Until recently, your enterprise may have considered smart contracts as a tool to bridge silos from one organization to another – that is to establish external connectivity over Blockchain. However, what if we proposed applying the same concept so a firm can be instrumental in addressing enterprise-wide data reconciliation and system integration / consolidation challenges to expedite time to market and streamline (i.e internal, regulatory, FP&A, supplier risk) reporting. 

Afterall, about 70-80% of reconciliation activity takes place within the enterprise. The best part? A firm can do this with minimal disruption to its current application suite, operating system and tech stack. We will look at traditional approaches and explain how smart contracts are the way to get started on one of those journeys when one never looks back

To set the stage, let’s cover the self-evident truths. Reconciliation tools are expensive and third party tool implementations typically require multi year (and multi million dollar) investments. Over 70% of Reconciliation requirements are within the Enterprise amongst internal systems. Most reconciliation resolutions start with an unstructured data input (pdf/email/spreadsheet) which requires a manual review/scrubbing to be ingested easily. For mission critical processes, this “readiness of data” lag can result in delays and lost business, backlogs, unjustifiable cost and worst of all, regulatory penalties. 

Magic Finserv proposes a three-fold approach to take on this challenge. 

  1. Data readiness: Tackle the unstructured data solution using AI and ML utilities that can access data sources and ingest them into a structured format. Often Reconcilliation is necessary because of incorrect or incomplete data, ML can anticipate what is wrong / missing from past transactions and remediate. This is the Auto Reconciliation.
  2. Given unstructured data elements may reside in fragmented platforms or organizational silos, the Firm must have an intelligent way of integrating and mutualizing itself with minimal intervention. An ETL or data feed may look appealing initially, however, these are error prone and do not remediate the manual reconciliation tasks for exception management.  Alternatively, a smart contract based approach can streamline your rule-based processes to create a single data source. 
  3. Seamless integration to minimize the disconnect between applications. The goal is to create an environment where reconciliation is no longer required. Ideally.

We have partnered with Digital Asset to outline a solution that brings together an intelligent data extraction tool, a DAML smart contract and a capital markets focused integration partner that will reduce manual end to end reconciliation challenges for the enterprise.

Problem statement & Traditional Approach

Given that most enterprise business processes run through multiple disparate applications with their respective unique databases, it has been proven a monolithic application approach is close to impossible. And not recommended due to issues with a Monolithic application architecture. Traditionally, this challenge has been addressed using integration tools such as an Enterprise Service Bus, SOA, where the business gets consumed in the cycle of data aggregation, cleansing and reconciliation. Each database becomes a virtual pipeline of a business process and an additional staging layer is created to deliver internal/external analytics. In addition, these integration tools are not intelligent as they only capture workflows with adapters (ad hoc business logic) and do not offer privacy restrictions from the outset. 


The Digital Assets DAML on X initiative extends the concept of the Smart Contract onto multiple platforms including Databases. The DAML on X interfaces with the underlying Databases using standard interfacing protocols, the Smart Contract mutualizes the Data Validation rules as well as the access privileges. Once you create a DAML smart contract, the integrity of the process is built into the code itself, and the DAML runtime makes disparate communication seamless. It is in its DNA to function as a platform independent programming language specifically for multi-party applications.

Without replacing your current architecture such as the ESB, or your institutional vendor management tool of choice, use the DAML runtime to make application communication seamless and have your ESB invoke the necessary elements of your smart contract via exposed APIs .  

Handling Privacy, Entitlements & Identity Management

Every party in the smart contract has a “party ID” plugged in directly with your identity management solution that you are using institutionally. You can even embed “trustless authentication”. 

The idea is that entitlements/rights & obligations are baked directly into the language itself as opposed to a normal business process management tool where you build out your business process and then put the entitlements/ marry them in phase 3 of the process – only to realize that workflow needs to change. 

DAML handles this upfront – all of the authentication is taken care of the persistence layer/IDM that you decide on. The smart contract template represents a data scheme in a database and the Signatories/controllers in our example represent role-level permissioning of who can do what/when and who can see what/when

 The image below shows how the golden source of data is generated.

It is a purpose built product that contains automatic disclosures and privacy parameters out of the box. You don’t need to keep checking your code to see if the guy who is exercising command is actually allowed to see the data or not. All of this is within the scope of the DAML runtime. 

Already kickstarted your enterprise blockchain strategy?

Firstly, Amazing! Second, since DAML Smart contracts can run on databases or distributed ledgers of your choice (Fabric, Corda etc. ), it’s a unique solution that gives you the flexibility to get started with the application building and even change underlying ledgers at any point. You can also Integrate between multiple instances. I.e. If you are running a DAML app on Fabric and another DAML app on corda, both apps can talk to one another. 

The key takeaway here is that most enterprises are held up with determining which ledger meets their needs. With its intuitive business workflow focused approach, developing your DAML applications while you select your ledger fabric can expedite revenue capture, implement consistent enterprise reporting and reduce the burden of reconciliation – the smart contract through to the integration layer is completely portable. 

COVID 19 and the associated social distancing and quarantine restrictions, has dictated new measures for business standards, forcing companies into a major overhaul in the way they work. Remote Working is just one key part of this change, this impacts workplaces and the global workforce significantly.

This cause-effect relationship is now at the forefront, fundamentally transforming existing business models, business practices, business processes, and supporting structures and technology. According to Gartner, “CIOs can play a key role in this process since digital technologies and capabilities influence every aspect of business models.”

Business process management ( BPM)  was the primary means for investment banks and hedge funds  to make internal workflows efficient. In investment banking, BPM  focused on the automation of operations management by identifying, modeling, analyzing, and subsequently improving business processes.

Most investment firms have some form of BPM for various processes. For instance, compliance processes appear to have some form of software automation in their workflows at most investment banks and hedge funds. This is because banking functions such as compliance, fraud, and risk management exert pressure to develop cost-effective processes. Wherever Automation was not possible,  manual labor-intensive functions were outsourced through KPO’s to comparatively cheaper South-East Asian destinations thereby reducing costs. With COVID-19’s social distancing norms levied, this traditional KPO model to handle Front, Middle, and Back Office processes is cracking up as it relies on several people working together. There is an urgent need to rethink these processes with a fresh vision and build intelligent systems that are remotely accessible, for handling all such processes like KYC, AML, Document Digitization, Data Extraction from Unstructured documents, Contract Management, Trade reconciliation Invoice Processing, Corporate Actions, etc.

Now more than ever, organizations need to embrace agility, flexibility, and transformation. As per KPMG, the modern enterprise must become agile and resilient to master disruption and maintain momentum. Optimizing the operations process can transform the business to support lean initiatives that lead to innovation—an aspect that can no longer be ignored. With the help of cross-functional domain experts, organizations can discover and subsequently eliminate inefficiencies in the operations and business processes by identifying the inconsistencies, redundancies, and gaps that can be streamlined.  Intelligent Workflow initiatives and goals align business improvement with business objectives and visibly reduce the probability of negative ROI and impact on projects and initiatives.

Using new technologies like AI and Machine Learning, organizations can quickly adapt and improve with precision and gain the multi-layered visibility needed to drive change and reach strategic goals across an enterprise. The proper use of Artificial Intelligence can solve business case problems and relieve enterprises from various technology or data chokes. AI techniques can help traditional software perform tasks better over time, thus empowering people to focus their time on complex and highly strategic tasks.

Best-Practices for Adoption of AI-Based BPM Solutions

Before moving into AI-based process automation, a crucial idea for investment banking business leaders to realize is that they need to shift their perspective of emerging technology opportunities. Many AI projects will be deployed before they return the desired result, 100 % of the time.

AI ventures require ample algorithmic tuning, so it can take several months to reach a state of high precision and confidence. This is important because banks, in their core business processes, cannot jump into large AI projects and expect seamless functions across the board straightaway. Any large project would result in a temporary impediment to the specific business process or push it into a downtime before the AI project is complete. 

So bankers need to develop a mentality of try-test-learn-improve while considering AI to gain confidence in data science projects. Also, it is advisable to choose an AI service provider with extensive experience and knowledge of the domain, to achieve desired results. An investment firm should expect to have a prototype solution in the first iteration which they need to improve by incorporating user feedback to correct minor issues to achieve an MVP status. The smaller and shorter projects, that focus on improving a particular sub-process within the entire process workflow are better suited for investment firms. This approach allows small AI teams to develop and deploy projects much faster. Such projects are advisable since they bring a significant positive business impact, while still not hindering the current workflow and process.  

Such attitudinal changes are decisive shifts from the conventional approach to technology that investment banking leaders have taken. This is presumably not something firms can change overnight and requires careful preparation, planning, and a strategy to help the workforce have an incremental improvement approach to business processes. These fundamental shifts demand that leaders prepare, motivate, and equip their workforce to make a change. But leaders must first be prepared themselves before inculcating this approach in their organizations.

Our interactions with CXO’s in the investment banking industry indicate that process optimization applications of AI can bring a  disproportionate benefit in terms of operational efficiency,  sorely needed in these challenging times.  

Magic FinServ offers focussed process optimization solutions for the Financial Services Industry leveraging New Gen Technology such as AI, ML, across hedge funds, asset management, and Fintechs. This allows financial services institutions to translate business strategy and operational objectives into successful enterprise-level changes, thus positively impacting revenues and bottom-line growth. With the relevant domain knowledge of capital markets and technological prowess, our agile team builds customized turnkey solutions that can be deployed quickly and demonstrate returns as early as 2 weeks from the first deployment. Discover the transformation possibilities with our experts on AI solutions for hedge funds and asset managers. 

Write to us mail@magicfinserv.com to book a consultation.

Firstly, a sincere wish for safety and wellbeing of all, my deepest sympathies for those who fought valiantly and prayers for those who continue to fight. As our communities fight for lives and livelihood, we as  business leaders shoulder the responsibility to help our organizations and the world arise strong and resurgent. 

Magic FinServ is one such company where we could, overnight, move our operations into a remote working model, with all the security and confidentiality norms intact. This was only possible because we are a cloud-first company, effectively running our business on the cloud while supporting numerous clients across geographies. Amidst efforts to minimize disruptions to our daily business operations, we were also highly cognizant of the increased security vulnerabilities arising out of this paradigm shift. We made some hard and expensive choices to keep our global teams functioning well during severe lockdowns. We improvised and made possible actions that we would have never dreamt of and we will continue to make difficult choices in the months to come. There is no “Going Back to Work” as we know it today as several aspects that we took for granted will no longer be required while repeated lockdowns and disruptions will  become the norm. 

The Rising popularity of Cloud

As per a survey conducted by Forbes, in early 2020, as many as 50% of Financial Services leaders had placed Cloud BI as their top priority this year. And in a post-COVID world, the cloud is definitely going to be the center of all technology. Cloud, thus moved quickly from being an IT cost-center of a hedge-fund to an essential component for running a nimble, agile, and highly scalable organization that operates on a fully variable cost model, and most importantly securely accessible to all stakeholders. Smart managers will seize this opportunity to design a whole new organization from a brand new set of principles as virtual is now our new reality.   

Cloud for Hedge Funds

As the situation around COVID19 having unprecedented business implications arose, a key question also emerged that begs an answer:  Why are only some companies thriving and handling this disruption well? From a technical viewpoint, the companies that are handling it well are either the SaaS companies or those that have set themselves up predominantly operating on the cloud. 

For hedge funds, asset managers, and other capital market entities, the cloud has capabilities to support front, middle and back-office functions. This includes everything ranging from business applications and client relationship management systems to data management solutions and accounting systems. Cloud emerged as a path of choice but its considerations for capital markets are different than ones applicable for other businesses, owing to industry regulations, complex reporting, the sensitivity of data, and compliance requisites of the industry. 

As a provider of Digital Technology (AI / ML / Blockchain / Cloud) Services, Magic FinServ has a unique proposition that makes deploying and maintaining a capital markets cloud initiative time-bound, cost-effective, and highly secure. Our deep understanding of the vertical enables us to be a strategic partner as our customers design their organization to take on the new challenges and opportunities. 

Getting Started With Cloud: Time for a Health Check

A highly recommended first step towards the cloud, for any hedge fund or asset manager,  would be a comprehensive assessment of your organization for cloud readiness and maturity. The assessment of your IT infrastructure and operations for business continuity, reliability, scalability, accessibility, while maintaining the same levels of security and confidentiality as physically secure operations centers, is rather imperative so you can plan and weather the disruptions to emerge stronger and leaner. Well begun is half done stands true for cloud as well. 

At Magic FinServ, we developed a 128 point assessment offering that measures your organization on these critical aspects. We understand the operational, security, and confidentiality demands of the buy-side industry and we assess your ability to meet these exacting demands. Increasingly, your customers, investors, and other counterparties will also assess you on these parameters, so a comprehensive assessment study will help you respond to these queries with confidence.

The assessment need not be a time consuming, expensive affair since we have customized and optimized our assessment for the buy side-industry. A typical small to midsize operation would need about 2-3 months. It is a relatively small time investment that will identify the gaps and make recommendations to bridge these gaps so that your onward cloud journey is smooth, in-line with your business objectives and saves you from expensive mistakes later. 

Migration and Deployment to Cloud

According to ValueWalk, almost 90% of hedge funds will move to the cloud, in the next 5 years. Migration / Deployment to cloud was often seen as an IT cost initiative earlier, however, as firms move from a CapEx to an OpEx preference, it is now increasingly becoming a key element of a whole new way of operations. 

Most organizations in the financial services industry take a phased approach of moving to the cloud, with multi-year plans. They start with setting the framework and testing the waters with an initial few applications, usually business applications like Email, File Sharing, OMS, Risk, and CRM, moving them to a hosted model. The benefits of adopting this hosted model include gaining a highly available infrastructure of the cloud providers. This is typically followed by migrating data to the cloud and finally moving the bulk of the workload in a lift and shift mode. 

Somewhere in this journey, security is addressed. What is often missing in this  journey is the aspect of transformation, especially when there is the burden of legacy, monolithic applications that are in dire need of modernization and transformation. The proper planned and orchestrated migration to cloud is an ideal opportunity to address this long pending initiative.

Magic FinServ, with its focus on capital markets vertical, has developed an Integrated, Incremental, and Scalable method of incorporating cloud into the customer’s ecosystem. An integrated approach to Applications, Infrastructure, and Security helps us come up with a robust and holistic plan. The approach uses as many native services of the cloud provider as possible making it easily adaptable to the cloud environment, bringing in cost efficiencies. A segmented and incremental approach to Applications (Microservices), Infrastructure and Security (DevSecOps, Micro-Segmentation) results in moving incremental and prioritized workloads to the cloud, helping utilize multiple cloud environments thereby leveraging the best of all the providers and something that is integrated well into the hedge fund’s specific environment. Implementing the Infrastructure-as-code helps in making the cloud environment extremely manageable, scalable, simplified, and secured. 

This systemized incremental approach has helped entities to achieve rapid time to market and highly optimized cost of deployment while bringing incremental benefits very early in the deployment life cycle. Our objective remains to make this transition as much self-funded and sustainable as possible thereby delivering a high ROI. 

Managing the Cloud Environment Effectively

The Cloud is democratizing the consumption of IT Services and driving innovation. However if not governed effectively, this sudden freedom and access could spiral your  cloud’s running and managing costs, while making it susceptible to security risk. The democratization has been made possible by public cloud providers making available out of the box capabilities, or native cloud capabilities. However, these additional capabilities come at the cost of additional spend as well as some loss of flexibility. Optimal management of such capabilities is necessary to maintain a balance between time to market on one hand and cost, flexibility, and security on the other.

Magic FinServ has developed an integrated operations and IT monitoring support capability to provide customers with a SaaS type model, enabling the smooth and uninterrupted running of business operations incorporated in the architecture itself. Automated release and deployment, coupled with automated infrastructure testing help make change and configuration management easy and fast. Since uptime is crucial to operational efficiency and profitability, the high-touch support model across L1, L2, L3, ensures quick resolution of any issues and congruence across functions. 

Handling Enterprise Data

A key element of the buy-side industry is the management of enterprise data. This not only impacts upfront costs but also could potentially impact business outcomes. Magic FinServ, as a member of the EDMCouncil, ensures that an enterprise data architect is a part of our cloud center of excellence, as a best practice. We have been supporting enterprise data initiatives for several buy-side organizations over the years and hence are abreast of the inconsistencies that may be caused by customizing underlying data models to suit specific organization needs. Our industry-driven high touch support services help in managing these inconsistencies, especially as we help move data to the cloud or the constant upstream and downstream in hybrid cloud systems. 


As Asset Managers and Hedge Funds make this move to the cloud in a new paradigm, they should ideally make the move with trusted and industry-oriented managed service providers, since this is a tectonic shift in their operating model. Ultimately the move to the cloud is not just a technology choice, it’s a business decision.

Every now and then, FinTech service providers approach Product Managers seemingly insulted by the question “have you considered amplifying your DevOps team or optimizing your Cloud Strategy with outside help to scale faster and cheaper?”.

Convincing these naysayers can sometimes make you feel like you are assuming a “bad cop” parental role – i.e. becoming someone who knows what’s good for you based on extensive experience, even when you may not see it or believe them at first. So let’s jump right into the spiel.

There are three imperative considerations to implementing a “Buy, Build, Partner” strategy that rest on the premise (which Silicon Valley seemingly forgets from time to time) that time and material resources are finite: Leverage Open-source, Protect your Mindshare and Trust Inorganic Growth. 

Steve Jobs once said, “it doesn’t make sense to hire smart people and tell them what to do; we hire smart people so that they can tell us what to do” –  Even for Apple, a maximum-security IP fortress, this did not mean augmenting payroll. In 2012, Apple revealed its 15-year association with the likes of Infosys and Wipro, implying Apple’s journey to a market cap of 1 trillion dollars was not achieved by internal hiring alone. The good news is, this is only getting easier to achieve, the bad news is too few emerging names are following best practices to accelerate ahead. Instead, the C-Suite is often at the mercy of the apprehension and fear of internal (usually technical) “gatekeepers”. Let’s take a look at 3 key components of a “Buy, Build, Partner” strategy in 2020, which assumes your partners and service providers aren’t seeking multi-year/million-dollar engagements, that they adapt to your servicing time zone with suitable SLAs and that they will not compromise on quality. 

1.The ubiquitous existing Open- source tech stacks today do not require you to reinvent the wheel

  • The famous four (Apple, Google, Microsoft, and Linux) have now been replaced with robust community-driven Open-source code that is not dependent on cyclical patches, provides real-time bug fixes and new enhancements, and can deliver results in T-0 vulnerabilities as opposed to proprietary solutions. Embracing the world of Open-source and applying your domain knowledge is how you get the biggest bang for your buck. 
  • For instance, Rasa: Open- source Conversational AI, has given multiple verticals (Airline, Retail, Healthcare, Financial Services, and counting…) the opportunity to create enterprise-grade intelligent virtual assistants that are well versed in the context of their industry. 

Extrapolate this tangible product approach to AI/ML solutions, data visualization, testing, cloud strategy and platform engineering with a range of emerging tech stacks such as Kubernetes, ELK, Kibana and Terraform. Take your pick and get in touch with me if you are looking to explore!

2. Protect your mindshare, build responsibly, keep costs low and hire for what you don’t know

  • Keep your team the right size and working on exciting stuff such as product development and feature building. A service provider with domain experts can easily handle manual QA, DevOps and migration projects that can be executed without the overhead (read: large fixed costs such as offices, servers, inventory) of doing it on your own. Note again for anxious readers: IP is not at risk, especially if your contract specifies that source code is to be handled and maintained by your firm. Decide on an outcome-based model that establishes clear deliverables. 
  • Burn rates should not make investors or leadership teams uncomfortable. As Venture Capitalist, Mark Suster warns, “a company’s runway should not fall below 6-7 months of cash on hand” and reminds us “high fixed costs and high debt rates killed many great companies in Dot Com 1.0”. Figure out a “Buy” strategy to keep sticky situations and rainy days to a minimum by increasing variable costs. This in turn, generates momentum for speed to market and allows you to maintain a position well ahead of your peers. 
  • Even though we are inundated with “self-help” advice on how to manage our personal lives and relationships, institutional introspection is underrated. It is equally just as important to identify and diagnose weak areas in your company from the outset. Then buy or hire those services from a vendor that spends day and night perfecting that exact skillset. 

3.The Butterfly Effect of Partnering on Business Development 

  • Do not underestimate the “Butterfly Effect” of your outsourcing partner’s ability to drive inorganic growth in unique ways. Unsuspecting partnerships have helped drive:
    • Geographical scale
    • Customer acquisition and adoption
    • IP augmentation 
    • Insights & analytics 
  • Choose the domain experts that can connect you to peers and establish these relationships. Just how Wipro and Infosys were able to leverage its internal IT projects with Apple to amplify adoption. Sewing a web of interconnectivity of Apple products with other clients’ business applications and adapting best practices continue to be a win-win for the iPhone/iPad maker as well as their outsourcing providers. 

Finally, the skeptics are not wrong to be wary of anything except “Build”. It  has become the dominant fall back approach for many emerging technology companies across Retail, Healthcare, FinTech and Blockchain after “outsourcing” earned a bad reputation over the last decade (read: overcharging, “landing and expanding”, and poor results). However, with the right governance, acknowledging that most engagements can leverage free open-source solutions with effective domain-specific frameworks, and creating equitable partnerships, a little bit more of “Buy” and “Partner” can get you where you want to go exponentially faster. 

Contracting as an activity has been around, ever since the start of the service economy. But despite it being a well-used practice, very few companies have mastered the art of managing contracts efficiently or effectively.  According to a KPMG report, inefficient contracting leads to a loss of 5% to 40% of the value of a given deal in some cases. 

The main challenge facing companies in the financial services industry is the sheer volume of contracts that they have to keep track of; these contracts often lack uniformity and are hard to organize, maintain and update on a regular basis. Manual maintenance of contracts is not only difficult but also cumbersome and prone to multiple forms of errors.  Also, it poses the risk of missing important deadlines or missed scheduled follow-ups, as written in the contract and could potentially lead to expensive repercussions.

Contract management is a way to manage multifarious contracts from vendors, partners, customers, etc. so that data from these contracts can be easily identified, segregated, labeled and extracted to be used in various cases and also updated regularly. 

Recent technological advances in Artificial Intelligence (AI) and Machine Learning, are now helping companies resolve many of the contracting challenges by delivering efficient contract management as a seamless automated solution. 

Benefits of Using AI in the contract management lifecycle

Basic Search

AI can help in enhancing the searchability of the contracts including clauses, dates, notes, comments and, even metadata associated with it. The AI method used for this purpose is called natural language processing(NLP) and the extraction of metadata is done at a granular level to enable the user to search from the vast repository of contracts in an effective manner.

Example: This search function would be extremely useful for the relationship managers/chat-bots to answer any customer queries pertaining to a particular contract. 

Analysis and Diagnostic Search:  AI can be used to proactively identify expiry dates, renewal dates, follow-up dates or low KPI compliance, and then can be used to apply suggestive course of action or flag any alerts. Analytics can further be used to study and predict any kind of risks or non-compliance and therefore send a notification to relevant stakeholders for pending payments or negotiations.

Example: This can be effectively utilised for improving customer satisfaction as well as guide negotiations based on accessible information.

Cognitive Support: AI is highly sought for its predictive intelligence. AI’s predictive capabilities can be used to do an analysis of the existing contracts to understand contract terms & clauses. Its pattern recognition algorithms can identify points of parity, differentiations on pricing, geographic, products & services. Based on the predictive analysis, AI can provide suggestions for inclusion/exclusion of clauses, terms & conditions, etc when authoring new contracts. 

Example : AI systems may automatically predict and suggest clauses pertaining to NDA (non-disclosure agreement) based on the historical contracts that have been previously processed and the events associated with it.

Dynamic Contracts: Advanced AI can be used to build an adaptive dynamic contract. Based on the past data and by taking into account external factors such as market fluctuations, currency exchange, prices, labor rate, changes in laws and regulations, etc, AI algorithms can create a contract. Such a contract would require auditing by an expert but nonetheless would reduce the effort required to generate the contract.

Example: AI can be used to assess existing contracts for making them GDPR (General Data Protection Regulation) compliant. It will insert the relevant data privacy terms and conditions into the contract and subsequently notify the concerned stakeholder about the changes in the contract, so they can be verified.

Challenges in contract management with AI-ML

The use of AI and Machine Learning for contract management is highly promising but it is also challenged by few limitations. 

Machine Learning (ML) is only as effective as the training data that has been used to train the ML algorithms. Therefore, before any AI-ML application is put into practice, an exhaustive dataset of contracts must be developed and then classified, sorted, labeled, and retrieved based on the metadata. This would provide the base, as training data, for AI to build up and therefore put the ‘intelligence’ in the Contract Management process.

For the exhaustive dataset to be developed, all the contract data must be assimilated together. In many organizations, the contracts are still hard copies lying in cabinets. Approximately 10% of written agreements aren’t even traceable. Even when digitized contracts are available, for the AI machine to read these contract’s insights, they must first be in uniform contents. This not only requires scanning of all the documents but also the ability to extract the meaning of the content in the contracts. 

Overcoming the challenges

In order to make the contract portfolios AI-ready, the first step is to  digitize these contract documents. This can be done using OCR (optical character recognition). OCR reads the physical document as a human eye would read it and converts into digitized text which can easily be searched with ML formulas. While it may be too onerous to scan all historical contracts, this purpose can be accomplished by using a CMS (contract management software), which is capable of converting the documents into machine readable filed, thus making a significant data pool. Then AI, can be used to use this data to gain relevant insights. When AI algorithms access huge pools of data, its ability to decipher patterns and provide insights becomes much stronger. The predictive insights can be achieved by incorporating NLP (natural language processing). NLP allows contact groups to identify when contracts have deviated from defined standards. This makes the approval process, negotiation process much faster when the stakeholder is aware of the current contract version deviation from standards. NLP is also used in reporting risk based on language meaning rather than just string matching. For example, identifying those contracts which are about to expire and starting their renewal process.


Potentially, AI in contract management will change the contract management lifecycle to uplevel the strategic role of the contract managers, which would position them in a superior spot while negotiating terms of contracts. It can also help tremendously in strategic planning, risk management, supplier search, and final selections. Thus enhancing the efficiency and effectiveness of category managers. AI innovation continues to play a vital role when contract managers educate themselves and ensure that their contract processes are fully digitized and AI-ready.

Get started with Artificial Intelligence by booking a workshop with us today!

According to ‘The Pulse of FinTech 2018’ report by KPMG, fintech startups bagged over $111 billion in investments across 2,196 deals. The technological evolution of fintech startups has outmatched that of traditional financial services by many leagues. Not only has this served to disrupt the space by directly pitting startups against tech giants, but has also transformed the tools of global trade and commerce.  One startup even estimated the total cost of the recent US government shutdown right down to its last cent.

Various emerging technologies have given rise to new business-technology startups that didn’t even exist ten years ago. It’s no surprise then that investments in sectors of regulatory technology (RegTech) have tripled from USD 1.2 billion in 2017 to USD 3.7 billion in 2018.

Meanwhile, the versatile nature of blockchain technology is being used to craft specific solutions for capital markets, everything from cryptocurrencies to capital issuance. Even the simplest technology tools in the hands of FinTech are being used to enhance point-of-sale customer experience while also controlling fraudulent transactions.

However, the most recent breakthrough amongst all these has been the rise of FinTech startups in capital markets. Since 2010, capital market infrastructure (CMI) linked FinTechs has grown nearly 300% since 2010, offering solutions to tackle complex front, middle, and back-office problems.

Why Startups?

For startups, success amidst cut-throat competition isn’t easy to achieve. ‘Nine out of ten startups fail’ is an oft-repeated maxim. Compliance and legal issues, along with inadequate funding have been the primary roadblocks in this quest. But despite these difficulties, fintech startups are ideally placed to resolve longstanding issues in the capital markets industry. These issues include high structural expenses, stagnant revenues, and enormous capital costs.

These challenges combined with the changes demanded by regulators have led to a decline in the returns on equity (ROE) for investment banks year after year. CMI providers (CMIPs) are compelled to deliver regulatory changes, such as the shift toward compulsory central counterparty clearing of over-the-counter derivatives, or external changes in customer behavior within the investor scenario. These pressures and complexity typically combine to cause organizational fatigue. This leaves high-level management with hardly any scope to invest in initiatives that can increase ROE.

Costs associated with the development and implementation of regulatory compliance systems are unavoidable, but costs incurred by investment banks to maintain disparate systems are unnecessary. Despite wanting to harness cutting edge technologies, they get caught up in the devil’s snare of legacy infrastructure. Instead, they need to leverage an external fintech solution to achieve their goals more optimally. Since startups aren’t tied to any entrenched IT architecture, they can accelerate cutting-edge product and service development.

The agile infrastructure of fintech startups has been proven to improve productivity by 25 to 30% within 6 to 18 months. CMIPs are already being empowered by fintech startups towards solving many of their challenges and are poised to make a significant impact on the capital markets industry. What they are not as certain about is knowing which specific technologies hold the key to helping them most efficiently resolve their challenges and the best collaboration methods when working with fintech firms.

Balancing the Equation

Sopnendu Mohanty, the Chief Fintech Officer at the Monetary Authority of Singapore (MAS), stated that while we normally understand fintech as a technology firm performing banking activities, the reality is only a fraction operate within the banking segment. Most startups are assisting in the digitization of banks. And while mergers and acquisitions by larger firms have been thought to benefit startups, recent developments along the CMI value chain suggests quite the reverse. 

Most startups assist banks by modernizing their dated infrastructure by becoming vendors and partners. Alliances such as the one between ING and the automated lending platform Kabbage are proof that conventional banks are looking to present new offerings to their customer base, and move to a more streamlined, agile, ‘plug-and-play’ model. 

They will continue to drive greater productivity in post-trade services like regulatory reporting and risk management by deploying automation and robotics. We are already witnessing capital markets seeking our next-gen artificial intelligence solutions to cope with their growing data streams and blockchain to optimize their transaction exchanges. Startups are well-positioned to bring in new digital markets, serve as an alternative to conventional access to capital and enhance the security of global financial systems.

Making Finance Relevant

The disruption brought about by fintech startups is indicative of the agile, mobile-first approach that customers across most sectors want. For the record, smaller startup fintech companies are the most active in the CMI space. Despite their considerable data pools and comprehensive resources, technology giants are being given a run for their money by these startups due to their enhanced agility and lack of legacy burdens.

They operate with existing providers rather than against them, and most of their products act as components within the industry, making conciliation much easier. Fintech startups have also been heavily backed by venture capital investment from the CMI sector and this trend is also on the rise. “The Fintech 250” list of 2018 by CBInsights’ further reinforces this reality, with Kabbage, incidentally, being the best-funded fintech startup under business lending and financing.

Ultimately, fintech startups are defying the norm by creating a space for established financial giants to leverage new technologies in a way that will bring about radical but meaningful change. There is no denying that fintech companies will continue to pioneer and outpace traditional financial giants as their technological innovation brings an unparalleled depth of value for capital markets in the 21 st century.

A New World of Banking

The rise of fintech in the last half decade or so has taken the financial world by storm. Research suggests that there are now more than 7,500 fintech firms around the world which have raised nearly USD 109 billion in investment. The sector raked in a record breaking USD 54 billion investment in 2018 and USD 10 billion within the first quarter of 2019. 

Clearly, the hunger for fintech is growing, and with it, the fear among banks and traditional financial business about potentially lost revenue and customers. The fact that customers are increasingly preferring these non-traditional competitors does little to calm the uncertainty. 

As established players in the financial services industry wake up to this new business dynamic, the majority are attempting to collaborate with fintech: to leverage its ever-expanding ecosystem, turn the innovation to their favor, and address the concerns that arise with their business being at risk. Research reveals that as many as 82% of incumbents in the financial industry sector expect to enhance their partnerships with fintech players, going forward. 

Fintech – A Force to Reckon With

Fintech can be rightly characterized as a movement that has brought disruptive and transformative innovation in financial services through cutting-edge technology. Unlike traditional financial institutions, fintech startups have the advantage of not being burdened by age-old regulatory constraints, legacy systems and processes. This has allowed them to move faster and come up with solutions that compete directly with conventional methods of financial service deployments. 

Another aspect that has fuelled the rapid progression of fintech is an entirely new generation of well-informed and connected mobile consumers who continue to reshape financial service requirements. With time, fintech companies have managed to rope in these digital natives with smart banking platforms. This has given them a head start in the race to capitalize on the ‘1.7 billion billion adults, who according to World Bank’s Global Findex Database 2017 are naturally inclined towards smart fintech services.

On the other hand, major players in the financial services sector and capital market incumbents have failed to gain precedence on this front. Burdened with massive structural costs, hefty capital charges, and stagnant revenues, this sector continues to score low on the innovation index. Additionally, the relentless pressure to stay compliant and adhere to regulatory guidelines also leaves organizations short of bandwidth to invest time and resources in initiatives that can improve margins. 

There’s no denying that in the digital age, customer experience (CX) is the final battleground for businesses. And here, fintech has a natural advantage. By placing CX above everything else, fintech offerings have been able to provide their users with unending benefits. For instance, by leveraging smart application program interfaces (APIs), fintech companies are able to nurture a healthy community of third party partners around their native software problem. Open APIs allow fintech players to expand their customer services by enabling third party partners and developers to create their own apps and layers into the middleware. 

Apart from this, the algorithmic design and data-rich environment in this sector has proven ideal for machine learning (ML), artificial intelligence (AI) and blockchain-driven product deployments. Developers today are able to leverage these technologies to simplify and optimize cumbersome and effort-intensive processes such as compliance, credit checks, risk management, and P2P payments. 

But there’s good news. These technologies can yield similar results in capital markets as well, provided they are strategically implemented in the right areas. For instance, process automation with Robotic Process Automation (RPA) can help organizations working in the capital markets space replace manual legacy systems, make the systems compliant with Know Your Customer (KYC), Anti-Money laundering (AML) and other regulations, reconcile reports and connect middle and back office functions. On the other hand, more contemporary technologies like AI can simplify cumbersome processes such as trade settlement, compliance reporting, contract management and accounts payable. 

Blockchain, is another area which promises to yield unprecedented gains for capital market players. No wonder, the financial services industry has witnessed some of the biggest use cases of this technology. For example, in digital trading, blockchain is helping organizations reduce settlement times. In the current trading architecture, a single transaction can take days to settle. A blockchain-based settlement solution significantly curbs this turn-around time. A cryptocurrency token that serves as a proxy to a particular transaction is immediately transferred to the wallet of the beneficiary, confirming the completion of the settlement and ledger update.   

Extrapolating into the Future of the Financial Services Sector

With the gradual implementation of next-generation technologies like ML, neural networking with long/short term memory, Blockchain,  AI and robo-advisors, fintech will continue to gain trust and popularity among customers . 73% of millennials are eager to shift to a new financial paradigm where service products from technology companies like Google, Apple, Paypal, and Amazon are more exciting, intuitive, and CX-friendly than anything traditional financial players currently provide.   

The times are clearly changing. Fintechs are fast opening the virtual vault doors to innovation in the once impenetrable banking and the financial services sector. Can traditional players take the bold steps necessary to match the frictionless experience that’s the new norm, or will they eventually lose grounds to the new entrants? Only time can tell. 

Security Token Offering seems to be the next hype to utilize BlockChain concepts and transform the current security instruments (Equity, Debt, Derivatives, etc) into digitized security. STOs have gained popularity and momentum in recent times due to lack of regulations in the ICO world with a lot of outliers for most of the ICOs in 2018. There are many Startups that are building platforms by utilizing programmable blockchain platforms like Ethereum. Recent developments in STO platforms seem to be moving in the direction of building an Ecosystem with defined standards as well. By seeing lots of traction on GitHub towards standards like ERC-1400, ERC-1410, ERC-1594, ERC-1643 and ERC-1644, it has given us the opportunity to think about how can a technology company like us (Specialized in ensuring Quality standards for Blockchain-based applications on Ethereum) can contribute to this. We started our journey in defining the Complete STOs processing cycle in the context of real-time usage (from a functional perspective) with underlying Ethereum platforms (from a technology perspective).

It is highly important that we list down all the major participants & their roles before actually defining the  STO lifecycle :

  1. Issuers – Legal entity who develops, registers & sells security for raising funds for their business expansion.
  2. Investors – Entities who are ready to invest in securities to expect financial returns.
  3. Legal & Compliance Delegates – Entities that ensure all participants & processes are complied within the defined rules & regulations by the jurisdiction.
  4. KYC/AML service providers – Entity which provide KYC/AML for required participants.
  5. Smart Contract Development communities like Developers, Smart Contract Auditors, QA Engineers.

Most of the companies claiming to provide STO platforms are using Ethereum as the underlying programmable blockchain platform with few exceptions. The rationale for using Ethereum as the first choice is – It is a Turing Complete platform to build complex decentralized applications by defining logics inside Smart contracts (Solidity is the most favorable programming language among developer communities). Parallelly, Ethereum is also getting matured, secured and improved on performance with scalability by introducing lots of new features and improvements. There are very few who are utilizing other platforms apart from Ethereum to build their own STO processing platforms and some of them are trying to build a completely new blockchain platform dedicatedly designed for STOs. The last approach seems to be too optimistic as it might take years to build such a  system whereas the current momentum around STOs does not seem to wait that long.

Basis the above, we can now define the generic STO lifecycle from a functional standpoint into 2 phases as below: Primary Market

  1. To issue STO by Issuer
  2. To invest in STO
  3. Secondary Market to trade STO on either on Exchanges or Over The Counter

Primary Market

  1. To issue STO by Issuer –
  1. Registration of Issuer
  2. Creation of STO Token
  3. Approval from Legal & Compliance for STO
  4. Issuance of STO post Legal & Compliance approval  
  1. To invest in STO by Investor –
  1. Registration of Investor
  2. KYC/AML for Investors
  3. Whitelisting of Investors for STOs post KYC/AML
  4. Investment in STO for allowed STOs based on whitelisting of corresponding STO

Before we actually get into the technical insight of underlying blockchain technology, we need to define the STO platform technical architecture from a  user perspective. Each STO platform that exists in any state in today’s world has –

  1. A Presentation layer (User Interface with any chosen front end technology, Integration with Wallets)
  2. A Business Layer (JS libraries to provide an interface to interact with Smart Contracts)
  3. A Data Layer (Ethereum data storage in blocks in the form of key-value storage)

Now let’s define a high-level overview from a technical standpoint by assuming that the STO platform is using Ethereum as an underlying blockchain platform ( assuming that the Backend Layer has been set up already) –

  1. Creation of an external account for all participants to bring everyone on Ethereum blockchain
  2. Defining transactions for Off-Chain and On-Chain for all activities defined for Issuer and Investors
  3. Merger of Off-Chain data with On-Chain data
  4. Develop Smart Contracts
    1. Standard smart contract to be built for each STO depending upon Jurisdictions for generic processes among required participants
    2. STO specific Smart Contract to be built for implementing business/regulation rules
    3. Smart contracts with all business logic especially for transaction processing

Based on the expertise of our group, Magic FinServ can contribute in a very big way in the development of Smart Contracts (Written in Solidity) along with Auditing of contracts.
For more details visit https://www.magicblockchainqa.com/our-services/#smart-contract-testing

In the next part, we will detail out all the above mentioned high-level technical overview with high-level functional overview followed by more insight on all these defined functional & technical flow.

When ERC-20 Standards came into existence, it eased down the ICO token interoperability across wallets & crypto exchanges for all ERC-20 compliant tokens. Having standards for any process not only helps to have bigger acceptance but also improves interoperability to build up an ecosystem. Being a technology obsessed firm, we’ve always encouraged standards to be in place. An acceptable standard not only helps developers (One of the strongest stakeholders in the ecosystem who have the responsibility to provide workable solutions by using available technology) to build  the ecosystem but also leads to minimal changes for implementing interoperability. In today’s world, there is no system in existence which does not raise any error /failure in real time usage . Using global standards provides us another vital advantage of finding a resolution for such errors/failures as  these cases would have already been resolved by the tech fraternity earlier.

Today, it is of utmost importance to have standards that can not only integrate multiple systems (STO Platforms, Wallets and Exchanges) with minimal changes but also make security tokens easily interoperable across wallets and exchanges. Security Token Offerings can’t be an exception for not having standards when they seem to have the biggest and most complicated technological advancement for transforming the existing world of security to Digitized security with automated processing over traditional blockchain technology.

The recent traction on ERC-1400 (now moved to ERC-1411) has helped towards defining standard libraries for the complete STO life cycle especially for on-chain/off-chain transactions This compilation of requirements has got the technology folks globally excited as this has the mettle to ease down the complete STO lifecycle. It completely makes sense that lots of individuals are very excited to see such a good compilation of requirements from various involved participants with probable interface that can ease down the complete STO lifecycle. Github, for instance has a lot of real time developers participating in discussions to share their experiences as well.

Ethereum Standards (ERC abbreviation of Ethereum Request for Comments) related to regulated tokens

The below standards are worth a read to understand in depth about the rationale behind targeting more regulated transactions based on Ethereum tokens –  

  1. ERC-1404 : Simple Restricted Token Standard
  2. ERC-1462 : Base Security Token
  3. ERC-884 : Delaware General Corporations Law (DGCL) compatible share token

ConsenSys claims to have implemented ERC-1400  on the Github repository & named the solution as Dauriel Network.  GitHub says, “Dauriel Network is an advanced institutional technology platform for issuing and exchanging tokenized financial assets, powered by the Ethereum blockchain.”  

ERC-1400 (Renamed to ERC-1411) Overview

Smart contracts  will eventually control all the activities like Security issuance process, trading lifecycle from an issuer & investor perspective as well as  event processing related to security token automatically. Let’s try to understand ERC-1400 standard libraries with respect to each activity for STO lifecycle :

  1. ERC-20: Token Standards
  2. ERC-777: A New Advanced Token Standards
  3. ERC 1410: Partially Fungible Token Standard
  4. ERC 1594: Core Security Token Standard
  5. ERC-1643: Document Management Standard
  6. ERC-1644: Controller Token Operation Standard
  7. ERC-1066: Standard way to design Ethereum Status Code (ESC)

All the defined methods inside each standard (Solidity Smart Contract Interfaces) at an activity level are (Pre MarketPrimary MarketSecondary Market)  and can be represented pictorially as below:

It is of utmost importance to distinguish Off-Chain & On-Chain activities  with those that will be processed outside STO platform before defining the mapping between standard libraries methods and activities across all 3 stages. Off Chain activities can be done outside the main chain of underlying blockchain platform then merged. However, Integration will be needed for all activities performed outside an STO platform where several standards (e.g. ERC-725 & ERC-735 define for Identity management) play an  important role.

All activities related to Pre-Market are supposed to happen outside the  STO platform as those are completely related to documentation like structuring the offering, preparing the  required documentation with all internal and external stakeholders including the legal team to ensure regulation compliances . To bring reference of all pre market documentation to the  STO platform, Cryptographic representation of all documentation can be used effectively.

Similarly, KYC/AML process can happen off-chain with proper integration on the STO platforms with proper identity management (standards around Identity management like ERC-725 and ERC-735).

ERC-1400 (now a.k.a ERC-1411) covers all activities related to primary and secondary market with proper integration to all off chain data which brings all related documentation/identity to the underlying blockchain platform on which the STO is designed.

Magic and its approach for defining ERC-1411 mapping

Team Magic is working continuously to define  the mapping between all defined methods with all real time activities of primary and secondary markets. A key part of our strategy is  to collect all requirements from various stakeholders like Security lawyers, Exchange Operators, KYA providers, Custodians, Business Owners, Regulators, Legal Advisor. Once we have all requirements collected then our experienced business analyst teams (Experts from Pricing, Corporate Actions, and Risk Assessment) take over and reconcile the requirements with ERC-1400 standards to not only map each requirement but also find out the gaps in the standards. Post this, our technology team  prepares the implementation strategy of all those standards by developing smart contracts in Solidity. Having an in-house developed smart contract for any specific case study (Provided by our Business Analyst team) helps us define Auditing of ERC-1400 specific smart contracts and the testing strategy for each contract as well. 

The original promise of blockchain technology was security. However, they might not be as invulnerable as initially thought. Smart contracts, the protocols which govern blockchain transactions, have yielded under targeted attacks in the past.

The intricacies of these protocols let programmers implement anything that the core system allows, which includes inserting loops in the code. The greater the options are given to programmers, the more the code needs to be structured. This makes it more likely for security vulnerabilities to enter blockchain-based environments.

The Attacks that Plague Blockchain

Faulty blockchain coding can give rise to several vulnerabilities. For instance, during Ethereum’s Constantinople upgrade in January of this year, reentrancy attacks became a cause for concern. These are possibly the most notorious among all blockchain attacks. A smart contract may interface with an external smart contract by ‘calling it’. This is an external call. Reentrancy attacks exploit malicious code in the external contract to withdraw money from the original smart contract. A similar flaw was first revealed during the 2016 DAO attack, where hackers drained $50 million from a Decentralized Autonomous Organization (DAO). Note the following token contract, from programmer Peter Borah, of what appears to be a great endeavor at condition-oriented programming:

contract TokenWithInvariants {   

mapping(address => uint) public balanceOf;

uint public totalSupply;

   modifier checkInvariants {

         if (this.balance < totalSupply) throw;


   function deposit (uint amount) checkInvariants {

     balanceOf[msg.sender] += amount;

     totalSupply += amount;


  function transfer(address to, uint value) checkInvariants {

        if (balanceOf[msg.sender] >= value) {

        balanceOf[to] += value;

        balanceOf-msg.sender] -= value;



  function withdraw() checkInvariants {

      uint balance = balanceOf[msg.sender];

      if (msg.sender.call.value(balance) ()) {

        totalSupply -= balance;

        balanceOf[msg.sender] = 0;

The above contract executes state-changing operations after an external call. It neither carries out an external call at the end nor does it have a mutex to prevent reentrant calls. The code does perform excellently in some areas, such as checking for a global invariant wherein the contract balance (this.balance) should not be below what the contract perceives it to be (totalSupply). However, these invariant checks are done at function entry in function modifiers, thereby treating a global invariant as a post-condition rather than holding it at all times. The deposit function is also flawed since it considers the user-mandated amount(msg.sender) instead of msg.amount.

Finally, the seventh line has a bug in it. Instead of,

if (this.balance < totalSupply) throw;

It should be,

if (this.balance != totalSupply) throw;

This is so because instead of checking for a stronger condition, we are now confirming a somewhat weaker condition of the contract’s actual balance being higher than what it thinks it should be.

These issues enable the contract to stock more money than it should. An attacker can potentially withdraw more than their share, heightening the danger of reentrancy even when the contract codes are watertight.

Overflows and underflows are also significant vulnerabilities that can be used as a Trojan Horse by non-ethical hackers. An overflow error occurs when a number gets incremented above its maximum value. Think of odometers in cars where the distance gets reset to zero after surpassing, say 999,999 km. If we affirm a uint8 variable that can take up to 8 bits, it can have decimal numbers between 0 and 2^8-1 = 255. Now if we code as such,uint a = 255;a++;

Then this will lead to an overflow error since a’s maximum value is 255.

On the other end, underflow errors effect smart contracts in the exact opposite direction. Taking an uint8 variable again:unint8 a = 0;a-;

Now we have effected an underflow, which will make a assume a maximum value of 255.

Underflow errors are more probable, since users are less likely to possess a large quantity of tokens. The Proof of Weak Hands Coin (POWH) scheme by 4chan’s business and finance imageboard /biz/ suffered a $800k loss overnight in March 2018 because of an underflow attack. Building and auditing secure mathematical libraries that replace the customary arithmetic operators is a sensible defense for these attacks.

The 51% attack is also prevalent in the world of cryptocurrency. A group of miners control more than 50% of the mining hashrate on the network and control all new transactions. Similarly, external contract referencing exploits Ethereum’s ability to reuse code from and interact with already existing contracts by masking malevolent actors in these interactions.

Smart contract auditing that combines the attention of manual code analysis and the efficiency of automated analysis is indispensable in preventing such attacks.
Solving the Conundrum
Fixes to such security risks in blockchain-based environments are very much possible. A process-oriented approach is a must with agile quality assurance (QA) models. Robust automation frameworks are also crucial in weeding out errors in coding and therefore strengthening smart contracts in the process.

In the case of reentrancy attacks, avoiding external calls is a good first step. So is inserting a mutex, a state variable to lock the contract during code execution. This will block reentry calls. All logic that changes state variables should occur before an external call. Correct auditing in this instance will ensure these steps are followed. In the case of overflow and underflow attacks, the right auditing tools will build mathematical libraries for safe math operations. The SafeMath library on Solidity is a good example.

To prevent external contract referencing, even something as simple as using the ‘new’ keyword to create contracts may not be implemented in the absence of proper auditing. Incidentally, this one step can ensure that an instance of the referred contract is formed during the time of execution, and the attacker cannot replace the original contract with anything else without changing the smart contract itself.

Magic BlockchainQA’s pioneering QA model has created industry-leading service level agreements (SLAs). Our portfolio of auditing services leverage our expertise in independently verifying blockchain platforms. This ensures decreased losses on investments for fintech firms, along with end-to-end integration, security, and performance. Crucially, this will usher in widespread acceptance of blockchain-based platforms. With the constant evolution of blockchain-based  environments, we are constantly evolving as well, to tackle new challenges and threats, while ensuring that our tools can conduct impeccable auditing of these contracts.

Blockchain technology first came with the promise of unprecedented security. Through correct auditing practices, we can fulfill this original promise. At Magic BlockchainQA’s, we aim to take that promise to its completion every single time.

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