and stress are common due to flight delays, check-in hassles, seating arrangements (or rather, the lack of them), Wi-Fi problems, and more. This can be distracting for many passengers who would like some quiet time.

An airport lounge is an ideal place to relax and recharge. With free food and drinks, Wi-Fi enabled workstations, and clean facilities, travelers can take advantage of these amenities to unwind or catch up on work. Additionally, the lounge provides a networking opportunity with colleagues and friends. For those who desire a highly personalized or exclusive experience, the Polaris lounge (United Airlines) or Lufthansa’s super exclusive First-Class Terminal offer even more luxurious amenities such as a full bar, cigar lounge, plush sofas, buffet, and salon.

Now, a big pause! Many of you may be wondering if this is a build-up for Premier Lounges or the credit card companies that sell them. The answer is – no, it is not! This is about the parallel between the plight of passengers whose flight gets delayed or cancelled and the fintech’s journey in recent times. While travelers can recharge themselves at airport lounges, financial lounges like Magic FinServ can help fintechs recharge by providing super exclusive, hassle-free, and streamlined services. Magic FinServ’s advisory services and technology solutions can boost the pace of modernization/transformation by a significant 10X times.

The Many Stressors of Fintechs

Similar to how travelers face many stressors such as connecting flights, delayed and cancelled flights, fintech companies can also experience frayed nerves, especially when struggling with legacy workflows, redundant tools and technologies, unending migration problems, data swamps, and potential industry- wide disruptions caused by unexpected forces such as generative AI. Additionally, they must account for past mistakes such as overspending, which has resulted in big banks failing one after the other. The latest to bite the dust is First Republic.

If you are a fintech or financial services provider struggling to keep up with the massive disruptions occurring in the world today and are looking for a way to de-stress and energize, a Financial Lounge is what you need. A financial lounge is perfect for de-stressing your cluttered, siloed workflows and legacy engines from decades ago. Let us explore how.

Welcome to Magic FinServ! The Financial Lounge for FinTechs and Financial Services

  1. Beat the Stress
    • Managing financial data is one of the biggest challenges faced by fintechs and financial services. It is complicated as it involves a lot of sensitive information. Another significant challenge is compliance. Fintechs must stay up to date with the latest standards and work with regulators to ensure that all obligations are met in a timely manner. However, organizations no longer need to worry about these challenges as Magic FinServ can get them up to date.
    • We can help you prioritize data security and privacy, maintain accurate and up-to-date records, and ensure that data is easily accessible and actionable using the cloud and our AI and ML- enabled solution.
    • We can help you streamline your workflows quickly and assist you in embracing disruption.
    • DeepSightTM analyzes vast amounts of data in real-time for use cases such as risk management, fraud detection, AML, KYC, portfolio management, regulatory compliance (Shareholding and voting rights, ESG, T+1, investment and fund monitoring and reporting).
    • You can also count on our team of AI and Machine Learning specialists and FinTech engineers to identify gaps and provide sound advice on how you can leverage technology such as AI to speed up your processes at minimum costs.
  2. Relax and Recharge while our bespoke AI platform crunches numbers faster than Speedy Gonzales
    • Rest and relaxation are important for both physical and mental well-being. Like airport lounges offer a place to unwind and recharge during a stressful time, Magic FinServ’s financial services acts as financial lounge for fintechs providing them with the needed “rest” and allowing them to focus on their core business. Our tools and services can help fintechs manage their finances with ease and confidence. Here is how
    • For humans, sleep is more than a biological requirement. It helps them recharge their batteries for another day of work. However, because of the existence of multiple time zones when markets are alive and active in one part of the world, our analysts weary and tired after a full day of work could be fast asleep, missing several critical incidents in another part of the world. So, when they come back to work the next day, they have their hands full. Most of the work that they would be required to do to keep the processes up to date would be of a manual sort, such as data entry, uploading and downloading files. Making the analyst feel tired like Jack – because all work and no play makes Jack a dull boy.
    • Now you can slay stress and be up-to-date faster than it takes to say I do! Unlike humans, our AI- powered platform does not need any sleep at all. So, while you are fast asleep, our powerful AI-powered solutions are deep at work automating facets of operations that were time-taking and tedious, ensuring that when you come fresh to work the next day, you only have to fine tune or take a summary, as the rest has been taken care of by AI.
  3. Experience a Seamless Transition
    Passengers go through an agonizing period when they wait for a connecting flight, and fintech companies experience a similar sense of anxiety while awaiting the results of cloud migration and modernization efforts. However, with financial lounges such as Magic FinServ, the desired transformation can now be achieved more quickly. Our three-step approach for cloud migration includes:
    • Conducting a cost-benefit analysis with the help of our dedicated cloud team. This analysis takes into account the costs of migration and ongoing maintenance, as well as the savings that organizations can expect to see.
    • Optimizing the cloud environment with the use of automation and orchestration tools.
    • Utilizing cloud-native services such as containerization and managed databases to reduce costs and improve efficiency.
  4. Utilize Time Profitably
    • In today’s fast-paced world, time is a valuable commodity. Similar to how airport lounges with workspaces allow travelers to catch up on work while waiting for their flights, our financial solutions enable fintech companies to leverage the power of AI and ML to stay prepared for any unforeseen consequences. By automating time-consuming and repetitive tasks, our solutions allow fintechs to focus on high-value work and take advantage of opportunities as they arise. This way, they can make the most of their time and operate with maximum efficiency, ultimately leading to increased profitability.
  5. Remain Exclusive
    • People go to these lounges not only when their flights are delayed but also for novelty- it offers a unique experience. So it is for the financial services, we are their niche partner offering them the unique space to innovate and experiment. Because it has become apparent now that despite indications that recession may have set in finally, organizations, especially the bigger ones, are earnest about prolonging investment in moonshot projects. Some of the most common moonshot projects relate to robo- advisory, de-fi, embedded banking.
    • If you are keen on continuing moonshot projects, ensure STF and automation of back and middle-end processes first, because unless these two ends are unified and compatible, it would be unreliable to expect long-term benefits from other areas.

Magic FinServ: an Oasis for FinTech’s

In today’s fast-paced world, FinTech companies face numerous challenges that can impact their ability to succeed. From managing legacy workflows to keeping up with constantly evolving technologies and regulations, it can be challenging to stay ahead of the curve. That is where Magic FinServ comes in – as an oasis for FinTechs.

As experts in data and AI for FinTechs, Magic FinServ provides customized solutions that help companies manage the stress that comes with operating in this turbulent environment. We understand the unique challenges that FinTechs face and work with our clients to develop solutions that are tailored to their specific needs.

Our services act as a refuge for FinTechs, providing them with a much-needed break from the chaos that often surrounds their operations. Just as an oasis provides water and shade to travelers, Magic FinServ provides FinTechs with the support and resources they need to thrive in an ever-changing landscape.

Our clients can count on us to help them manage complex data sets, navigate legacy workflows, and keep up with the latest technologies and regulations. With Magic FinServ by their side, FinTechs can take on new challenges with confidence, knowing that they have a partner who understands their unique needs and can help them achieve their goals.

In conclusion, Magic FinServ serves as an airport lounge or oasis for FinTechs, providing the support and resources they need to navigate the challenges of the modern business world. With our expertise in data and AI, we help FinTechs manage the stress that comes with operating in a constantly evolving

landscape and enable them to thrive in the face of adversity. Contact us today at mail@magicfinserv.com to know more.

Microservices are truly remarkable, revolutionizing the way applications are constructed, managed, and supported within the cloud environment. They play a pivotal role in the cloud-native paradigm, enabling effortless scalability of assets and proving to be a perfect fit for the fiercely competitive market. The extraordinary achievements of Monzo bank and Uber serve as compelling evidence that cloud-native and microservices architecture are undeniably the future. With a digital-first mindset, both Monzo and Uber have embraced minimal infrastructure maintenance costs, exemplifying the immense value of this approach.

Take Monzo, for instance. They have meticulously developed their core banking system from the ground up, leveraging the unparalleled flexibility and scalability of the AWS cloud infrastructure. Through the adept utilization of microservices architecture and employing container tools like Docker and Kubernetes across multiple virtualized servers, Monzo has successfully attracted a significant proportion of millennials to its customer base, owing to its streamlined and user-friendly approach. As the cloud- native approach continues to gain traction, it becomes imperative to delve into the challenges and benefits that organizations encounter when utilizing microservices, which lie at the heart of the cloud- native philosophy.

Capitalizing on the Cloud: Understanding Cloud-Native Architecture

How can organizations break free from mainframes, monolithic applications, and traditional on- premises datacenter architecture? The answer lies in adopting a cloud-native approach, which empowers modern businesses with unparalleled speed and agility.

Cloud-native applications are built from the ground up, specifically optimized for scalability and performance in cloud environments. They rely on microservices architecture, leverage managed services, and embrace continuous delivery to achieve enhanced reliability and faster time to market. This approach proves particularly advantageous for financial services, banks, and capital markets, where a robust and highly available infrastructure capable of handling high- traffic volumes is a necessity. The key components of a cloud-native approach are as follows:

  • Cloud service model: Operating on the fundamental concept that the underlying infrastructure is disposable, this model ensures that servers are not repaired, updated, or modified. Instead, they are automatically destroyed and swiftly replaced with new instances provisioned within minutes. This automated resizing and scaling process guarantees seamless operations.
  • Containers: Container technology forms another critical pillar of the cloud-native approach, facilitating the seamless movement of applications and workloads across different cloud environments. Kubernetes, an open-source platform, takes center stage in managing containerized workloads efficiently, with speed, manageability, and resource isolation.
  • DevOps: DevOps is a methodology widely adopted in the software development and IT industry. It encompasses cultural philosophies, practices, and tools that enhance an organization’s ability to deliver applications and services at high velocity, thus enabling accelerated innovation. This approach promotes collaboration and communication between development teams and IT operations, driving efficiency and agility.
  • CI/CD pipelines: Continuous Integration/Continuous Delivery (CI/CD) pipelines focus on automating and streamlining software delivery throughout the entire software development lifecycle. By integrating frequent code changes, running automated tests, and deploying applications in a consistent and automated manner, organizations can improve productivity, increase speed to market, and ensure higher quality software releases.

Lastly, microservices play a pivotal role within the cloud-native architecture. Drawing a parallel to the Marvel character Vision, microservices are fragmented and independent, similar to how Vision remains intact despite encountering multiple setbacks on his journey to becoming a superhero. Microservices function as modular and cohesive components within a larger application structure, enabling flexibility, scalability, and resilience.

By embracing cloud-native architecture, organizations can unlock the full potential of the cloud, capitalizing on its scalability, reliability, and performance. It offers a transformative approach to application development and deployment, revolutionizing the way businesses operate in the digital era.

The Game-Changing Benefits of Microservices Architecture

Microservices offer numerous advantages. Unlike monolithic applications, where all functions are tightly integrated into a single codebase, microservices provide a less complex architecture by separating services from one another.

In the ever-growing landscape of application development and testing costs, microservices are an excellent choice for fintech and financial services due to the following reasons:

  • Quick scalability: Microservices enable easy addition, removal, updating, or scaling of individual services, ensuring flexibility and responsiveness to changing demands.
  • Disruption-proof: Unlike monoliths, where a failure in one component can disrupt the entire system, microservices function independently. This isolation ensures that a failure in one service does not impact the overall service, enhancing reliability and fault tolerance.
  • Language agnostic: Microservices architectures are language agnostic, allowing organizations to use different programming languages and technologies for individual services. This flexibility facilitates the use of the most suitable tools and frameworks for each specific service, optimizing development and maintenance processes.
  • Easier deployment: Microservices enable the independent deployment of individual services without affecting others in the architecture. This decoupling of services simplifies the deployment process and reduces the risk of unintended consequences.
  • Replication across areas: The microservices model is easily replicable across different areas or domains. By following the established patterns and principles of microservices, organizations can expand their architecture and leverage the benefits of modularity and scalability in various contexts.
  • Minimal ripple effect and faster time to market: In monolithic architectures, introducing new features or implementing customer requests can be a lengthy and complex process. However, with microservices, new features can be developed and deployed independently, reducing the risk of a ripple effect, and enabling faster time to market. Customers can experience desired features within weeks rather than waiting for months or years.

By leveraging microservices, fintech and financial service organizations can enjoy increased agility, scalability, fault tolerance, and accelerated innovation while optimizing development and operational costs.

Why are microservices difficult to implement?

With great power comes great responsibility and so while microservices are indeed a brilliant step toward application development, there are many challenges that make it tough to handle. However, because there are multiple depedencies associated with microservices, testing microservices-based applications is not an easy task.

Here are some of the challenges that teams face when implementing microservices:

  • Collaboration across multiple teams: The existence of multiple teams working on different microservices can lead to coordination challenges. Ensuring effective communication and collaboration between teams becomes crucial to maintain alignment and avoid conflicts.
  • Scheduling end-to-end testing: Conducting comprehensive end-to-end testing becomes challenging due to the distributed nature of microservices. Coordinating a common time window for testing all interconnected services can be difficult, especially when teams are working across different time zones or have varying release cycles.
  • Isolation and distributed nature: Microservices operate independently, which brings benefits but also challenges. Working in isolation can make it harder to ensure seamless integration and coordination between different microservices, potentially leading to compatibility issues or inconsistencies in functionality.
  • Data management complexities: Each microservice typically has its own data store, leading to data management challenges. Ensuring data consistency, integrity, and synchronization across multiple microservices becomes critical to maintain a holistic view of the system.
  • Risk of failure: With the increased number of services and their interdependencies, the risk of failure also amplifies. A failure in one microservice can potentially affect other dependent services, leading to cascading failures and system-wide disruptions.
  • Bug fixing and debugging: Identifying and fixing bugs in a microservices architecture can be more complex than in monolithic systems. Since microservices work in isolation, debugging and troubleshooting require careful analysis and coordination among different teams responsible for individual services.

Resolving the Challenges

Microservices serve as the fundamental building blocks for modern digital products and ecosystems. Their architecture offers the flexibility to choose the language or technology for rapid and independent development, testing, and deployment.

To overcome these challenges, it is essential to address the following:

  • Include specialists for every layer: Ensure the presence of experts in user interface (UI), business logic, and data layer to effectively handle the complexities of microservices architecture.
  • Manage turnover effectively: Acknowledge the possibility of skilled resources leaving and establish a plan to ensure seamless transitions and quality replacements.
  • Prioritize dedicated infrastructure: Ensure the availability of high-quality cloud computing and hosting infrastructure capable of handling the anticipated load and traffic, guaranteeing the optimal performance of the product.
  • Implement a principled DevOps approach: Given the higher risks of security breaches in microservices, adopt a rigorous DevOps approach to enhance security measures. Secure APIs play a vital role in safeguarding data by allowing access only to authorized users, applications, and servers.
  • Establish service alignment through APIs: Despite working independently, microservices are interconnected within the application structure. Therefore, it is crucial to ensure proper alignment and communication between services through well- designed APIs.
  • Enable dynamic communication: Microservices should possess the ability to communicate not only in the static state but also in the dynamic state. This requirement necessitates the utilization of load balancers, DNS, smart servers, and clients.

Why Choose Magic FinServ for Cloud-Native and Microservices Excellence?

Capitalizing on the power of cloud-native and microservices architecture is crucial in today’s digital landscape. However, organizations face challenges such as re-platforming and re- factoring when implementing cloud-native applications, as highlighted by an IDC survey. To fully leverage the potential of the cloud, organizations need a partner that possesses a comprehensive understanding of cloud architecture, DevOps practices, and the architectural changes brought about by microservices to support the cloud-native model.

At Magic FinServ, we have a proven track record of successfully building and delivering digital products, web apps, and services to market using agile methodologies. Our solutions are built on a structured approach that optimizes value and ensures early wins.

By partnering with us, you can expect the following benefits:

  • Break the monolithic application into microservices.
  • Enable a shift from waterfall to agile with a minimum viable product at the core.
  • Cost management by focusing on early wins and generating incremental value.
  • Ensure operational excellence with automation with CI/CD pipelines and IAC. Enhance productivity with DevOps and Agile methodologies.
  • Incorporate horizontal scaling and design for performance efficiency.
  • Ensuring security is baked into the DevOps lifecycle.

If you would like to know more about you can write to us mail@magicfinserv.com

In today’s fast-paced world, technological advancements are reshaping industries, and businesses must adapt to stay relevant and competitive. This infographic explores the importance and inevitability of modernizing applications and platforms, uncovering the transformative potential that lies within this process.

Unlock the power of modernization and embark on a journey towards a brighter future for your business. By breaking the shackles of legacy, you embrace the inevitability of progress and position your organization for success in a rapidly evolving digital landscape. Stay tuned as we delve deeper into the world of modernization and share insights on how to navigate this transformative journey. Together, let’s shape a new era of possibilities.

What is the strategy for halting #Erling Haaland’s unstoppable goal-scoring spree? He has been an unstoppable force!

In his debut season, the exceptional Norwegian striker has scored an incredible 48 goals in 41 matches. In the Premier League, he is only a couple of goals away from breaking previous records.

With Haaland’s remarkable ability to convert strikes into goals during the Champion’s League playoffs, rival team managers are on a prolonged hunt for a solution. While Haaland continues to amass more Easter eggs, his opponents must find ways to impede the ascent of the 22-year- old Manchester City sensation.

It is a relief that a plan has finally surfaced, and it is strikingly like what our developers at Magic FinServ have been implementing for a while now to prevent a bug from unleashing its destructive potential. In an interview with a TV show, Brantford defender, Ben Mee, elaborated on a strategy to confront Haaland on the field. The strategy entails several steps:

  1. “Man-mark” Haaland. Train all your guns on him. Predict all his moves including his goal scoring and penalty taking tendencies, etc.
  2. Sandwich him or crowd him out of the game which simply means pushing him out of the picture or breaking the link between him and his teammates.
  3. Withold midfielders, who are more important than the star striker as their creative passes enable Haaland to make the golden strike.
  4. Bee Mee openly admitted that Brentwood’s strategy was all about stopping Kevin De Bruyne’s link play with him, and that’s why Brentwood was one of the few teams that could keep the Norwegian star striker from going on a rampage.

Whether it is Haaland or bugs, it is necessary to contain them before they go on a destructive spree and cause harm (to opposing teams) or applications. As with Haaland, developers have some strategies for stopping bugs which are as under:

Tackling bugs is not an easy task

When it comes to the issue of bugs, there is unanimous agreement that developers must eradicate them to prevent additional harm. This involves identifying and isolating the bugs, carrying out comprehensive testing to eliminate them, and thoroughly checking the environment and APIs, whether in the cloud or on-premises, where significant threats may exist. Magic FinServ’s approach is akin to Ben Mee’s strategy. Our QA and testing teams ensure that the bugs are promptly addressed to prevent their proliferation.

Crowding out the Bugs with Automation and Integrated DevOps practices

We crowd out the bugs using an extensive mix of automation, regression testing, and carrying out tests of the software in different environments to ensure that the performance is as desired irrespective of the kind of operating systems, APIs, browsers, and hardware configurations. To fully test an application and ensure optimal performance, developers rely on different types of testing – functional testing, usability testing, and performance testing.

The kinds of tests we do:

  • Magic FinServ offers test automation/tool expert services, test automation frame and design services, and business and domain assurance testing services for data verification.
  • We provide non-functional testing such as Data warehouse testing and ETL services along with security assessment and security testing services. If the data is on the cloud, then cloud-based test design and execution services
  • Additionally, we offer functional testing for QA performance engineering optimization, QA agile transformation services along with QA audit and process improvement services.

The Benefits of Integrated DevOps and Lifecycle Automation for Testing Approach

At Magic FinServ, an integrated DevOps approach and automated testing are utilized for quality assurance, in contrast to a manual approach where testing is conducted at the end of the development lifecycle due to business and operational constraints, leaving only time for functional tests.

Fewer incidences of bugs slipping in: Compared to the manual approach, where the incidences of bugs slipping in or flaws existing are high, – Magic FinServ’s approach to QA and testing is more effective as it relies more on technology and less on human intervention and hence is quick and proactive (anticipating bugs and flaws is easier).

High visibility and less dependence on key people: In the manual approach the same set of people are required to carry out key tests increasing the dependability on them.

We follow the Agile and DevOps practices which promote high visibility and limit dependency on key people. The use of automation also eliminates the need for synchronization with downstream systems, ensuring that teams can continuously test using shift-left/shift-right methodologies to quickly identify and eliminate potential threats, resulting in a richer user experience.

Automated testing and an integrated approach minimize defects to less than 5% and the time taken to fix an issue and provide the QAs with a new build is less than a day. As the incidences of false positives are minimized with automation, less time is spent weeding out the exceptions.

API Automation Accelerator


Erling Haaland’s presence on the field leads to one-sided matches but watching him play is a delightful experience. We hope Ben Mee’s evaluation will bring about more excitement and breathtaking goals during the upcoming May 2023 semi-final match between Manchester City and Real Madrid, and the Champions League final in June 2023. If you have any inquiries regarding bug deactivation and ensuring optimal user experience, please contact us at mail@magicfinserv.com in the meantime.

For most organizations, the lack of timely insights can make contract data management a nightmare. Without the necessary tools and technologies, many organizations can be caught off-guard when it comes to negotiations, execution, renewals, and termination of contracts. It is estimated that lack of timely insight into obligations and terms can result in revenue leakage of more than 9% annually. Source: (World Commerce and Contracting)

Whether it is Auto-Renewal, Termination, and in recent times Force Majeure, these clauses within the contract results in unnecessary diversion from business objectives, as the excessive reliance on the manual approach can only lead to unsavory incidents and disagreements between parties concerned.

No one would want that. The experts point out that an average Fortune 1000 company could handle several tens of thousands of contracts. Now if we were to consider the various stages of the contract management lifecycle – negotiations, execution, renewal and the multiple stakeholders involved – sales, finance, and legal teams, all this would simply mean that the amount of effort deployed (and expenses paid) to ensure streamlined operations would be huge. Source: (World Commerce and Contracting)

Hence in recent times, businesses have switched from the predominantly manual approach of contract data management to a more agile and technology-oriented perspective using automation, digitization, and robust data management (including meta data management) practices such as organizing a unique repository for each contract and curated database for locating a specific contract with ease. This shift provided organizations with a definite strategic advantage even during the pandemic, improved vendor relationships, enhanced visibility, and business gains as negotiations were conducted timely, while keeping at bay all possible risks.

So, if you are considering an overhaul to have better control over your contract data management, here are the 6 key players that could be a game changer for your organization.

5 key players of Contract Lifecycle Management

According to the latest forecast by Gartner, by 2023, artificial intelligence (AI) will enable 30% faster contract negotiation and document completion processes in organizations that deploy leading contract life cycle management (CLM) solutions. As a fintech or financial organization, you can still salvage the situation. For reports point out that the latest tools are enhanced with a version control mechanism and searchable repositories for arriving at the single source of truth with minimum effort and human intervention resulting in significant productivity improvement and reduction of sales cycles.

Digitizing data: Begin with the digitization of data. Keeping track of documents, the multiple edits that are incorporated from time to time, can be a tedious and wasteful exercise. Furthermore, with data existing in silos a nightmare situation can arise if stakeholders have multiple versions of the contract. In order to avoid contract nightmares, the first critical step is to digitize data. Whether public documents, emails, or paper agreements, digitize the contracts so that there is a single source of truth.

The 5 levers of transformation

When it comes to contract data management, the following technologies have a key role to play in its transformation. The following 5 levers of transformation supplant the slack/inefficiency associated with traditional manual contract data management and provide it with agility, visibility, accuracy, faster response times, and productivity.

Optical Character Recognition: Once organizations have proceeded with the digitization of the diverse document types, they must work out how they must extract relevant information from the volumes of data available because machines inherently lack the power to read them. Despite the variety of document types, and field types – names, dates, boilerplate text, different fonts, and even handwriting, OCR can read through it all and extract the relevant information faster in a standardized, streamlined fashion.

Natural Language Processing: The language used in contracts is complicated and legal in nature and can be best understood by professionals or the legal experts. A rule-based approach enables progressive understanding of the terms and the context, and organizations can even retain experts for relating and better understanding of context when it comes to ambiguous/difficult-to-understand terms and conditions.

Robotic Process Automation: Contract automation has been defined as the software to enable both legal and non-legal teams to self-serve on routine legal documents, at scale, without needing to involve lawyers every time. It can be described as the process of generating, managing, and storing contracts digitally to create a more efficient contract workflow. In order to bring about greater productivity and efficiency, we recommend automation of all tedious and repetitive data extraction tasks.

Machine Learning and Artificial Intelligence: No organization will like to miss the deadlines as there could be significant costs associated with it. Staying-up-to speed on contract renewals can seem like an uphill task, but with artificial intelligence and machine learning, you can ensure that your teams never miss an important obligation. Artificial Intelligence and Machine Learning comes streamlines the process for most organizations dealing with multiple contracts (big organizations juggle some 20,000 and 40,000 active contracts). Keeping up-to-date and abreast of the latest on a monthly or yearly basis would simply be impossible without the technology underlined above.

Taking control of contract management with Magic FinServ’s DeepSightTM

We can help streamline contract data management. Ensure that there are no contract nightmares that ever cause organizations to pull in resources needlessly for firefighting. Here’s how we assure a smarter contract management powered with OCR, RPA, AI and ML.

Contract Data Extraction Workflow

Magic’s DeepSightTM – the process optimization platform along with our Advisory practice provides a configured solution that acts as a virtual assistant to the analyst thereby reducing the complexity of the task. It automates standard processes to reduce errors and omissions and enables the less experienced and less skilled analysts to be able to perform their tasks.

How DeepSightTM works?

Processing diverse documents: Service Provider Agreements vary by type of service; each service provider has its own unique terms and conditions. These documents have to be categorized according to type of service and for each service provider, relevant content identified and extracted

Unique folder for easier access and retrieval: Our solution not only identifies and segregates different documents but also files all documents for a particular service provider in the same folder to enable ease of access and retrieval.

Rules based: Magic DeepSightTM solution incorporates business specific rules to identify relevant information and extract the same and update it in deal maintenance system after proper cleansing, enriching and transformation. Content extracted can be key value pairs, tables, or free flow content such as covenant clauses. If it is deal related, the key value pair is extracted. In the case of governance, contextual data is extracted and in deal maintenance details, combination of contextual and key value pairs are extracted which are all driven by the rules. Solution can go through the entire set of documents related to a particular deal including annexures, renewals, etc. to identify the latest terms and incorporate in the deal maintenance system.

But remember all this starts and ends with data. Data is the motherboard of contract lifecycle management. So as an organization we are in a unique position to aid data-driven transformations as we have the expertise, and the skill sets to deal with all your concerns. If you too would like to know, how we can be of help, contact us mail@magicfinserv.com.

The Future’s Getting Breathtakingly Simple

Before the Covid-19 pandemic, managing contracts was not an easy business. The legalese that contracts are clouded in, constitutes just a small fraction of the challenge that organizations face during contract management. The bigger challenge is the existence of contracts in diverse forms such as public websites, paper, emails, and ensuring that obligations are met in a timely manner so that there are no monetary losses or wranglings/disputes with the parties concerned later.

A change has been necessitated because as the world gets smaller, as borders fade out when it comes to doing business, and the number of stakeholders multiplies, the stakes have also become disproportionately high, and as a fintech or financial institution you simply cannot afford to leave anything to chance. Hence, the need for augmenting human intelligence and capacity with intelligent tools powered by Artificial Intelligence (AI) and Machine Learning (ML) and relying enormously on digitization capacities and the cloud for managing, storing, and interpreting contractual information effortlessly.

Demystifying the Reasons Behind the Shift!

Though contract data management has always been a long-winded and paper-heavy process, there has been a subtle shift post covid as organizations are becoming more open to using modern technology such as AI and ML post covid 19 for addressing many of their pain points post covid. This was primarily because, during the pandemic and post-it, organizations realized that they could not leave contract data management to the legal experts and the analysts (solely) anymore – for not only was it becoming extremely time-consuming and expensive, but also manual contract data management was proving incapable of providing the desired level of scalability and deep insight that organizations required. So, here’s decoding why as a fintech or Financial Institution, Smarter Contract Lifecycle Data Management is critical for keeping pace in a changing business landscape.

A) Unstructured data in files, cabinets, and silos across the enterprise were difficult to access and update

When the pandemic struck, which was quite sudden, some organizations had either digitized their contracts and processes or hadn’t. For those who hadn’t digitized the swathes of paper agreements or the contract management process, managing contracts turned into a nightmare as accessing files from the repositories or cabinets at a minute’s notice was improbable. This probably was the biggest learning for organizations as they realized that digitization or cloud solutions/cloud-based contract lifecycle management (CLM) enabled a level of business continuity that was not possible when you were relying simply on paper agreements or contracts. If the challenge posed by unstructured data was not enough, the existence of structured data such as the ones in public repositories with multiple stakeholders and existing in silos enterprise-wide constituted another major challenge during the pandemic for the same reason of lack of accessibility.

B) Staying in control was difficult as there was limited visibility into data

In 2020, the number of Force Majeure clauses invoked was a record high in many parts of the world. The force majeure clause implies an Act of God or some unforeseen circumstance, man-made or natural disaster that makes it difficult to fulfill certain obligations of the contract. By invoking this clause in the contract, the parties involved can protect themselves from liabilities that arise due to their failure to provide a certain service or product. Interestingly, the force majeure clause was rarely invoked prior to the pandemic, and if we were to go by the findings of the World Commerce & Contracting Report on the latest Most Negotiated Terms, 2022, it ranks a low 26 in the list of the most negotiated terms, but post the pandemic, it was one of the oft-invoked clauses.

In 2020, the number of Force Majeure clauses invoked was a record high in many parts of the world. The force majeure clause implies an Act of God or some unforeseen circumstance, man-made or natural disaster that makes it difficult to fulfill certain obligations of the contract. By invoking this clause in the contract, the parties involved can protect themselves from liabilities that arise due to their failure to provide a certain service or product. Interestingly, the force majeure clause was rarely invoked prior to the pandemic, and if we were to go by the findings of the World Commerce & Contracting Report on the latest Most Negotiated Terms, 2022, it ranks a low 26 in the list of the most negotiated terms, but post the pandemic, it was one of the oft-invoked clauses.

Today, it would not be hard to imagine how tricky, tiresome, and time-consuming would it be for a human, whether a legal expert or an analyst to skim manually past the swathes of paper contracts or public repositories for finding the terms and conditions associated with clauses such as termination, scope and goals, payment and payment options, data privacy, services levels, acceptance, regulatory compliance among others, and keeping up-to-date and in case of conditions such as the force majeure compliance among others, and keeping up-to-date and in case of conditions such as the force majeure how an untoward incident would have an impact on the organization. Considering the fast-paced business environment that the banks and FinTechs are operating in, finding, updating, and validating the relevant information manually is totally undesirable. However, with intelligent contract data management solutions, and automated solutions, it takes no time to extract, update, validate and monitor information that is required for keeping up to date.

C) Making intelligent decisions was difficult without appropriate tools, approaches, and technology

During the contract data management lifecycle, organizations get the best value from the services or products that must make intelligent decisions. They must access data quicker and faster than ever before. However, with data existing in silos, and in multiple formats, a data swamp builds up over the course of time. In order to make intelligent decisions faster, all data about a particular contract must be in one place instead of clustered everywhere. Using a combination of intelligent tools, powered with artificial intelligence and rules-based engines with capacities for learning and robust data management practices and metadata – a unique identifier without which one would have to wade to tons of data, organizations can take accurate and on-time decisions.

D) The realization that a centralized source of truth is more readily accessible than a file or a cabinet or data in silos

A unique centralized repository where you can store all your data in a digital format is better equipped to handle the challenges of the next-gen contract management lifecycle than the outdated physical file or cabinet. It is bestowed with dynamism thanks to automation, a unique digital repository centralized repository where it is readily available along with metadata, making it much more convenient for organizations than a filing cabinet or a siloed existence.

The Future in Simplicity

Contract data management does not end with the negotiations and signing of the contract between the parties. There is a lot of work that goes in the management of a contract such as keeping up to date, remaining compliant, and realizing maximum benefits, and for that contract management must be made simpler so that there is on-time/on-demand information.

As a financial institution, if you are unable to access information about the contract that you have signed in time and make decisions accordingly, you expose yourself to needless disputes and wranglings later, and are burdened with higher costs, poor performance, unnecessary risks, etc. Contract intelligence solutions begin by centralizing and streamlining contracts providing visibility into all contract data, thus empowering the organization to efficiently monitor all contractual and regulatory compliance obligations. That is the first step to simplifying it.

In the next blog, we will tackle the tools and technologies that make contract management more intelligent and how Magic DeepSightTM enables it. Magic’s DeepSightTM the process optimization platform along with our Advisory practice provides a configured solution that acts as a virtual assistant to the analyst thereby reducing the complexity of the task. It automates standard processes to reduce errors and omissions and enables the less experienced and less skilled analysts to be able to perform their tasks. Stay Tuned!

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