Banking on Future: Technology Innovation in Compliance and Risk Management
Compliance and Risk Management in banks
The past decade has brought an avalanche of legislations for banks – ranging from Dodd Frank, EMIR, MiFID, FinFrag, SFTR, to FTRB , GDPR, and Market Abuse. The pressure to comply with myriad regulatory obligations is pushing the compliance programs of banks and financial institutions (FIs) to the brink. The additional threat of penalties for non-compliance has most banks spending greater than ever time and energy towards compliance. The lack of a centralized function which oversees compliance to regulations reduces the bank’s ability to manage risks arising out of compliance.
The risk management functions have also changed dramatically in the last decade and are moving towards crackdown on unethical transactions, fraud monitoring, and collection of taxes. Amid new risks like cybersecurity risk and model risk that have emerged, the BASEL IV requirements mandate use of regulatory capital, risk data aggregation and introduction of IFRS 9 accounting standards as well.
Digitization trends in compliance: Key technologies driving innovation
As the scope and nature of compliance and rules-based banking regulations evolves, banks are tapping into a wide range of digital technologies to drive compliance innovation. Key banking technologies making an impact in today’s world include:
#1 Robotic Process Automation (RPA) for operational efficiencies
RPA automates compliance processes like addressing reporting obligations to Trade Repositories or Approved Reporting Mechanism, supervision by Operations team related to regulatory reporting, and more. It also enables rapid integration of front and back-end systems to track and monitor compliance-evidencing and audit trails, thereby improving control by ensuring consistent adherence to set rules, without much human intervention. RPA. . For instance, Royal Bank of Scotland and ICICI have implemented RPA and Cognitive technologies to reduce operational costs and lower response time to customer queries. In fact, ICICI Bank reported reduction in response time by about 60%, with a 100% improvement in accuracy.i
#2 Natural Language Processing (NLP) for KYC verification
Usage of NLP is envisaged to process legislations and compliance requirements and then compare them with internal policy requirements to appraise banks and FIs of any changes to legislations. Banks can also monitor customers for KYC compliance requirements by using NLP and can even apply it to customer interactions to analyze them and identify policy deviations, if any. Standard Bank, Africa’s largest bank, is successfully leveraging NLP along with ML based cognitive automation, to bring down the client onboarding and KYC timelines from 20 days to just five minutes.ii
#3 AI-ML based compliance and transaction monitoring
AI-ML models based on self-learning algorithms use a champion-challenger approach to monitor and flag transactions and alert banks of fraudulent transactions above a certain threshold. These models help identify patterns in spending and transactions of customers and pinpoint suspicious activities. They can also aid development of a control framework for monitoring transactions which are reported to the regulator and a four-eye principle for signing-off on the reports. A dashboard can be created to enable the reporting team to address reporting obligations with an aging analysis of the acknowledgements and non-acknowledgements received from regulators. Australian Transaction Reports and Analysis Centre (AUSTRAC), the country’s intelligence agency leverages AI/ML tools for detecting and deterring suspicious activity.iii
#4 Augmented and Virtual Reality (AR-VR) for training
Financial institutions need to ensure that they are training employees to give them skills that will help them do their jobs to the best of their abilities. Banks can use a VR experience to experientially train their employees (simulations, role plays, etc.) on compliance norms. Bank of Kuwait leverages VR to train its employees on ‘branch of the future’ requirements.iv
#5 Voice/Speech and Facial Recognition Software for compliance monitoring
Voice and speech recognition software is used for trade surveillance and compliance monitoring in banks to reduce fraud, insider trading and money laundering.
Facial recognition in banks helps reduce compliance burden and is key to meeting KYC requirements by the regulators in some cases.
#6 Big Data and Machine Learning for superior risk and asset management
Use of structured and unstructured data is helping banks make informed decisions related to credit monitoring, guideline monitoring and breach remediation of portfolios. Identifying patterns in transactions and trades can remove cognitive biases and mitigate risks in asset management.
#7 Advanced Analytics and Risk Reporting
Advanced risk reporting capabilities in management information systems improve data quality, risk aggregation and risk-reporting timeliness. Real-time risk reporting analyzes granular behavioral patterns of customers to identify deviations and anomalies sooner and more accurately. The People’s Bank of China leverages AI, Big Data, and cloud computing capabilities to improve its ability to identify, prevent and decrease cross-market and cross-sector financial risks.v
Approach to addressing compliance and risk needs by use of technology innovation
Banks needs to optimize their current compliance function and leverage the use of technology. An approach to streamlining the compliance function by use of innovative technology is provided below.
Banking on tech to transform compliance into competitive advantage
While technology is not a panacea for all of the compliance management challenges of banks, it is certainly a powerful force to augment and accelerate the work humans do in this regard. However, there is no one-size-fits-all approach to successfully leverage banking tech for compliance and risk management. Collaborating with the right technology partner can be a good first step for banks and FIs looking to future-proof their compliance and risk functions and turn them into success enablers.
- IBS Intelligence, Intelligent Operations in the Banking Industry, https://www.gieom.com/wp-content/uploads/2018/12/Whitepaper_Gieom-Intelligence-Operations-in-Banking.pdf
- Banking Tech, Convergence of RPA and AI: the changing landscape in banking compliance,
- Australian Government, Making a difference: Outcomes of ARC supported research 2016–17,
- The Financial Brand, 10 Ways Banks and Credit Unions Are Using Virtual Reality,
- Bloomberg, How Central Banks Are Using Big Data to Help Shape Policy,