Robotics: Taking Automation to the Next Level in …

1 Robotics: Taking Automation to the next Level in capital markets R. obotics has picked up in the last 3-4 years and back of ce operations, capital market rms with a rapid growth in off-the-shelf have been using the traditional method of con gurable platforms. With signi cantly offshoring work from high cost location to low cost reduced timelines to automate manual processes locations. However, since labor arbitrage has and low investment, robotic process Automation become institutionalized, it is no longer sustainable (RPA) has become a part of cost and ef ciency to achieve further cost reductions.

2 Therefore, there programs across back of ce operations and shared has been a major focus on new digital technologies services. RPA ts in well to provide a secure and in the capital market industry. Most of the capital controlled environment, making the processes market rms are resorting to RPA as a quick and error-free. tactical solution to transform their back of ce to In capital market rms, complexity cannot be achieve cost reduction and higher ef ciency. avoided- it is a natural by product of growth and In this paper, we have presented RPA's success. There is an emerging need to solve applicability in the context of capital market back deep-rooted operational inef ciencies in a of ce operations (excluding front of ce) for fundamental way.

3 Some of the reasons for sell-side rms (Investment banks and brokerage operational inef ciency are: houses) based on our experience in performing these operations for leading clients. Gamut of applications, data movement in multiple applications requiring reconciliation robotic process Automation in capital markets High capex requirement, long gestation period to enhance or replace aged Most of the large nancial institutions have applications successfully completed robotic pilots leveraging Complex processes, changing regulatory multi-product vendors and service providers in requirements resulting in change in business the last 12 months.

4 They have now shortlisted rules RPA as the tool of choice and have carried out due Labor intensive processes, leading to diligence exercises to identify right opportunity operational risk and higher cycle time and areas for robotics within their back of ce errors operations, either outsourced or captive. To succeed in today's challenging and complex Our initial assessment of the process landscape in environment, capital market rms need to act capital market rms suggest multiple process areas swiftly with precision to maximize economies of wherein value can be derived from robotics, subject to scale of operations, Level of consolidation and scale and reduce cost per trade to penetrate new nature of information (See Figure 1).

5 Customers. In order to reduce costs in middle High RPA Applicability 1. Client services Front Of ce Client Client Client Client relationship Research 7. Enterprise onboarding insights / analytics management reporting risk management 2. Trading Pre-trade Order Trading Trade Post-trade analytics management risk management execution analytics market risk 3. Trade support Middle Of ce Trade Pricing and Risk enrichment P&L monitoring and Trade capture valuations and validation management limit management Credit risk 4. Cross product operations Back Of ce Settlement Data Collateral Con rmations Asset servicing and margin and payments management management Operational risk Treasury Fees Transaction Tax Reconciliations operations andinvoicing reporting operations 5.

6 Financial control Liquidity risk Functions Financial Regulatory Financial capital Product control Support control reporting reporting management 6. Legal and Compliance Business Anti-money Legal Tax and continuity KYC Audit management laundering reporting accounting Figure 1:RPA applicability areas in capital market rms 2. We have seen early success in areas of transaction Apart from that, 100% pre-matching is being done reporting, reconciliations, and settlements and on touchpoints and there has been a payments processes over the last 12 months. This 70% reduction in trade fails through standardized has resulted in signi cant reduction in transaction approach and narrations.

7 The pre-matching work time (30-70%), accuracy improvement (70- 90%) was centralized by asset class and proactive and effort reduction on in-scope FTEs (above 40%). pre-matching using RPA, thereby improving ability to focus on matched fails reduction. Let us consider the case of deployment of robotics in a client's pre-matching process, which was Why would RPA succeed in capital completely manual. A pre-matching process markets? typically involves extracting a report, identifying As revenues and operating margins in the capital unmatched trades, checking agent updates and market industry continue to decline on account of calling/emailing counterparties to resolve evolving regulations, enhanced liquidity, capital discrepancies and updating narrations with requirements and new emerging technologies, the comments.

8 This process, which is performed focus is on simpli cation and rede ning business across asset classes cash equity, xed models to ensure growth and sustainability in this income, prime brokerage and stock borrow loan, challenging environment. faced numerous challenges related to manual Most of the capital market rms work in silos and effort involved in pre-matching the trades and have a number of legacy systems. Replacing these sometimes, not all trades were pre-matched legacy systems require signi cant cost and time, before the value date. Also, there were multiple and with shrinking margins, most of the rms do instances wherein multiple analysts were sending not have budgets for huge investment in multiple queries for un-matched trades to a single technology.

9 RPA can help them bring those counterparty contract. Post robotics deployment in ef ciencies without much investment. Further, the pre-matching process more than 80% of the there has been increased scrutiny by market manual effort in the process was automated regulators, high volume of data and dif culty in (See Figure 2). integrating different legacy systems with new technologies. Pre-Matching Process Steps Involved Identifying Checking Calling / emailing Resolving Agreeing &. Report extraction unmatched trades agent updates counterparties discrepancies updating comments Asset Class APAC.

10 $ $. EMEA. $. US. Stock borrow Cash equity Fixed income Prime brokerage loan (SBL). Figure 2: RPA implementation in pre-matching process 3. RPA is enabling capital market rms to overcome Reporting: RPA can be useful in creating and these challenges by automating middle and back sending annual and quarterly reports to regulators operations. Robots can handle seasonal increase in and in standardizing client reporting. Robotics can volume of data without adding additional extract information from different internal headcounts. Further, an RPA platform maintains and external systems, compare the information an audit trail for each step/activity of a process, across systems and highlight the variances.