To say that computer programmers will one day replace investment traders might sound like hyperbole, but don’t laugh — it is already happening. Investment management software is replacing human managers at a surprising rate.
As the fintech industry quietly disrupted entire sectors within the world of finance, banks initially stood idly by, with the paralyses common to a people being invaded. But not for long. When it was apparent that banks would either find a way to embrace fintechs and the technology they rode in on, or else be superseded by them, they opted for the former.
Today, banks are not only adopting, they are innovating, creating opportunities for themselves and developers, alike. By investing in AI/big data-driven portfolio management software, investment planning software, and powerful platforms, they are redefining their own industry.
In this article, we will explore how trends in fintech technology are shaping the investment banking industry.
Table of Contents
Artificial Intelligence (AI)
As banks increasingly make AI a part of their IT strategy, finding ways to harness the power of AI for their investment services will become a top priority. Goldman Sachs — who has invested in AI startups, spoke for many in the banking industry when it characterized the potential of artificial intelligence as “unbounded.”
To understand the value of AI in the investment banking sector, let us look at a few of the unique capabilities it offers.
The value of AI to the marketeer of investment services is the same as for any service: the ability to better identify which marketing strategy is best suited for a given prospect at a given time. By tapping the power of big data (more on big data later in this article), AI can help investment marketing managers make decisions based on more-timely information and more-intelligent analysis of that data.
For example, people and machines respond to language differently. A website content item that may be optimized for CEO may not be constructed in a way that best suites a human audience. This is often the case, and copywriters have become resigned to compromising between creating the most readable copy and the most SEO-friendly copy. AI applications can help investment banks create SEO-optimized content, while simultaneously channeling human-friendly content to the user via email, social media message, tweets, or other information channels.
Other advantages AI offers investment marketing managers include automatic separation of good leads from bad leads, automatic gathering of prospect information such as contact information and income, and human voice/speech recognition-empowered automated sales assistants.
Enhanced Customer Relationship Management (CRM)
The best portfolio managers are also the best relationship managers. And while advanced Customer Relationship Management (CRM) tools have been on the market for a few years, most merely provide information to managers in an organized way that helps build and retain customer relationships.
AI software, however, can do more. Unlike conventional CRM software, or even portfolio managers themselves, AI-based CRM applications can continuously monitor customers’ social media posts, tweets, credit factors, and other data points and can alert investment managers accordingly. Moreover, AI applications can initiate event-driven communications with customers, and engage them in near-human ways that traditional software cannot.
Additionally, AI-based CRM platforms can interface with customer portals to provide customized user interfaces. The customer is presented with the information he or she is most likely to need, based not only on previous interactions, but also on big-data predictive analysis.
AI technology provides a wealth of opportunities for portfolio managers to engage the right clients with the right offerings at the right time and through the right channels. And that is technology banks are willing to invest in.
Unethical mutual fund practices, accounting fraud, and Forex fraud are but a few types of fraud that can impact the investment sector. While increased regulation hopes to stifle opportunities for fraud within the banking industry, a great deal of such regulations rely on human oversight to detect fraudulent activity.
By incorporating AI applications into their processes, banks are easing the burden on even legacy systems to catch fraud or prevent it before it occurs. AI excels at identifying normal patterns within reams of data and spotting deviances from those norms. Since most fraudulent activity is designed to occur very close to the margins of what is normal activity, AI applications are far superior to humans at identifying potential fraud. A typical AI program can accurately and consistently evaluate tens of thousands of transactions per second, which no human can do.
In response to a rash of banking crises in recent years, regulatory agencies have placed ever-increasing and seemingly unending compliance requirements on the financial industry. Burdensome regulations now affect nearly every aspect of banking, from how data must be stored and protected to risk reporting. To ease the mounting costs of compliance — up to $4 billion per year for larger institutions, banks are turning to AI.
The result of far-reaching regulations on investment banks has been a chilling effect on profitability. Industry reports indicate that fixed-income flow products, in particular, will suffer profit losses for banks by 15-25% over the next three years.
AI technology can help reduce the burden of regulatory compliance for investment banks in a number of ways. Just one example is AI’s ability to analyze and sort large volumes of data, which can enable AI software to determine what data is pertinent to regulatory compliance and what is not. By directing only relevant data to compliance officers for review, AI can reduce their workload substantially.
Big Data Analytics
Few technology articles, today, would be complete without mentioning big data analytics. The ability to collect and analyze large data sets lends itself to an increasing number of markets and applications — investment banking not the least of them. Indeed, the use of big data by the financial trading industry is, perhaps, among the best examples of how big data can be used.
Why big data analytics is of such significance to the investment banking industry is obvious, if you think about it. Let us enumerate a few of the reasons why:
- Investment banks process huge amounts of transaction data daily.
- Transaction data must be continuously evaluated against changing regulatory requirements.
- Recommendations banks make to their investment customers must be based on timely, accurate, and relevant information.
Big data, which is a collection of both structured and unstructured data sets from numerous internal and external sources, contains crucial information needed for making trading decisions. The information contained in big-data data sets is often real-time data, which can affect decisions within milliseconds of an execution.
Through the use of powerful analytics algorithms, banks can make intelligent use of the data collected. As a result, investment banks can offer their clients more accurate and more timely investment advice, which makes both banks and customers happy.
Blockchain is a disruptive technology that is, essentially, a ledger that is shared among various parties. The blockchain is so-called because the shared ledger consists of a continuously-growing list of records called blocks. Each block contains a timestamp, and is linked chronologically to the preceding block of data. The structure of a blockchain makes it inherently secure. Blockchains can be created to record, store, and validate any type of transactions, including purchases, currency exchanges, peer-to-peer exchanges of goods and services, and financial trades, to name a few.
Blockchain technology lends itself to numerous applications within the investment banking industry. A short list of ways blockchain can benefit investment banking might include the following: automating back-office processes, automating regulatory compliance, significantly decreasing transaction settling time, enhanced transaction security, and reduced fraud.
While the technology, as applied to banking, is still in its infancy, investment banks are showing keen interest in the technology and the promises it provides for trading. One financial giant, Barclays, for example, experimented with the technology by allowing two participants to exchange trade data using a blockchain.
Bank’s willingness to embrace blockchain technology should be all the incentive developers need to innovate in this explosive market.
Few technologies, today, are unaffected by the cloud, in one way or another. Investment banking is no exception. While banks were initially — and understandably — reluctant to host secure processes in the public cloud, their attitudes seem to be changing. Fears of scrutiny by regulatory agencies, if a cloud vendor experienced a breach, lead many banks to focus on how they and their customers might benefit from private cloud technology. With more and more businesses moving their secure assets to public cloud servers, banks have started slowly doing the same.
Even though private clouds offer their own benefits, mostly in terms of security, they are not very well suited for public transactions. While banks will continue to explore private clouds for internal processes, they are rapidly seeing the advantages of going public.
Investment banks, in particular, can benefit from the advantages of cloud computing. Compared with legacy systems, cloud computing offers a number of benefits, including:
Reduced Costs — By reducing the need for onsite hardware and software, cloud-based applications can be developed, distributed, and updated for less costs.
Greater Flexibility and Scalability — Having applications centralized in the cloud, rather than residing on numerous PC or servers, make it easier to implement changes or scale up to meet increased demand.
Improved Efficiency — Since cloud-based applications focus resources on one application, or a group of applications, rather than numerous disconnected applications residing on different platforms, cloud-based applications can be managed with greater efficiency.
Better Customer Experience — The inherent fast speed and cross-platform compatibility offered by cloud services can result in faster, more-customized experiences by customers.
In November of 2016, Citi launched a new API Developer Hub designed to help developers build solutions that will benefit Citi customers. The open source platform speaks volumes about banks’ willingness to connect with fintechs for the mutual benefit of both parties.
What this means for investment banks, and developers, alike, is opportunity. As banks invest more heavily than ever in technology, there will be ever-increasing opportunities for developers to capture the market, not only by developing applications for existing API platforms, but in helping banks develop their own API platforms and libraries.
With online trading becoming more mobile, the opportunity is enormous for banks to capitalize on API platforms that can be used by mobile solutions developers. Applications that allow you to track your investments, mobile stock portfolio management solutions, and mobile portfolio management platforms represent a few of the possibilities for developers with API expertise.
How Ignite Can Help?
Rarely has an existing industry provided such opportunity for developers. And, yet, those who will shape the future of investment banking must be well-prepared if they plan to profit from this exciting and highly dynamic market.
Ignite has the experience and resources you need, if investment banking is to be your new frontier. With six R&D labs across Europe, we have the capability to develop your fintech solution, regardless of the scope. Whether your project involves an application or a platform, we can bring your idea to fruition.
We specialize in custom development at outsource prices.
If your software development strategy includes outsourcing your project, why not contact us today?