The revised Payment Services Directive (PSD2) is set to change the role of banks in the financial services space. PSD2 aims to increase competition, innovation, and transparency in the EU banking sector, by opening up banking APIs to various trusted third-party services. PSD2 mandates banks and payment service providers to facilitate access to user account data and payment initiation via API, meaning that banks may no longer be the sole providers of online banking services, and instead begin acting as back-end utilities for other financial and non-financial service providers.
What to expect from banks
Banking APIs can be divided into five main categories: client data, account data, cards, payments, and credit.
Client data can act as an alternative to the various online KYC services we see today. Banking clients would be able to “login” using their personal bank details, providing the relevant third-party service with verified personal information, thereby fulfilling any KYC requirements. This allows financial and non-financial online services to piggyback on banks KYC processes, while allowing banks to monetize their KYC process outside of their own services.
Account information may include bank account numbers, balances, transactions, and similar information. Accounts APIs can be used in various applications such as wealth management, robo-advising, accounting, and applications for tracking personal and/or business expenditure.
APIs for credit and debit cards would allow third-party services to save user's bank details without PCI compliance implications. Cards payments are of course available through various payment providers, banking APIs may however increase the competitiveness in this space. Card issuance may also become available via API, meaning that bank and credit cards can easily be issued through non-banking institutions.
Payments APIs mainly revolve around initiating bank transfers and retrieving the statuses of transfers. End-users could for instance sign up for subscription based services with regular bank transfers, or pay bills directly from third-party portals.
Credit APIs include loans and repayments. Non-banking institutions could potentially offer credit to their customers seamlessly with banks operating in the background. Furthermore, credit consolidation and aggregation could become more sophisticated with access to more data.
What lies ahead?
Banks may either choose to embrace PSD2 and commence building an ecosystem with their banking products in the center, while other players may take a more passive approach and comply with the regulations in the most basic manner.
We expect banks with higher digital ambitions to deploy more extended APIs in order retain customer interactions and broaden access to their services in the highly competitive banking environment which is to come. Meanwhile, banks with lower digital ambitions may comply with the minimum legal API requirements, thereby holding on to their current customer base and having a lesser chance of creating a broader ecosystem.
Most banking APIs are expected to roll out in the start of 2018. Banks such as BBVA have already published API documentation and started building their developer ecosystem. Other institutions such as Nordea have published a roadmap and overview of services to come.
We work with leading institutions in the era of Open Banking and look forward to building out the ecosystem of available services both for the market to utilize.
This post originally appeared on Crowd Valley Blog.
Big changes are happening in the financial services industry, with Fintech that has experienced a fantastic growth and with financial technology companies now on pace to see the level of investments to reach a new record in 2017. As part of this, there is a case represented by Real Estate, a trillions dollars sector that has been slow to change, which is seeing a wave of innovation with property technology, or Proptech.
We talked about Real Estate crowdfunding different times already, but when speaking about Proptech, we are considering a far broader segment, referring more in general to those companies using technology to “improve or reinvent the services we rely on in the property industry to buy, rent, sell, build, heat or manage residential and commercial property”, improving a range of related services from the access to mortgages to building energy efficient homes. And we are now starting to have very concrete examples about how this is changing the property market.
An illiquid market where it’s expensive to trade property and where “there is a large risk of abortive expenditure, and the result can be a very wide bid-offer spread” is listed as one of the key Real Estate’s current limit in a report called “PropTech 3.0: the future of real estate”, recently published by Professor Andrew Baum of the Saïd Business School at the University of Oxford. “Crowdfunding platforms, on line secondary market platforms and blockchain make this the most intriguing of FinTech questions. It seems very likely that the many tech-based contributions to the residential sales process will bear fruit. If investor protection issues can be solved, tech platforms will enable smaller residential assets to transact on platforms and exchanges in reasonable quantity, leading to exponential growth and radical change.” said Professor Baum.
Alex Gosling, CEO of HouseSimple.com, says that he managed the sale of more than 18,000 properties since the launch of its platform in 2015, with a rough £40M (approximately $54M) saved, considering the usual agent fee charged on the average UK house price. “As more people feel comfortable with the online model, we expect online agents to grab a bigger slice of the UK estate agency market. Currently, online estate agents have around 5% market share. We believe this will increase to 15%–20% by 2020,” Gosling says.
Returning to an area more familiar to our readers, there is RealtyShares, a San Francisco based company that just raised a new funding round of $28M, led by Cross Creek Advisors.
They developed a debt and equity Real Estate investments platform, that since its launch in 2013, has deployed $500M across more than 1,000 properties, with a typical transaction size between $2M and $5M.
Another good example of Proptech company that is doing well is Habito, a digital mortgage broker that just received investments for £18.5M (approximately $25M), in a raise led by the venture capital fund Atomico. Since its launch in April last year, Habito advised over 50,000 people on mortgages worth more than half a billion pounds. Niall Wass, Partner at Atomico, said that the big inefficiencies within the mortgage market present at the moment an attractive investment opportunity.
Looking more in general at the market, Proptech companies received about $6.4B in investments across 817 deals since 2012, with investments from venture capital that peaked last year. In 2017, with $1.46B already invested across 107 deals in the first part of the year, the total amount of dollars invested is expected to reach $3.4B, exceeding 2016 by 25%. We will need to wait to see how the market will develop in the future, but the perspectives at the moment certainly seem very positive, not the least considering the massive scale of the labor intense global property market.
This post originally appeared on Crowd Valley Blog.
Source: CB Insights - https://www.cbinsights.com/research/real-estate-tech-startup-funding/
With the Payment Services Directive becoming a reality at the start of 2018, can we expect to see a panacea of connected services at users’ fingertips, offering best in class quotes for financial products based on actual information? Will we see firms position themselves as leaders beyond their previous borders and existence, in the digital realm with limitless data-driven possibilities? Or will we maybe see cross the board resistance and siloed architecture that prevents valuable use?
If you are looking for the short answer, here it is: Yes.
If on the other hand you can accept the reality will be multidimensional and layered, well the answer is still “Yes”. In any new market, and let’s be very clear this is a new market, we will see behavior and approaches from each end of the spectrum searching for their preferred way to adapt and benefit from the new reality.
With the inception of financial digitalization, we’ve seen new firms such as Goldman Sachs adapt their strategy to cover retail and embrace fintech, firms such as Citi and BNY Mellon have ventured into open banking and finance APIs and Vanguard has created a digital behemoth of their robo-advisor.
Yet for each firm there are dozens that are still in 2017 evaluating their position and strategy, laying out plans that have yet to see the public and some still on the fence. Having started looking at the market in 2009, it was clear the market would not move in uniform fashion yet the complexity of the market and its adoption of new technologies and paradigms was still a surprise.
Open Banking is still a new concept and, as new concepts go, it will be refined by trial and error. Some banks are farther along than others, with e.g. BBVA already in commercial use with several APIs. Yet the roll out of new “API Markets”, as they are often called, will see a learning experience from both the bank providers as well as those looking to utilize them.
From our experience working alongside many of these Open Banking interfaces, there are areas that require more than just a technical understanding, such as client on-boarding and related requirements around KYC and AML, not just the requirements but how institutions like global banks actually deal with them; these impact behavior, use and ultimately the design of new products and services.
We’ve talked about opportunities with PSD2 before, including the Open Banking concept of how a full financial app ecosystem will emerge on top of the Open Banking platform with extensive business implications. One thing we are beginning to see is how the concept of Open Banking can fundamentally shape and transform mandates, where financial institutions may see their services and opportunities broaden beyond their traditional operations. And how would this happen? For one, it may happen organically by the very virtue of having an open platform and allowing the third party ecosystem to truly flourish. Banks may indeed find new customers that they did not consider previously, from places they are not active in – whether that be a geographical area or a market segment.
Whatever we foresee with PSD2 and Open Banking, we are likely going to be right. It’s going to be a direction we follow and a little bit of everything along the way. Yet as an industry as long as we are focused on ultimate client value, that direction should guide us along.
Written by Markus Lampinen, Crowd Valley CEO
This post originally appeared on AltFi.
Clouds have become the standard for many online services. Now we are really moving to serverless services that offer many benefits over the traditional cloud server models. Serverless architecture can offer better use of resources, more cost-effective pricing and also better security against some threats.
There are, of course, still servers in serverless solutions. Serverless means dynamic allocation of server resources, i.e. we don’t need to pay or rent dedicated servers, but we buy computing capacity and we can use it based on our needs. These solutions are also called Function-as-a-Service, FaaS. Most leading cloud providers already offer serveless services, for example, AWS Lambda, Google Cloud Functions, IBM OpenWhisk, and Microsoft Azure Functions.
Serverless models also change software architecture. The microservices model means that each small task or job is a separate function that works independently. For example, in a finance service a KYC process (know-your-customer) can have an independent ID check, sanction list and anti-money laundering checks, so that all of them are independent functions that can run in parallel too (see an implementation example in the picture). This model enables the development of more independent functions by different developers and also makes it easier to debug smaller functions - and the same functionality can be then used for different services. Of course, starting and running many functions also creates some overhead, but it is quite small compared to the benefits. This doesn’t mean that all services need to become microservices, it is possible to also create functions that handle bigger tasks.
Serverless means that a service provider needs to pay only for the capacity actually used. This is especially valuable for services where capacity needs vary. Earlier a service needed capacity based on peak demand, but with serverless models the service pays for the functions executed in the cloud service. These solutions neither take resources for traditional server setup or management work.
The concept also makes it easier to implement API services that can process in the background and an API call doesn’t lock any other services. For example, a user can ask his / her investment portfolio details. The back office API replies immediately that it will be processed. The actual data then comes in several patches through webhooks to the front end. This can help also with blockchain implementations, when blockchain functions often don’t guarantee any latency time.
The serverless model works very well for many digital services, but of course, there are still some services where the traditional server model is faster and more cost-effective. For example, services that constantly require a lot of computing capacity are probably better to run in the traditional environment to avoid the overhead required to constantly start tasks when capacity is needed. When the load is easy to predict, it is also cost-effective to rent an optimal server capacity.
Most internet and mobile services have off-peak and on-peak periods. FinTech services are one example of those. If we think for example about payments, finance back office functions, and banking services, load needs vary a lot. They are also often critical services, i.e. they must work properly also during a peak demand.
Serverless solutions can also offer better security against some threats. For example, a serverless solution is more immune against denial of service (DoS) attacks, when the service is not dependent on certain servers. An attack can create additional costs, if it means a lot of capacity is used for in-coming requests, and attackers with massive capacity can target a whole cloud. Some serverless clouds (at least AWS Lambda) offer tools to require API key or authentication for a function. This means a DoS creates only API calls to the API gateway, but don’t start more processing - this eliminates the load and cost effects of DoS. The model also helps against attacks that compromise individual servers that are then used to attack further. Serverless also eliminates problems caused by unpatched server software.
This doesn’t mean all of this comes without any potential issues and security risks. Vulnerabilities in software and applications are still a risk. Serverless can also make traditional security monitoring more complex. As a whole we can conclude that serverless can help with security risks, but it also needs competence to manage vulnerabilities and a new kind of software and data architecture.
FinTech is a fast-growing service area that is also moving to clouds. This is a good timing also consider serverless solutions for finance applications, especially when they can also help with security. You can already develop a serverless payment solutions with Stripe. Crowd Valley is piloting serverless version of its finance back office as a service. US bank Capital One has been reported to be an AWS Lambda customer. Thomson Reuters and US finance industry self-regulator Finra also already use serverless solutions.
Serverless solutions will most probably come to dominate all event-based services. It fits well to financial services too, and timing with many other new things in finance is now good to make the transition. For example, the PSD2 regulation will open APIs to banking services and will significantly change finance services and their structures (read about old banking APIs). Serverless can offer a lot of value to create more cost effective and stable services, but of course they also need their own competencies to do it right.
This post originally appeared on Telecom Asia.
Los Angeles & Hong Kong, September 29, 2017 – Grow VC Group, the leading fintech technology and data holding company, has today officially sold its ownership in Los Angeles based TradeUp Capital Fund (TradeUp). TradeUp offers efficient services for export capital. The new owners will integrate the offering into their existing portfolio of export services. The acquirer sees that new finance services for export business are an important part of a service portfolio to support export companies. The companies have decided to not disclose the acquirer or price. The acquirer will announce its future services later on in the year.
The Grow VC Group has been an owner in TradeUp since early 2014. TradeUp was the first online investment service that especially focused on companies that raise capital for globalization and export. Grow VC Group has been an owner and investor in several online investing and crowdfunding services since its inception in 2009, and over the markets maturity divested several ownerships, and focused on enabling technology and data in the fintech market, and increases its operations for blockchain, financial data and digital assets (including ICO) based solutions.
Grow VC Group companies build businesses that enable digital finance services globally, by offering technology, data, finance instruments and competence to disrupt old finance models, and making it easier for anyone to implement new finance services, invest and get access to capital. Established in 2009 Grow VC Group is the global leader of fintech innovations, digital and distributed finance services, and digital infrastructures. Its mission is to make the finance services more effective, transparent and democratic.
Jouko Ahvenainen, Chairman, Grow VC Group, email@example.com, +1 646 363 6664
Grow VC Group and its companies will participate and speak in several FinTech events during the fall 2017. We listed here some events the group representatives will speak. The speeches focus especially on new digital finance services, data and data analytics, and enabling technology that disrupts finance services.
Hong Kong FinTech Week is a leading FinTech event in Asia. It combines the development of FinTech in the traditional finance hub Hong Kong, in the leading FinTech country China and the latest development in Asian emerging markets. Grow VC Group Co-founder and Chairman Jouko Ahvenainen speaks in the event and focuses especially on data, data analytics and AI in FinTech.
FinTech World event in Washington DC focuses on blockchain, digital currencies and new ways to have digital assets. This event gathers the leading digital currency and blockchain experts in the US. Grow VC Group's Jouko Ahvenainen speaks about data and AI for digital currencies and assets, and Crowd Valley's (a Grow VC Group company) Markus Lampinen about technology to build services, market places and applications for blockchain, crypto currencies and ICOs.
World Funding Summit in Los Angeles has the leading experts of the funding market to talk about new funding models, online alternative finance and how digital currencies, assets and ICOs change the market. An important theme is also, how these new solutions can make the finance market more equal and democratic. Grow VC Group's Jouko Ahvenainen speaks, how new solutions, instruments and digital assets change the fund raising and investing.
In many industries – such as airlines, retail, and media – disruption has been linked to new low-cost, almost commodity-type services. Southwest Airlines and Ryanair paved the way for low-cost flights, online news has become a commodity, and retail chains like Walmart, Aldi and Lidl have created a new cheap-prices-always category. The common theme is: cheap basic things, with a better experience available for a premium. FinTech disruption is changing finance in the same way, and when basic finance services become a commodity, they will be integrated to other services.
Some finance services have, of course, been in this category for a long time already. For example, payments are a crucial part of all e-commerce services and brick-and-mortar check out processes. It has become natural that services use third-party payment solutions rather than develop their own. We will see the same development for many other traditional finance and banking services.
Online lending, p2p lending and quick loans have been a fast-growing market. Those new lending services offer many benefits – sometimes a better price, but typically a much better customer experience. Sometimes they offer loans for people who cannot get a bank loan, and they might have more flexibility in terms and conditions. For many loan categories, bank loans are not a very attractive option anymore, especially when you factor in the customer experience, paperwork and time needed to get a loan.
Ford Motor Company just announced that they are going to adjust their car finance process (read more on WSJ). They decided that the traditional credit-scoring model is not very effective or optimal nowadays, and that they could get more customers and sell more with new finance models. Basically, they plan to use more data from new sources to get a more accurate profile of customers and optimize their financing better. It’s worth noting they were forced to do this because alternative lending services are already doing it, and competitive finance is an important component in car sales.
Car sales finance is just one example illustrating that companies outside the traditional finance sector need to develop better new finance solutions. FinTech makes it easier. The real estate sector has adopted a lot of new finance and investment models during the last five years, especially in the UK and the US – but now new real estate finance services are emerging globally. This means there are many new models available to invest in real estate – e.g. in development projects, rented apartments and commercial buildings, and new models to lend and borrow in real estate. Typically, this includes new finance instruments that are then offered through online finance services. These services are offered by some finance companies, real estate development companies and several startups.
At the same time, more inexpensive technology – or even technology-as-a-service – is available to build finance services. You don’t need a $100-million-plus IT back office to set up an investment or lending service – you can get it as a service from cloud, and they can offer access to relevant data sources (including credit ratings and richer data). It is quite easy to develop the actual application and your own investing and lending models.
We will see more:
All this is a part of the overall development towards an API and platform economy. Finance is becoming an integrated component for many other services. It means more competition for banks. But it also means significant new competition for credit card companies that have had an important role in smaller online purchases, and their money has typically been expensive.
When we think about FinTech and its impact, it is easy to focus only on the traditional finance sector. Certainly there will be significant impact on the whole finance value chain, as I have written earlier. At the same time, however, finance is shifting to a platform economy, and it is fundamental to adapt to the requirements of that business model by building the business network, offering APIs and utilizing data. After a few years, we will think about the old-fashioned bank loan process, with all these paper forms, and laugh as we do now at the thought of sending a fax or buying printed flight tickets.
This post originally appeared on Disruptive.Asia.
Artificial intelligence (AI) and machine learning (ML) are becoming an infallible part of the development of present-day technology. Yet the public discussion often centers around a notion of a ‘human-like’ robot and my concern is that the impact gets downplayed. How then should we look at the future with AI? One way which may be helpful is examining the aspect of morality and consciousness, or rather, the lack of both in decision-making in a new paradigm.
Humans have evolved based on a complex process of long-term trial and error. Our biological machinery has been honed over thousands of years to optimize (mainly) for survival and procreation and for these tasks, the human mind is highly advanced. However, we have to realize that the subjective aims of the human mind are the primary reason and motivation for all decisions made. Morality is a key element in the support of sustaining these two goals of the human species, and has successfully introduced a human-wide consensus to better our chance to achieve our goals.
As we look at crafting AI for better data-driven decision making in critical processes – such as optimizing far-reaching and complex value chains, making real-time decisions in applications such as self-driving cars and many more – we should recognize that without coded in morality, AI will actually act without the concept of morality or human subjectivity. In short, it will optimize any and all decisions based on the rational best outcome for the desired parameters rather than what ‘a good person would do.’
A Future with Less Morality May Be One Humans Find Uncomfortable
Looking at the grinding, long process of trial & error humans have undergone to evolve, we could expect AI to dwarf this process and undergo a rather rapid process of trial & error. Especially with the concept of connected machines and the vast availability of real-time data, we can expect the process to be fundamentally fast and unlike anything that has ever been seen before.
The entire human species has used a moral compass in guiding development and uniting humanity behind a broader direction. For the first time in history, we may have a future chapter of innovation written and executed by a new kind of decision-making and at that, entirely non-human.
However, we should not be blind in assuming this future is far off. As authors in Moral Decision Making Frameworks for Artificial Intelligence point out, AI is already used in highly complex ethical fields of decision making such as organ transplants and waiting lists, deciding effectively who lives a little longer and who does not.
Yet one does not even have to go to medical fields to find life-altering decisions made by non-humans, where AI is already far-used in determining eligibility for receiving and underwriting credit decisions including loans, which will determine who has an opportunity to access finances for a specific reason and again, who does not. This too has far-reaching consequences.
We’re already far along in introducing an objective decision maker into situations that truly matter, yet humans make a vast number of decisions each day with limited information and most importantly, limited objectivity. We shouldn’t write off the human brain however – it is truly a cognitive miracle that derives information from all senses in real time and through conscious and unconscious steering, shapes our thoughts & actions. Yet a lot of human morality centers around the concept of self-protection in complex decision making and a lot of the information accessible to humans, is a fraction of what AI will be able to tap into and process.
Well Then – Can We Introduce Human Morality Into Technology?
It’s certainly a possibility and one that several leading researchers and authors of our future are pursuing. For example, Future of Life Institute and Duke University have been active in the foray of introducing ethical engines into artificial intelligence and decision making by interesting applications of game theory. Researchers often look at the now-infamous examples such as the self-driving car and an unavoidable pedestrian accident and attempt to find very tangible ways of introducing intended morality in a way that is actionable and clear.
It is a complex task which involves classifying actions as morally right or wrong in a universal and generally accepted way. The establishment of a pre-written ‘moral compass’ would allow an element of human decision-making to be codified and carried on into applications that will learn on their own at some point.
We can generally think of the concept in different phases:
We can argue that we currently find ourselves in the first phase with the question of whether we’ll ever reach the third phase at all.
Morality as a Lens for Future Outlook
The future of technology and AI will likely be a series of events, some controlled and pre-planned, and others the result of unintended consequences. Morality will be a key component in determining how the future looks and the exercise of considering the absence of morality may be useful in understanding why the field’s importance is so profound. If we indeed never come to the third phase, we will also be looking at a future derived largely by a presence lacking consciousness. These elements may be impossible to imagine ahead of time, yet their implications are likely to be paramount.
Written by Markus Lampinen, CEO of Crowd Valley, Inc.
This post originally appeared on Let's Talk Payments.
Photo: MIT Moral Machine.
"We need new solutions for collecting and using data that strikes the right balance between consumer benefits and control over their own data."
I was looking for the opening hours of a local supermarket in San Francisco from Google Maps. When I found them, Google also told me an interesting additional detail: “You visited this place 17 hours ago.”
In fact, yes, I did. It reminded me that my Android phone indeed collects my every movement and location. (You can check your history at https://www.google.com/maps/timeline, when logged into your Google account.)
Here’s another example of the same thing: an insurance technology (“insurtech”) company recently demonstrated its app to me, and it had a full history of drivers’ driving data, including each acceleration, braking and speeding, on the map. The insurance company collects all that data, which it can then use to try to influence driving habits, and adjust premium prices.
Yet another example: new credit rating agencies that not only collect your income and loan payment history, but also try to utilize all data about you available on the Internet –including location, social network and payments – to evaluate the risk in lending you money.
We are really starting to live a new type of public life, although we don’t always know it. It is not breaking news anymore that mobile, Internet services and social media collect a lot of data from us. It has been used for marketing and advertising for years. But now there are more and more ways to use it – for example, recommendations, financial services, political marketing, and personalized customer experiences.
Many parties and people are very worried about this. They see that companies can now know perhaps too much about individuals, sensitive data can leak into the wrong hands, and we cannot know how the data is used in the future if ‘bad forces’ take over. That’s why governments are developing new laws and regulation for collecting, storing, processing and utilizing data – perhaps the most well-known example right now being the EU’s General Data Protection Regulation (GDPR), which takes effect in May next year.
Naturally, we also hear many horror stories how this all can get worse in the future. When your phone, TV and digital assistant are listening to you speak, they can collect everything that is said in your home. Services could analyze all your communications, including emails, calls, and chat messages. There are totally new opportunities here to create intelligence gathering services much more effective than the East German Stasi ever were. And we know many government intelligence services already collect this data, or are trying to.
But the flip side is the potential benefits of all this data collection. Big data analytics can make many services better. Isn’t it fair and good that your driving habits have a positive impact on your motor insurance premiums (provided you’re a good driver, of course)? Or that your life habits can determine the cost of your health and life insurance? Or your money management behaviour and spending habits can be used to evaluate the risk and price for your loan? Or services can personalize your experiences and tailor them especially for your needs and behaviors?
People usually find data collection stories scary because they have no control over who gets to collect data and where and how it’s used – therefore, the simple answer is to give them control, to include the ability to forbid use of data and even to have the data deleted.
In practice, of course, this is far from simple. According to different studies, the majority of people believe they had lost the control of their data. So many services collect and use data, and users are not always able to follow or control this. Companies also sell and buy data. This is a new complex area for authorities to monitor and control, although we have also seen that some Internet companies are more interested in protecting privacy and use of data than some governments.
We can conclude, then, that while there are threats and risks to collecting and utilizing user data, at the same time this data is fundamental to making many services better for users, as well as more affordable.
There is definitely a need for new solutions where people can manage their own data and ensure it is used to suit their needs. For example, if a person has all his or her own verified data, it would not be necessary to reveal all data for a loan application, motor insurance application or location-based service – only profile-level data that is relevant for the service in question. Today, companies are the ones collecting all the user data they can – in the future. each person should be able to collect and use their own data. At least, people should have their own copies of their data to verify that it is true.
It is clear we have a need for totally new solutions to utilize data so that privacy and user control can live together. Governmental and legal control alone is not enough to handle the fundamental problems involved in data collection. (Governments can even be part of the problem of data misuse.) Instead, we will soon see a new era of data analytics that is based on fundamentals to combine personal data management, profiling and targeted utilization of profiles.
The article was first published on Disruptive Asia.
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The adoption of open APIs by banks and financial institutions has been steadily growing, as has the ecosystem delivering these services. Companies providing KYC products rank among the most well established services to help financial institutions cut cost, increase scalability and help comply in a more scrupulous regulatory environment. A Thomson Reuters global survey reveals that banks are taking as long as 48 days to onboard a new customer. Also, the banks are spending in excess of $60 million per annum on KYC and client onboarding.
Although newer more dynamic platforms process KYC in an automated fashion, most financial institutions still handle KYC verifications manually. Manual verification is cumbersome and error prone. This is more true as institutions scale, adding further compliance officers compounding the problem at hand. Outside of basic requirements, Booz Allen Hamilton estimated compliance failure costing firms $13.4 billion in 2014.
When taking a practical approach to deploying automated KYC workflows using open APIs into financial institutions, they need to support both technical and operation members.
Technical teams are burdened with ancient core banking systems that are costly to service and as time passes, more difficult to do so. The cooperation between Fintech and financial institutions allow these technical teams to leverage cost effective solutions when compared to building and managing new infrastructure. They also vastly increase time to implement systems from an average of more than 36 months down to a period of 8 to 12 months. Making systems future proof, scalable and cost effective is a core concern being addressed by open APIs.
Operational teams are focused on workflow efficiencies and the bottom line. KYC APIs allow the compliance officers to be more productive while decreasing headcount. Officers are able to monitor rather than process, needing a light touch on most onboarding workflows. Better reporting, record-keeping and the near complete reduction of manual paper work can reduce compliance failure. Decoupling the rise in deal flow with the increase of headcount allow financial institutions to scale more efficiently while mitigating compliance failure.
We at Crowd Valley support both technical and operation teams migrate legacy systems into an open API environment. Technical teams can leverage our Bank grade Cloud Back Office connected to global KYC providers to efficiently launch compliance workflows into their core systems. Operational teams leverage our global reach where we have helped more than 130 institutions navigate the use of open APIs and industry best practise. If you are looking to capitalise on KYC efficiencies within the Fintech space and would like to discuss this further, please do not hesitate to get in touch with us.
This post originally appeared on Crowd Valley Blog.
Est. 2009 Grow VC Group is the global leader of fintech innovations, digital and distributed finance services. Our mission is to make the finance services more effective, transparent and democratic. The Group includes leading fintech companies in their own areas.
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