Capital Market - How to drive Technology led growth?

Capital market industry is facing challenges across revenue growth, capital charges and high structural costs. Investment banking revenue fell 4% last year mainly due to 8% decline in Fixed income, 5% drop in advisory and underwriting revenues. While growth is hard to come by, the problem is further magnified by deterioration of cost-income-ratio due to higher compliance cost and complicated business processes & IT infrastructure.

In spite of all these, the future of investment banking can be great. Microfinance sector is expected to grow at 19% over next 5 years. Asia will lead the growth in service like trade finance and Digital technology will invade back office and reduce operations cost.

In this environment, technology led innovation in Blockchain, IoT, RPA, AI, Advanced analytics, CLOUD computing coupled with outsourcing of non-core operations & Infrastructure will drive growth of the industry.

Here is a summary of front to back services which can be transformed using IT innovations.

Client Services

Client onboarding requires compliance with rules like AML, KYC and FATCA. This is an area where utility based model significantly reduce the cost of operation. Also, 3rd party data providers and RPA may further improve the speed and quality and reduce cost.

Client insight is also a key challenge due to complex and multi-dimensional relations exist across region, product and services. In such scenarios Big-data analytics can do sentiment analysis and provide “next best action”; advanced analytics can provide early warning on customer exit and provide alternative investment strategy; behavior based pricing engine can encourage customer to move to low cost channels like mobile and internet.

Investment research can be improved by moving to natural language process format. If coupled with advanced analytics – it can respond to questions like “what happens when the Oil price goes up by 20%?”. Linguistic search engines can be deployed to reduce research time to gather data across regulatory filing, customer presentations and earning calls transcripts. 

And finally, Client relationship management can be further refined by providing IT applications with combination of speech, test and touch (biometric authentication) interfaces. This will significantly reduce the operation cost of managing clients.

Trading

Pre-trade analytics can benefit in modelling of capital, balance sheet and tax impacts; real time analysis of trade, margins and positions across multiple asset classes; compliance for MiFID II.

Trade execution services is going through transformation. Trading platforms are available As a Service, which can facilitate ring fencing and help reduce cost, manage risk & transparency better for MiFID II.  CLOUD based “soft Turrets” systems might eliminate the cost and infra associated with turret and voice telecom systems. In B2C space Robo-advisors can manage the portfolio with limited human touch resulting in disruption in brokerage services.

Post trade analytics allows buyers to see the price achieved vs market rates and identify seller giving the highest price. There is also use cases on compliances on the sell side to expose trades with high profits. Advanced analytics can also show where traders might leave money on the table by comparing trade with market news and data available to the trader resulting in alerts pushed to trader to accommodate other market sentiments.

Data management

Market data analysis and consumption pattern can help reduce cost significantly. Software’s can priorities news feeds based on trading style, optimize news feed based on relevance. This will allow COO’s to reduce cost of data feed by eliminating low value news & data. BI tools can further show complex relationship between news and events in the context of portfolio. Analytics of consumption of market data by front office can establish any market abuse and help in compliance and surveillance use cases. 

Use of different version of counterparty, instrument and product reference data is resulting in trade inefficiencies and reporting across front, middle and back office.  Analytics can be used to access data quality and bottlenecks around processes. Moreover RPA can be used to repair the data. Blockchain technology can also be used create an unambiguous sharing of ref data across the Organization.

Post trade operations

Post trade processes are disrupted the most in the era of distributed ledge, utilities and CLOUD platforms.

Clearing and settlements are subjected to risks like counterparties not able to provide cash or securities as obliged. T+2, T+3 settlements also means firms have to model all assets available at future point to optimize collateral management.  Application of Blockchain could address all these issues and make large number of process and human interventions redundant. Australian equity market is investing on simplifying and seeding up post-trade processing using blockchain. NASDAQ and R3 have already taken steps to issuance of share to private investor using blockchain technology. Blockchain’s ability to tokenize assets could mean commodities like GOLD can change ownership without physically moving it.

Collateral management will be subjected to RPA to address cost and quality issues in the process like margin calculation, margin calls and valuation.

In custody and asset services space potential benefits can be derived in entitlement capture, election instruction, payment an reconciliations using RPA. Use of distributed ledge technology might in long term provide an immutable asset ledge.

Treasury management systems can be externalized by introducing CLOUD based solutions. Deploying RPA & analytics can provide realtime view of cash balance and enable real time decision making.

PRA can play a key role in reducing headcount and time to complete reconciliation. Analytics coupled with AI can start to address upstream issues to prevent breaks. CLOUD and Visualization techniques coupled with BPO services can further optimize cost of Reconciliation process.

Data quality of upstream systems are becoming critical for complex transaction reporting across multiple regions (Dodd-Frank, EMIR, MiFID II and REMIT etc). There is an opportunity to use RPA, AI and analytics to drive more data quality. In long run if Blockchain replaces post-trade processing, regulators will have access to all transaction and can build the reporting capabilities on top of it.

Risk

Post crisis regulations such as Basel III, Dodd-Frank, FRTB, IFRS 9, CRS and BCBS 239 require better risk management. Risk function has integral part of trading and exposures are monitored proactively. In this new world CRO’s play critical role in applying technology to better manage risk. Development of regulation as a service platforms help simplify & automate capital assessment, tracking, monitoring and reporting works.  Risk function can use analytics to optimize balance sheet and improve ROE up-to 400 basis points by running different scenarios across regulatory ratios like Capital, funding, leverage, total loss-absorbing capacity and bank levy. Time series data can be managed as a service on CLOUD to support risk calculations.

Finance

Financial processes tend to have higher level of manual processes due to underinvestment of technology over several decades.

Due to regular change of capital requirement, banks need to respond to this change with right financial models. Moreover banks need to report (MI) the capital requirement calculation to regulators on regular basis. In such environment, banks can consider building capital management as a service utility. Also, analytics can be used to enable flexible capital calculations and model waivers across asset classes.

Financial & regulatory reporting will benefit from AI tools, which can ingest and interpret regulatory guidance.

Compliance

Finally, Compliance cost is rising on regular basis. Estimates suggest up to 40% of the total cost can be accounted for compliance. In this ever complicated compliance environment, heavy use of Utility based service coupled with OCR, cognitive computing, AI and analytics can help reduce the cost and improve the accuracy across AML & trade surveillance, KYC and Anti-bribery and corruption cases.

There are many fintech & banks working to bridge the gaps mentioned above. I will be keen to know your view on where Technology can make most impact!!.