Automation, AI and Analytics: Predictions for 2020

2019 was the year of widespread AI, increased regulations and innovative technologies. We saw a huge increase in the amount of data across the globe. In fact, more than 2.5 quintillion (that’s 18 zeros!) bytes of data are generated worldwide every day – and it keeps on growing.

So what’s next?

In 2020, we’ll see enterprises driving technology as a disruptive force, permeating innovation and change. New technology, even more data and sophisticated analytics will empower organizations to gain greater decision intelligence in our data-driven world.

Here are Quantexa’s top 20 predictions for 2020:

Anti-money laundering

#1. Agile technologies will enable banks to combat multiple risks from one platform.

We expect to see a greater convergence of the three disciples of AML and Fraud (FRAML), as banks adopt more agile technology. With the ability to handle feeds from all associated systems, innovative technology will help banks to focus on data completeness, accuracy and availability, empowering a master once, share many approach to data.

#2. There will be a greater focus on Trade Finance Fraud as banks intensify the prevention of cross-border movement of illicit funds.

Banks will need to adapt to the increasing scrutiny on outdated business and compliance processes as well as the new reforms to the EU’s 5^th Money Laundering Directive. Financial institutions will need to adopt an intelligence-led approach to decision making to mitigate trade-based money launder and fraud risk. Banks are also investing in network-based analytical techniques to help identify ultimate beneficial owners (UBOs) so they can better understand corporate structures and relationships.

#3. Regulators will explore innovation and collaboration worldwide.

Regulatory pressure will continue to grow and we expect to see regulators turning their attention to innovation, similarly to the UK’s FCA Global Financial Innovation Network which launched in 2019. This will increase opportunities for collaboration between RegTech firms and regulators around the globe.

#4. Knowing counterparty information will become a must.

Understanding who your customers’ customers are is no longer a nice-to-have, but a need-to-know. Systemic and singular banking failures have been exposing financial institutions in both low and high-risk jurisdictions.

#5. Financial institutions will fuse their trade surveillance efforts with their AML and financial crime efforts.

Banks will begin to merge Markets Abuse Surveillance and Financial Crime Compliance to bring together employee and client intelligence and make better decisions to assess suspicious activity with a holistic contextual view.

#6. The U.S. will move closer to establishing a beneficial ownership registry.

The lack of business ownerships is giving criminals somewhere to hide. Kenneth Blanco, director of FinCEN, has endorsed the creation of a registry and the House of Representatives passed a bill in October that will help to expose owners of shell companies. The EU will also continue to focus on transparency and ownerships of corporate entities with the introduction of the new Ultimate Beneficial Owner registries created as part of the 5^th anti-money laundering directive.

#7. The manual burden of investigations will be alleviated using automation.

By identifying additional data sets, organizations can enhance monitoring output and gain more valuable analytics to help eliminate part of the manual burden of current investigative processes. Building context enables more holistic view of data, which will result in more efficient and effective decision making.

#8. 2020 will be the year of information sharing and multi-jurisdictional monitoring will take off.

Legal frameworks within countries will begin to catch up with the needs and wants of law enforcement and financial institutions. This will enable the sharing of information and use of as much data as possible in order to catch criminals and help mitigate financial crime risk. The technology and willingness to facilitate data sharing are already there but these partnerships require changes to current laws and directives surrounding privacy.

#9. The U.S. will see a renewed focus of enforcement actions in the Markets and Trade businesses.

Dirty money has exited retail and institutional environments to Markets and Trade businesses. Products historically considered low or no risk have been exploited for considerable gains, such as in the Azerbaijani Laundromats. FINRA will look more closely at Markets AML especially LPS and FX, but not ignoring precious metals and arts and antiquities.

Know-Your-Customer (KYC)

#10. Knowing counterparty information will become a must.

Understanding who your customers’ customers are is no longer a nice-to-have, but a need-to-know. Systemic and singular banking failures have been exposing financial institutions in both low and high-risk jurisdictions.

#11. Financial institutions will move to a continuous, dynamic KYC model.

We predict there will be more reliance on dynamic customer risk rating models to provide sophisticated triggers and advanced analytics. This will allow for low-risk customer reviews to skip the manual review process and for customers to receive a better customer experience.

#12. Financial institutions will take a look at their costs around KYC.

From both an operational perspective and from a customer perspective, financial institutions that are unable to streamline their onboarding processes and reduce internal costs will suffer from higher customer attrition. More than one in five UK consumers say they primarily use a challenger bank with better and easier KYC processes, meaning banks need to focus on technology that can provide a better customer experience without increasing risk.

Credit risk

#13. Banks will use new technologies with historic data to gain new insights.

New technology, more data inputs (especially networked inputs) and sophisticated modelling approaches will yield a more granular view of credit risk. This will help banks to grow their lending portfolio sustainably by highlighting potentially mispriced or declined lending opportunities.

#14. Climate risk will become more mainstream in the assessment of credit risk.

The growing effects of climate change have resulted in the increasing risk from disruption within supply chains, ultimately impacting credit risk. To overcome this, organizations must gain a greater understanding of the global supply chain network to view clear connections between finance, trade and farming. This can also be enriched with information on physical climate risks and carbon usage to see where the highest risk lies and assist with consumer decisions.

#15. Trade wars, rising protectionism and Brexit risks will continue to add uncertainty and stresses to global supply chains.

Credit risk increases with an uncertain market. With advanced analytics, organizations can monitor for negative news on complex networks to uncover early warning signs of risk, such as credit distress.

Customer intelligence

#16. The growth of digital-only business banks will continue.

Digital-only banks are set to triple their global customers in the next year, providing seamless customer experiences which are driven by sophisticated analytical platforms, automated decision-making and virtual engagement. With regulatory hurdles on the horizon, challenger banks will also need to ensure they have implemented effective anti-financial crime systems.

#17. The extension of Customer Data Platforms will include more third-party data.

This, alongside unstructured data, will provide context on customers and prospects, enabling more effective customer engagement and marketing automation.

#18. Banks will focus their time on customer relationships.

To enable better customer management and more efficient business development, relationship intelligence will be leveraged to identifying touchpoints with customers and prospects across all business lines. There will also be a shift in the level of augmented decision making within relationship manager and private bank teams, with staff increasingly able to focus their time on meaningful conversations with clients whilst being provided useful information and prompts by artificial intelligence-based solutions.

Cloud and analytics

#19. AI will emerge from adolescence and start to achieve maturity.

More business leaders will get personal exposure to what AI can and cannot deliver. This will result in organisations moving away from buzzwords and focusing on gaining genuine value from practical AI, such as overcoming data quality challenges by creating a single customer view using context.

#20. There will be a greater focus on operationalizing analytics.

The open-source community is moving away from demonstrating and training new algorithms, to focusing on the ongoing process of keeping production models live and up to date while delivering measurable results. This will be achieved by using graph networks as input to models to provide accuracy levels that can be operationalized.

BONUS Prediction!

#21. Context will be paramount to make better business decisions.

Even the most data-intensive organizations, from banks to insurance firms, are still struggling to gain tangible value from their ever-growing data lake. By connecting all this data, wherever and however it is available, organizations can build the context of relationships between people, organizations and accounts.

We believe in 2020, contextual decision intelligence will empower organizations to shift their focus from data quality to decision quality.